HBIM and BEM association: Systematic literature review

Shoeboxer: An algorithm for abstracted rapid multi-zone urban building energy model generation and simulation

Cultural heritage conservation and restoration work is a complex process that includes documentation, data collection, interpretation and production. By integrating the BIM (Building Information Modeling) methodology into this process, the concept of HBIM (Historic Building Information Modeling) has been formed. In this article, the progress of this process with the HBIM methodology in the restoration, protection and management studies of cultural heritage buildings and sites requiring collective and holistic work, the evaluation of access to the information obtained, and the provision of interdisciplinary information exchange were analyzed. By using the SWOT analysis method, the opportunities and threats offered by using the HBIM working methodology were evaluated and the strengths and weaknesses of the HBIM technology were determined. As a result of the SWOT analysis, it has been determined that the HBIM application will positively contribute to the heritage structures and increase in the direction of potential opportunities by eliminating the weaknesses.

Co-simulation of dynamic underground heat transfer with building energy modeling based on equivalent slab method

Buildings account for nearly 40% of the global process and industrial greenhouse gas emissions, and within the building sector. And within the building sector, nearly 72% of the CO2 emissions are due operational carbon demand in the building sector. To meet the goals set out in the Paris Accord, we need to halve carbon emissions by the end of this decade: an aggressive and ambitious timeline. It has become an immediate and urgent need to design and construct buildings that are minimally intrusive in their impact on the environment and operate efficiently. Improvement of the building's energy performance must begin at the early design stage as the potential for sustainable intervention in the project's early phases is higher. The opportunity to improve building performance as the design progresses, is constantly reducing, while the cost of optimization is constantly increasing. One of the major design variables impacting the performance at the early phase is the building morphology/form and its associated variables. Sensible optioneering of the building form and its variables at the early stages of design - especially the conceptual design stage - can help improve the performance of the design early on in the design process at minimum cost. However, for effective early-phase design optimisation, there is a need to develop tools/methods that allow instantaneous evaluation of a large design sample space without much “lag” between the design and performance evaluation workflows. Also, in regular early phase sustainable design workflows, multiple stakeholders - like the designer, the performance analyst, etc. - are involved, which leads to a cognitive divide in the design process. For instance, while the architect designs the initial conceptual massing with a functional design intuition, the performance analysts suggest design interventions with a performance oriented design intuition. This cognitive divide leads to a dipartite design cognition in early phase design. The underlying premise of this research is to support the notion of blurring the dichotomy between conflicting design intuitions through exploring Human + Artificial Intelligence (AI) synergies and their underlying foundational technological requirements with respect to early phase design, to enable intuitive high performance design scenarios with a centralized design cognition where there are no other stakeholders other than the designer and the design environment. With the paradigm shift of other industries towards Machine Learning (ML) and AI, recent research advances in ML and the increasing availability of Big-data in the AEC industry have bolstered multivariate problems like building performance evaluation to a great extent. Design optioneering with instantaneous performance feedback through a ML method called Surrogate Modelling is an upcoming and promising methodology, which delivers feedback based on knowledge through available data, rather than simulation. Also, paradigms in Concurrent Human Machine Interaction (HMI) have explored avenues of augmenting the architectural design process through data-driven approaches. The type of data (input-output pairs) forming the basis for these paradigms depend on the target problem at hand. For early phase performance optimization - especially energy use optimization - Building Energy Model (BEM) forms the primary data. The US Department of Energy defines BEM as a versatile, multipurpose tool that is used in new building and retrofit design, code compliance, green certification, qualification for tax credits and utility incentives, and even real-time building control. BEM is also used in large-scale analyses to develop building energy-efficiency codes and inform policy decisions. A comprehensive BEM dataset that is large and accessible can support the growing interest in ML and HMI research in the high performance building design field. However, common techniques to acquire large BEM datasets like manual 3D energy modeling and simulation, 3D scanning, etc. are very tedious and time consuming. Also, existing datasets are usually incomplete, inconsistent and very difficult to access, owing to data privacy and open-access issues. And lastly, these datasets are fixed, static and cant be easily reproduced for different use case scenarios, nor scalable to adapt to needs. This research aims to tackle this problem by introducing a novel framework to generate custom problem-specific synthetic BEM dataset that generates a user defined amount of context specific 3D early phase building geometries and their associated BEM models, that is suitable for ML and HMI research. Synthetic datasets generated with this framework offer flexibility and customization in the generation process, making these datasets modular, reproducible and scalable. The framework uses the concepts of Generative Design, Geometry Manipulation, Simulation and Computational Automation to build the dataset. The dataset is qualified through the concepts of Preservationism and Sustainability, which are discussed in further sections of this article. The research identifies the importance and multifacetedness of the impact of building geometry on its performance, and demonstrates the application of generated synthetic BEM datasets by developing an enactive, conversational design environment that allows the designer to make real-time sustainable design decisions based on instantaneous machine feedback, for an intuitive, centralized design intuition.

The design and evaluation of virtual learning environments for construction and surveying students is presented in this paper; by combining virtual learning environment and on-site student surveys to model and replicate practice in the architectural heritage sector. The Virtual Learning Environment is enhanced with real live survey projects whereby students collect the data to build virtual historic buildings from onsite surveys using advanced survey equipment. The survey data is modelled in HBIM; Historic Building Information Modelling (HBIM) is currently being developed as a virtual learning tool for construction and surveying students in the Dublin Institute of Technology. HBIM, is a novel solution whereby interactive parametric objects representing architectural elements are constructed from historic data, these elements, including detail behind the scan surface are accurately mapped onto a laser or image based survey. The architectural elements are scripted using a Geometric Descriptive Language GDL. In the case of this project a Virtual Learning Environment is being developed which combines advanced recording and surveying with Building Information Modelling (BIM) to simulate and analyse existing buildings.

Building Information Modeling (BIM) efficiently integrates environmental analysis into the design and delivery of high-performance buildings. Building Energy Modeling (BEM), a subset of BIM, employs various simulation tools for predicting the environmental performance of buildings. As the demand for high-performance buildings has increased, BEM has facilitated the delivery of buildings that meet expected performance requirements. The research objectives were to: 1) evaluate various BEM tools, and 2) develop guidelines for using BEM tools in design and delivery of high-performance buildings. Twelve BEM tools were evaluated using four criteria: interoperability, user-friendliness, available inputs, and available outputs. The top three programs (Autodesk Ecotect, Autodesk Green Building Studio, and IES ) were selected based on this evaluation. Each of these selected BEM tools was used in the case study to simulate energy consumption, daylighting performance, and natural ventilation for two buildings, one LEED certified and one non-LEED certified. The results of the case study were used to compare the environmental performance of the two buildings and to develop guidelines for using BEM tools to analyze building environmental performance.

In Europe, the energy renovation of the existing building stock is a great opportunity to significantly reduce energy consumption and greenhouse gas (GHG) emissions and reach the European sustainability targets. In this framework, building energy simulations (BES) tools are very useful in verifying energy retrofit measures' effectiveness and compliance with national standards. However, an inaccurate numerical prediction, the so-called “performance gap” between measured and numerical performance, is often obtained, mainly due to the inherent uncertainty of model input. Due to its stochastic nature, the occupants’ behavior (OB) is considered among the key contributors to this gap. However, the most recent Building Energy Model (BEM) approaches adopt deterministic hourly-defined profiles for characterizing OB, thus neglecting the related uncertainty. In this work, the impact of OB uncertainties on energy consumption (EC) prediction is evaluated by adopting a Karhunen-Loève Expansion sampling technique, used to randomly perturb OB profiles such as heating setpoint (HS), internal thermal loads (IL), and windows opening (NV). Two BEMs of a typical Italian residential building in pre- and post-renovation scenarios are considered and calibrated on real EC data. The results demonstrated that HS uncertainty has the highest impact on EC in all scenarios. Moreover, the higher the energy performance of the building, the higher the impact of OB, especially for IL and NV patterns.

Improving accuracy in building energy simulation via evaluating occupant behaviors: A case study in Hong Kong

Recent technological evolutions in the acquisition and management of building data are offering new opportunities for digital reconstruction. At the same time, the BIM (Building Information Modeling) methodology, based on the implementation of libraries composed of parametric objects provided by the IFC (Industry Foundation Classes) standard, allows the design and management of data of existing buildings, and, in particular, historical and archaeological buildings. In the latter case, the great variety of Cultural Heritage (CH) distributed over the European territory, and the ability of BIM to cover the life of buildings or/and other artefacts from a geometric, descriptive, physical and static point of view, have stimulated the development of the HBIM (Historic BIM) modelling. The HBIM approach should consider the complexity of historical or archaeological buildings or artefacts, with particular attention to possible fragmentation or incompleteness of parts. In this work, different approaches regarding the survey, restitution and data management will be described, finalised to the construction of an HBIM model, considering different possible variables, emerging from different study cases.

<p>Designers from the Architecture, Engineering, and Construction (AEC) industries have shown a desire to allow for quantitative data to back up sustainable decision-making (Braasch, 2016). Methods and software used to reach this goal often do not provide all the information to make informed design decisions or require a complete remodelling of designs at each stage. These factors make Building Performance Simulation (BPS) feasible at early design stages, where it is most beneficial for Architects. This thesis explores the current process to translate Architectural models constructed within a Building Information Modelling (BIM) environment into Building Energy Models (BEM) so that performance simulations can take place. Within the aim of exploring translation processes, the objectives were to document: • Whether current processes can facilitate modelling of environmental building performance during early design, as well as during developed design? • Whether there are any common problems or successful approaches that might form the basis of future improvements in the way Architect’s and consultant’s models work together? This thesis has identified 19 translation processes from current literature and examined a range of representative processes for exchanging information between Architectural modelling and BPS programs. It concluded that translation issues can be classified into similar groups based on the overall processes used. The eight categories of issues can be used by future developers to determine their priorities in development, and those looking for a current solution can adopt one for themselves. None of the processes tested allowed for issue-free modelling of building performance during sketch design. The two types of building translation schema evaluated in this thesis divided identified references between a dedicated and generalised approach. The dedicated approach of gbXML and the generic approach of IFC identified similar issues; however, IFC contained more of these problems because it communicates with all modelling programs at a lower information quality. Due to the generic approaches containing more issues that take longer to solve, it is currently more complicated to generate an energy model out of IFC data. While the gbXML schema can only provide benefits for BPS related translations, it is the most viable way to provide the service.</p>

Interoperability and data exchange within BIM platform to evaluate building energy performance and indoor comfort

The management of cultural landscapes with protected historic buildings faces challenges due to these structures’ unique characteristics and scale. Semantically enriched 3D modeling methods, like Historic Building Information Modeling (HBIM) integrated with Historic Geographic Information Systems (HGIS), offer a multi-scale approach to documenting and conserving cultural heritage, from building components to territorial levels. This study explores the integration of HBIM-HGIS for multi-scale digital documentation of architectural heritage, focusing on modern architecture designed by Oscar Niemeyer in 1944, located in Belo Horizonte, Brazil. An exploratory qualitative approach is used to create a highly detailed model of the ensemble, utilizing point clouds generated by terrestrial laser scanning and drone photogrammetry as data for model development in Revit. The geometric and semantic information of the model is then exported in IFC format and integrated into a Geodatabase, following the integration of HBIM and HGIS. The study demonstrates that a 3D semantic model integrating HBIM with HGIS enhances preservation efforts. It enables detailed analyses for decision-making and offers a comprehensive understanding of heritage across scales, including landscapes. This holistic approach supports the effective conservation of architectural heritage by unifying tangible and intangible data within a single platform.

The Italian building stock consists of buildings mainly constructed until the mid-20th century using pre-industrial construction techniques. These buildings require energy refurbishment that takes into account the preservation of their architectural heritage. In this view, this work studies an innovative integrated modelling and simulation framework consisting of the implementation of Historical Building Information Modeling (HBIM) for the energy retrofit of historical buildings with renewable geothermal HVAC system. To this aim, the field case study is part of a medieval complex in Central Italy (Perugia), as representative ancient rural offshore architecture in the European countryside. The system involves of a ground source heat pump, a water tank for thermal-energy storage connected to a low-temperature radiant system, and an air-handling unit. The building heating energy performance, typically influenced by thermal inertia in historical buildings, when coupled to the novel HVAC system, is comparatively assessed against a traditional scenario implementing a natural-gas boiler, and made inter-operative within the HBIM ad hoc platform. Results show that the innovative renewable energy system provides relevant benefits while preserving minor visual and architectural impact within the historical complex, and also in terms of both energy saving, CO2 emissions offset, and operation costs compared to the traditional existing system. The integrated HBIM approach may effectively drive the path toward regeneration and re-functioning of heritage in Europe.

Recently, interoperability between BIM (Building Information Model) and BEM (Building Energy Model) has been highlighted. Even though it has been widely recognized that there are significant potentials in BIM by data sharing and reuse, BIM has not been actively utilized for building energy simulation. With this in mind, in this paper, the authors investigated several issues: (1) limitation of Industry Foundation Class (IFC) and BIM authoring tools, (2) immature IFC data schema, (3) data mapping problem between BIM and BEM. Firstly, IFC files exported from major BIM authoring tools are not consistent with each other and don't include significant thermal parameters. In addition, building geometry, e. g. underground wall, is not properly exported. IFC data schema are not ready to describe detailed information on thermal and dynamic properties (efficiency, performance curves, etc.) of mechanical systems (HVAC, AHU), delivery systems (fans, pumps), and plants (boilers, chillers), which are very essential for BEM. Finally, most of the efforts on BIM-to-BEM are focused on data conversion (data-driven approach), without considering dynamic architectural design process which involves many different stakeholders. In near future, BIM-to-BEM interface should take into account design context and rational decision making so called 'process-driven approach'.

Simulations of local heat islands in Zürich with coupled CFD and building energy models