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Results for “Building Information Modeling”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Enhancing occupant behavior representation for interoperability between building information modeling and building energy modeling

Building Performance Simulation (BPS) has been adopted as an essential tool for designing, operating, and retrofitting buildings to optimize energy efficiency throughout the building life cycle. The Green Building XML (gbXML) schema facilitates seamless data exchange between Building Information Modeling (BIM) and Building Energy Modeling (BEM) software tools. However, limited occupant behavior (OB) representation in BIM often leads to inconsistent and inaccurate energy simulation in BEM software. This paper presents 154 systematic enhancements to the existing occupant behavior XML (obXML) schema v1.3.4, initially developed for standardizing OB representation for BEM, to address existing limitations and improve interoperability with BIM models. The enhancements encompass improved integration with BIM models through extended building representations and system operations, expanded support for advanced OB models with additional environmental parameters and mathematical capabilities, and implementation of a standardized model documentation framework. To facilitate seamless data transformation between gbXML and obXML schemas, we developed a publicly available gb-obXML Schema Converter. Three case studies demonstrate the enhanced schema’s capabilities: representation of building information using a two-story office building model, documentation of a window operation behavior model, and validation of the schema converter’s functionality. The enhanced obXML schema v1.4 enables sophisticated modeling of occupant-building interactions while maintaining consistency with industry-standard BIM schemas. The standardized documentation framework facilitates reproducibility and knowledge sharing in the OB research community, while the schema converter automates the integration of building information into OB simulation workflows. These enhancements establish a foundation for more accurate building performance simulation by supporting sophisticated representation of occupant behavior within the BIM-to-BEM simulation workflows.

Chung, Jihoon↗
DOE OSTI2015

Automatic building information model query generation

Energy efficient building design and construction calls for extensive collaboration between different subfields of the Architecture, Engineering and Construction (AEC) community. Performing building design and construction engineering raises challenges on data integration and software interoperability. Using Building Information Modeling (BIM) data hub to host and integrate building models is a promising solution to address those challenges, which can ease building design information management. However, the partial model query mechanism of current BIM data hub collaboration model has several limitations, which prevents designers and engineers to take advantage of BIM. To address this problem, we propose a general and effective approach to generate query code based on a Model View Definition (MVD). This approach is demonstrated through a software prototype called QueryGenerator. In conclusion, by demonstrating a case study using multi-zone air flow analysis, we show how our approach and tool can help domain experts to use BIM to drive building design with less labour and lower overhead cost.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Automated Progress Monitoring in Modular Construction Factories Using Computer Vision and Building Information Modeling

Modular construction methods have recently gained interest due to the advantages offered in terms of safety, quality, and productivity for projects. In this method, a significant portion of the construction is performed off-site in factories where modular components are built in different workstations, assembled on the production line, and shipped to the site for installation. Due to the labor-intensive nature of tasks, cycle times in modular construction factories are highly variable, which commonly leads to major bottlenecks and delays in construction projects. To remedy this effect, recent methods rely on sensors such as RFID to monitor the production process, which is reportedly expensive, and intrusive to the work process. Recently, computer vision-based methods have been proposed to track the production process in modular construction factories. However, these methods overlook monitoring the assembly process on the production line. Therefore, this paper presents a method to monitor the assembly process by integrating computer vision-based methods with Building Information Modeling (BIM). The proposed method detects the modular units using object segmentation; superimposes the installation area with the corresponding 2D region using BIM, and identifies the installation of the components using image processing techniques. The proposed method has been validated using surveillance videos captured from a modular construction factory in the US. Successful implementation of the proposed method can lead to timely identification of delays during the assembly process and reduce delays in modular integrated construction projects.

building information modeling↗
DOE OSTI2013

A BIM-based system for demolition and renovation waste estimation and planning

Highlights: ► We developed a waste estimation system leveraging the BIM technology. ► The system can calculate waste disposal charging fee and pick-up truck demand. ► We presented an example scenario demonstrating this system. ► Automatic, time-saving and wide applicability are the features of the system. - Abstract: Due to the rising worldwide awareness of green environment, both government and contractors have to consider effective construction and demolition (C and D) waste management practices. The last two decades have witnessed the growing importance of demolition and renovation (D and R) works and the growing amount of D and R waste disposed to landfills every day, especially in developed cities like Hong Kong. Quantitative waste prediction is crucial for waste management. It can enable contractors to pinpoint critical waste generation processes and to plan waste control strategies. In addition, waste estimation could also facilitate some government waste management policies, such as the waste disposal charging scheme in Hong Kong. Currently, tools that can accurately and conveniently estimate the amount of waste from construction, renovation, and demolition projects are lacking. In the light of this research gap, this paper presents a building information modeling (BIM) based system that we have developed for estimation and planning of D and R waste. BIM allows multi-disciplinary information to be superimposed within one digital building model. Our system can extract material and volume information through the BIM model and integrate the information for detailed waste estimation and planning. Waste recycling and reuse are also considered in our system. Extracted material information can be provided to recyclers before demolition or renovation to make recycling stage more cooperative and more efficient. Pick-up truck requirements and waste disposal charging fee for different waste facilities will also be predicted through our system. The results could provide alerts to contractors ahead of time at project planning stage. This paper also presents an example scenario with a 47-floor residential building in Hong Kong to demonstrate our D and R waste estimation and planning system. As the BIM technology has been increasingly adopted in the architectural, engineering and construction industry and digital building information models will likely to be available for most buildings (including historical buildings) in the future, our system can be used in various demolition and renovation projects and be extended to facilitate project control.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Issues in Bi-Directional Interoperability between BIM and BEM

The state-of-the-art interoperability between Building Information Modeling (BIM) and Building Energy Modeling (BEM) is mainly one-way. BEM software like EnergyPlus takes design input from BIM and simulates the energy consumption of the building. BIM, however, is unable to leverage energy simulation results from BEM smoothly. This lack of bi-directional interoperability between BIM and BEM prevents buildings from seeking more energy-efficient design options and limits BIM applications in optimal generative design. In this research, the authors have conducted the following activities related to two-way interoperability between BIM and BEM: (1) surveyed its current status through literature review, (2) investigated barriers to the bi-directional interoperability, and (3) suggested possible approaches to enable bi-directional interoperability and research outlook in the field. As a result, the authors have identified three main barriers to BIM BEM interoperability, namely, inefficient collaboration, limited scope in information transformation, and lack of BEM to BIM transformation. Future directions are suggested to address these barriers.

building design↗
DOE OSTI2023

Data Reliability in BIM and Performance Analytics: A Survey of Contemporary AECO Practice

As awareness around building energy consumption increases, practitioners are encouraged to consider performance aspects regarding the built environment more closely and find ways to improve its efficiency. Improvements in building information modeling (BIM) and building performance simulation (BPS) tools present opportunities to facilitate information communication with a wider range of stakeholders. The building sector can benefit from the integration of performance informatics; however, there has been limited success in utilizing available technologies that promote data integration and management in favor of enriching our knowledge and understanding of buildings as artifacts of information. This phenomenon was investigated by conducting a survey, together with a review of relevant literature, to depict the relevant challenges and opportunities for the architecture, engineering, construction, and owner-operated (AECO) industry, as it undergoes digital transformation, as well as the working practices that have formed around them. It is argued that the current tools available to practitioners do not support effective data serialization between design and analytics processes, affecting the collaboration between team members. Lastly, a series of functional goals are proposed to support a higher level of reliability in the ways information is mobilized, by rethinking the technologies and methods for organizing information systems.

42 ENGINEERING↗
DOE OSTI2024

A semantics-driven framework to enable demand flexibility control applications in real buildings

Decarbonising and digitalising the energy sector requires scalable and interoperable Demand Flexibility (DF) applications. Semantic models are promising technologies for achieving these goals, but existing studies focused on DF applications exhibit limitations. These include dependence on bespoke ontologies, lack of computational methods to generate semantic models, ineffective temporal data management and absence of platforms that use these models to easily develop, configure and deploy controls in real buildings. This paper introduces a semantics-driven framework to enable DF control applications in real buildings. The framework supports the generation of semantic models that adhere to Brick and SAREF while using metadata from Building Information Models (BIM) and Building Automation Systems (BAS). The work also introduces a web platform that leverages these models and an actor and microservices architecture to streamline the development, configuration and deployment of DF controls. The paper demonstrates the framework through a case study, illustrating its ability to integrate diverse data sources, execute DF actuation in a real building, and promote modularity for easy reuse, extension, and customisation of applications. The paper also discusses the alignment between Brick and SAREF, the value of leveraging BIM data sources, and the framework's benefits over existing approaches, demonstrating a 75% reduction in effort for developing, configuring, and deploying building controls.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

An overview of data tools for representing and managing building information and performance data

Building information modeling (BIM) has been widely adopted for representing and exchanging building data across disciplines during building design and construction. However, BIM's use in the building operation phase is limited. With the increasing deployment of low-cost sensors and meters, as well as affordable digital storage and computing technologies, growing volumes of data have been collected from buildings, their energy services systems, and occupants. Such data are crucial to help decision makers understand what, how, and when energy is consumed in buildings—a critical step to improving building performance for energy efficiency, demand flexibility, and resilience. However, practical analyses and use of the collected data are very limited due to various reasons, including poor data quality, ad-hoc representation of data, and lack of data science skills. To unlock value from building data, there is a strong need for a toolchain to curate and represent building information and performance data in common standardized terminologies and schemas, to enable interoperability between tools and applications. This study selected and reviewed 24 data tools based on common use cases of data across the building life cycle, from design to construction, commissioning, operation, and retrofits. The selected data tools are grouped into three categories: (1) data dictionary or terminology, (2) data ontology and schemas, and (3) data platforms. The data are grouped into ten typologies covering most types of data collected in buildings. This study resulted in five main findings: (1) most data representation tools can represent their intended data typologies well, such as Green Button for smart meter data and Brick schema for metadata of sensors in buildings and HVAC systems, but none of the tools cover all ten types of data; (2) there is a need for data schemas to represent the basis of design data and metadata of occupant data; (3) standard terminologies such as those defined in BEDES are only adopted in a few data tools; (4) integrating data across various stages in the building life cycle remains a challenge; and (5) most data tools were developed and maintained by different parties for different purposes, their flexibility and interoperability can be improved to support broader use cases. Finally, recommendations for future research on building data tools are provided for the data and buildings community based on the FAIR principles to make data Findable, Accessible, Interoperable, and Reusable.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2012

A comparison of thermal zone aggregation methods

The impact of increasing energy prices on building operation budgets has fueled demand for more energy-efficient structures. Existing building energy simulation tools generate an immense amount of data yet comparatively little knowledge. This paper introduces a framework that allows aggregation-based model reduction to operate on geometric building information models. The resulting aggregation sequence provides designers with faster simulations and affords insight into complex multi-scale thermal interactions. A comparison of the trade-off between simulation speed and accuracy for three hierarchical cluster partitioning methods concludes the discussion.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2012

Creating 3D Web-Based Game Environment Using BIM Models for Virtual On-Site Visiting of Building HVAC Systems

A web-based 3D game project was presented in this paper to demonstrate the process of using building information modeling (BIM) to create an interactive 3D on-line `Green' training environment. The system architecture, the implementation process and major components of this virtual training environment were discussed. Existing studies on BIM-based collaborations mainly focused on local-file-sharing approach using proprietary applications. Limited research focused on using BIM as an online gaming platform to create a web browser-based interactive 3D virtual environment for collaboration, learning and/or training. The gap was partially caused by the lack of understanding how to implement a BIM-based game in web browser environment. In this paper, the authors provided an implementation example using a hospital BIM model to create an interactive web-based 3D BIM game environment to allow users to visualize and interact with the BIM components using regular web browsers. The intention of this project is to create a proprietaryindependent training environment to conduct energy re-commissioning trainings for hospital facility management staff. This virtual BIM environment can potentially be customized for engineering student learning and project collaborations as well. The conclusion was that current BIM and game technology are mature enough to allow us to create serious web-based interactive learning/training virtual environment. The successful integration of BIM and web browsers paved the way for many learning and training applications, which need built-environment as context.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2013

Transforming BIM to BEM: Generation of Building Geometry for the NASA Ames Sustainability Base BIM

Typical processes of whole Building Energy simulation Model (BEM) generation are subjective, labor intensive, time intensive and error prone. Essentially, these typical processes reproduce already existing data, i.e. building models already created by the architect. Accordingly, Lawrence Berkeley National Laboratory (LBNL) developed a semi-automated process that enables reproducible conversions of Building Information Model (BIM) representations of building geometry into a format required by building energy modeling (BEM) tools. This is a generic process that may be applied to all building energy modeling tools but to date has only been used for EnergyPlus. This report describes and demonstrates each stage in the semi-automated process for building geometry using the recently constructed NASA Ames Sustainability Base throughout. This example uses ArchiCAD (Graphisoft, 2012) as the originating CAD tool and EnergyPlus as the concluding whole building energy simulation tool. It is important to note that the process is also applicable for professionals that use other CAD tools such as Revit (“Revit Architecture,” 2012) and DProfiler (Beck Technology, 2012) and can be extended to provide geometry definitions for BEM tools other than EnergyPlus. Geometry Simplification Tool (GST) was used during the NASA Ames project and was the enabling software that facilitated semi-automated data transformations. GST has now been superseded by Space Boundary Tool (SBT-1) and will be referred to as SBT-1 throughout this report. The benefits of this semi-automated process are fourfold: 1) reduce the amount of time and cost required to develop a whole building energy simulation model, 2) enable rapid generation of design alternatives, 3) improve the accuracy of BEMs and 4) result in significantly better performing buildings with significantly lower energy consumption than those created using the traditional design process, especially if the simulation model was used as a predictive benchmark during operation. Developing BIM based criteria to support the semi-automated process should result in significant reliable improvements and time savings in the development of BEMs. In order to define successful BIMS, CAD export of IFC based BIMs for BEM must adhere to a standard Model View Definition (MVD) for simulation as provided by the concept design BIM MVD (buildingSMART, 2011). In order to ensure wide scale adoption, companies would also need to develop their own material libraries to support automated activities and undertake a pilot project to improve understanding of modeling conventions and design tool features and limitations.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2014

Emerging Technologies in the Built Environment: Geographic Information Science (GIS), 3D Printing, and Additive Manufacturing

Abstract 1: Geographic information systems emerged as a computer application in the late 1960s, led in part by projects at ORNL. The concept of a GIS has shifted through time in response to new applications and new technologies, and is now part of a much larger world of geospatial technology. This presentation discusses the relationship of GIS and estimating hourly and seasonal energy consumption profiles in the building sector at spatial scales down to the individual parcel. The method combines annual building energy simulations for city-specific prototypical buildings and commonly available geospatial data in a GIS framework. Abstract 2: This presentation focuses on 3D printing technologies and how they have rapidly evolved over the past couple of years. At a basic level, 3D printing produces physical models quickly and easily from 3D CAD, BIM (Building Information Models), and other digital data. Many AEC firms have adopted 3D printing as part of commercial building design development and project delivery. This presentation includes an overview of 3D printing, discusses its current use in building design, and talks about its future in relation to the HVAC industry. Abstract 3: This presentation discusses additive manufacturing and how it is revolutionizing the design of commercial and residential facilities. Additive manufacturing utilizes a broad range of direct manufacturing technologies, including electron beam melting, ultrasonic, extrusion, and laser metal deposition for rapid prototyping. While there is some overlap with the 3D printing talk, this presentation focuses on the materials aspect of additive manufacturing and also some of the more advanced technologies involved with rapid prototyping. These technologies include design of carbon fiber composites, lightweight metals processing, transient field processing, and more.

New, Joshua Ryan↗
DOE OSTI2025

Scenario Generation for Built Environment Decision Support under Uncertainty: Case Studies of Airflow Modeling and Climate-Resilient Infrastructure System Design

When confronted with unforeseen challenges, practicing informed decision making is crucial for enhancing resilience in the built environment. While scan-to-building information modeling (BIM) is a well-established approach for creating detailed digital representations of physical assets, its application in assessing and improving infrastructure resilience remains underexplored. This study addresses this gap by proposing a novel application of scan-to-BIM, namely, scan-to-BIM-to-digital twin (S-BIM-DT) workflow. By integrating reality capture and digital twin technologies, this workflow creates continuously updated and accurate digital representations of physical assets, enabling the generation of various scenarios. Unlike traditional methods, the S BIM-DT workflow facilitates continuous model refinement, supporting informed resilience strategies. By combining these technologies into a cohesive process, the workflow facilitates decision making under uncertainty, enabling stakeholders to evaluate and respond to various scenarios effectively. We demonstrate the implementation of the S-BIM-DT workflow through two use cases that highlight its capability to enhance resilience at different scales. The first use case involves the Combined Transportation, Emergency, and Communications Center (CTECC) in Austin, Texas. BIM-enriched computational fluid dynamics (CFD) modeling simulates airflow and develops alternative scenarios for optimizing the heating, ventilation, and air conditioning (HVAC) systems. This approach enhances resilience against airborne health threats in a postCOVID context. The second use case focuses on designated areas within Beaumont, Texas, as part of the Southeast Texas Urban Integrated Field Laboratory (SETx-UIFL) research. By developing inundation maps to assess extreme weather events, this modeling aids in preparedness efforts and informs the development of climate-resilient infrastructure in vulnerable neighborhoods. Results indicate that the S-BIM-DT workflow effectively generates scenarios that enhance resilience in the built environment by facilitating informed decision making. Furthermore, this study serves as a bridge between advanced scan-to-BIM methodologies and the practical strategies needed to improve built infrastructure resilience.

Built environment↗
DOE OSTI2019

Innovative Hot Lab Concept for Advanced D and D Application - 19175

Hot Labs are used in the nuclear industry for various purposes: maintenance of nuclear reactor, sampling and testing of fuel, inspection activities and decommissioning. Despite their vast use, their current designs and operations do not meet entirely today's needs and requirements of the operations nor tomorrow's. This paper will give an overview of the research and investigations performed around Hot Cells design and concept in order to integrate new operability modes and functions. The overall idea is to bring modularity, flexibility and adaptability to the Hot Lab nuclear industry. Taking the key principles of Model Based System Engineering, an interoperable data model, the most advanced digital technologies (Building Information Modelling - BIM, Virtual Reality / Augmented Reality, Artificial Intelligence), and looking at all the life-cycle of such a facility, a concept design of a new type of Hot Lab has been developed. Four mains aspects are implemented during this study: Implement the principles of the Industry 4.0; use modular and flexible solutions; explore the concept of in service maintenance and predictive maintenance; optimise the decommissioning and dismantling process by taking into account the entire life-cycle of the facility. The design was developed as a case study taking several assumptions to adapt to any project. The design developed demonstrates that modularity and flexibility can be brought in without compromising the core safety functions of such a facility. This Hot Lab concept brings the current Hot Lab to the next level as the design has been adapted to meet the current operational needs, implement novel ideas and consider its entire life-cycle. This paper will demonstrate how decommissioning and dismantling operations can become more efficient and safer with such a concept. In addition, the Model Based System Engineering approach used from the beginning of the design phase allows to have an optimum architecture during its entire lifetime. It also allowed to flag new topics to be further developed for the benefit of the nuclear industry as a whole. A first example would be the development of the Control System using digital tools and artificial intelligence to run remotely controlled equipment inside the Hot Lab. Assystem is an international engineering group. As a key participant in the nuclear industry for over 50 years, the Group supports its clients in managing their capital expenditure throughout their asset life-cycles. Assystem can offer support in project management, design, digital engineering, industrial control systems, security and safety and industrial digitalisation. Assystem's Imagine program is an internal program intending to serve as an incubator for the development of innovations. The Innovative Hot Lab project integrates one of the four innovation projects Assystem choose to develop and invest in. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2026

Alchemy: A Model-Based Approach for 2D to 3D Autonomous Nuclear System Design

Engineering design of nuclear power plant (NPP) piping and equipment systems frequently bypasses crucial 2D system planning, instead moving straight to 3D modeling. This often leads to designs that exceed building envelope constraints, forcing expensive and time-consuming redesigns. When 2D modeling is employed, it typically involves labor-intensive manual workflows that convert 2D drawings into 3D models, resulting in inefficiencies and errors across design iterations. These workflows further suffer from poor software interoperability and dependence on proprietary software ecosystems, thereby contributing to schedule delays and cost overruns. This paper presents Alchemy, an autonomous framework that transforms 2D system definitions into Industry Foundation Classes (IFC)-compliant 3D building information models (BIMs) for expediting nuclear facility design at the conceptual preliminary phase. Using a model-based approach, the framework treats the 2D system diagram as the central reference model employed to automatically generate all subsequent outputs, ensuring consistency between the system definition and the resulting physical design. A web-based interface enables engineers to define hierarchical system topologies including associated equipment, geometric properties, and connectivity requirements. A two-phase equipment layout optimization algorithm automatically computes collision-free spatial configurations within predefined building envelopes. An artificial intelligence (AI)-assisted pipe routing module then generates orthogonal, collision-free routing paths, allowing the user to select either an A* search-based method or an Ant Colony Optimization (ACO)-based method. All outputs are authored natively in IFC format, relying on open-source technologies and standardized formats in order to ensure extensibility and eliminate proprietary software dependencies. The proposed framework is validated on two representative pressurized-water reactor (PWR)-based case studies, for which it autonomously generates IFC-compliant 3D models in minutes, drastically reducing workflows that typically require hours of manual effort. The generated model demonstrates topologically correct equipment placement, physically plausible spatial relationships, and collision-free pipe routing consistent with known PWR loop configurations. This work represents a foundational step toward digital engineering for nuclear facility preliminary design, with future ongoing development targeting design code compliance and expanded system complexity.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Improving and Automating Building Model Data Exchange

There are many instances throughout a project’s lifecycle where there arises a need for quick and accurate risk assessment of building designs. For example, an unexpected design change during construction may necessitate structural engineers to perform a seismic risk assessment on analytical models of the updated building design using high fidelity structural analysis software, such as ANSYS or Abaqus. However, the efficiency of such workflows often depends upon the interoperability of architectural design software and structural analysis software. When the quality of this interoperability is lacking or even non-existent, the efficiency of virtual engineering workflows is hampered, which increases project costs. A McGraw Hill industry survey of professional users of Building Information Modeling (BIM) technologies found that there is high demand for BIM interoperability for structural analysis, but that the value/difficulty ratio is currently too low for practical use. There have been efforts by the academic community to facilitate model data exchange between the architectural design and structural analysis domains, but such solutions have not been widely adopted by industry, face technical challenges, and oftentimes are limited in applicability for users of various BIM software. Therefore, INL is developing capabilities to improve, automate, and generalize model data exchange between architectural BIM software (e.g., Revit) and structural analysis software (e.g., SAP2000, ANSYS). The goal is to help expedite and automate as much of the pre-processing step for creating analytical models in finite element analysis software as reasonably as possible. Such a "BIM-to-FEA" conversion tool should provide direct benefit to end-users through accuracy, automation, quick turn-around, and wide applicability. To generalize the application of this BIM-to-FEA conversion tool and increase its useability among the many different commercial BIM software currently used by industry, the program is being developed with the concept of openBIM. OpenBIM is the application of non-proprietary, open data standards that allow for BIM model data exchange in a format that is accessible, retainable, and useable for all users. The most widely used open, non-proprietary data exchange format for BIM is the Industry Foundation Classes (IFC) schema. IFC is developed by buildingSMART international and is ISO certified (ISO 16739-1:2018). The BIM-to-FEA conversion tool is being developed for compatibility with typical commercial building designs of steel framed structures. The tool is currently capable of importing architectural BIM data of framed building structures, recognizing and extracting the aspects of the model that are required for structural analysis, adjusting the connectivity of frame members, and finally exporting to an analytical model stored in the IFC format. The exported IFC analytical model can then be imported into various openBIM compliant software, such as SAP2000. Such capabilities have already been tested on commercial software, as shown above, and continue to be improved. Work is underway to test the conversion on various commercial BIM software, develop a user-friendly interface, incorporate the program into the broader DeepLynx data warehouse project being developed by INL, and to eventually open-source the tool for the benefit of the community. Future development of the tool envisions the ability for efficient iterative risk assessment of generative building designs, all within a workflow utilizing open-source tools. One such open-source tool will be MOOSE, an advanced finite element analysis tool developed at INL. The conversion tool will also branch out from typical commercial building designs and will aim to incorporate nuclear construction. The aim will be to convert both structural and non-structural components of nuclear facilities, such as curved concrete containment structures and piping systems, respectively.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Deep Point Cloud Building Envelope Segmentation (DeeP-CuBES) using Deep Learning

Building Information Modeling (BIM) plays an important role in building design and construction, particularly for achieving energy-efficient retrofits. Building envelope retrofits using panelized prefabricated system, such as those popularized by the Energiesprong program, need accurate as-built dimensions of facade features (windows, doors, etc.) to achieve the desired thermal and air tightness. Traditionally, building surveying is done manually, resulting in a time-consuming and labor-intensive process. Recently, 3D point clouds from terrestrial LiDAR have been used to automate the generation of as-built dimensions of existing buildings. However, automated BIM using LiDAR relies on solving the point cloud semantic segmentation (PCSS) problem. In this work, we propose a robust pipeline for solving the PCSS problem using deep neural networks, focusing on overcoming challenges posed by imbalanced datasets and complex architectural features. We introduce the first high-density, labeled, and validated building envelope point cloud dataset derived from multiple building scans, specifically curated to tackle challenges in facade-level segmentation. Results from the trained neural networks show that advanced attention-based architectures and incorporating radiometry (light intensity and RGB) features significantly boost segmentation accuracy for windows and doors.

Selvakumar, Balaji [ORNL]↗
DOE OSTI2013

Virtual Design Studio (VDS) - Development of an Integrated Computer Simulation Environment for Performance Based Design of Very-Low Energy and High IEQ Buildings

Executive Summary The objective of this study was to develop a “Virtual Design Studio (VDS)”: a software platform for integrated, coordinated and optimized design of green building systems with low energy consumption, high indoor environmental quality (IEQ), and high level of sustainability. This VDS is intended to assist collaborating architects, engineers and project management team members throughout from the early phases to the detailed building design stages. It can be used to plan design tasks and workflow, and evaluate the potential impacts of various green building strategies on the building performance by using the state of the art simulation tools as well as industrial/professional standards and guidelines for green building system design. Engaged in the development of VDS was a multi-disciplinary research team that included architects, engineers, and software developers. Based on the review and analysis of how existing professional practices in building systems design operate, particularly those used in the U.S., Germany and UK, a generic process for performance-based building design, construction and operation was proposed. It distinguishes the whole process into five distinct stages: Assess, Define, Design, Apply, and Monitoring (ADDAM). The current VDS is focused on the first three stages. The VDS considers building design as a multi-dimensional process, involving multiple design teams, design factors, and design stages. The intersection among these three dimensions defines a specific design task in terms of “who”, “what” and “when”. It also considers building design as a multi-objective process that aims to enhance the five aspects of performance for green building systems: site sustainability, materials and resource efficiency, water utilization efficiency, energy efficiency and impacts to the atmospheric environment, and IEQ. The current VDS development has been limited to energy efficiency and IEQ performance, with particular focus on evaluating thermal performance, air quality and lighting environmental quality because of their strong interaction with the energy performance of buildings. The VDS software framework contains four major functions: 1) Design coordination: It enables users to define tasks using the Input-Process-Output flow approach, which specifies the anticipated activities (i.e., the process), required input and output information, and anticipated interactions with other tasks. It also allows task scheduling to define the work flow, and sharing of the design data and information via the internet. 2) Modeling and simulation: It enables users to perform building simulations to predict the energy consumption and IEQ conditions at any of the design stages by using EnergyPlus and a combined heat, air, moisture and pollutant simulation (CHAMPS) model. A method for co-simulation was developed to allow the use of both models at the same time step for the combined energy and indoor air quality analysis. 3) Results visualization: It enables users to display a 3-D geometric design of the building by reading BIM (building information model) file generated by design software such as SketchUp, and the predicted results of heat, air, moisture, pollutant and light distributions in the building. 4) Performance evaluation: It enables the users to compare the performance of a proposed building design against a reference building that is defined for the same type of buildings under the same climate condition, and predicts the percent of improvements over the minimum requirements specified in ASHRAE Standard 55-2010, 62.1-2010 and 90.1-2010. An approach was developed to estimate the potential impact of a design factor on the whole building performance, and hence can assist the user to identify areas that have most pay back for investment. The VDS software was developed by using C++ with the conventional Model, View and Control (MVC) software architecture. The software has been verified by using a simple 3-zone case building. The application of the VDS concepts and framework for building design and performance analysis has been illustrated by using a medium-sized, five story office building that received LEED Platinum Certification from USGBC.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗