Search Results (80)

Building Information Modeling (BIM) three-dimensional (3D) objects undergo repeated conversion and reconstruction processes for cross-platform utilization, during which geometric information loss, topological distortion, and semantic omission frequently occur, leading to fundamental limitations in accurate shape reconstruction and semantic-based functional reuse. The academic objective of this study is to overcome these limitations by proposing a three-stage sequential cross-platform reconstruction framework, consisting of semantic-vertex-based functional utilization, semantic-vertex-based invariant triangle mesh reconstruction, and semantic-vertex-based functional reuse, and to experimentally validate its effectiveness. To this end, an FBX–JSON dual-pipeline-based data management architecture is introduced to process visual geometric data and non-visual semantic metadata in parallel, thereby ensuring platform independence and data consistency. Experimental validation was conducted using IFC-based BIM objects generated in Autodesk Revit and triangle mesh models processed in Blender, at both the object and project levels. Quantitative evaluation was performed using geometric identity preservation, mesh completeness, semantic vertex restoration accuracy, and functional retention rate as the core performance indicators. The results reveal that the primary cause of mesh failure during platform transformation is face normal inconsistency, which can be stably resolved through auxiliary remeshing, thereby ensuring robust mesh reconstruction. Although the experiments were limited to round-trip transfers between Blender and Unity, the results experimentally verify the effectiveness of the proposed three-stage reconstruction framework and dual-pipeline data architecture, while also demonstrating their strong potential for generalization to broader cross-platform BIM environments. Full article

The building sector accounts for a large percentage of global greenhouse gas emissions, largely from the embodied carbon in common building materials like concrete and steel. Embodied carbon (EC) refers to the greenhouse gases released during the manufacturing, transportation, installation, maintenance, and disposal of building materials. Although growing in popularity, mass timber is still not nearly as common as other building materials. During the early building design stages, engineers often do not have the time or resources to holistically optimize material selection; consequently, concrete and steel remain the materials of choice. This research focused on the development of a fully automated parametric design tool, APDT, to showcase the viability of evaluating and optimizing mass timber in building construction. The APDT was developed using Autodesk’s Revit 2022 and the visual-based programming tool housed within Revit: Dynamo. The automated designer uses parametric inputs of a building, including size, number of stories, and loading, to create a model of a mass timber building with designed glulam columns and beams and cross-laminated timber floor panels. The designer calculates overall material quantities, which are then used to determine the building’s overall embodied carbon impact. Discussed herein is the development of a building design tool that highlights the benefits of optimized mass timber using existing software and databases. The tool allows the designer to expediently provide an estimate of the amount of material and embodied carbon values, thereby making it easier to consider mass timber when determining the structural system at the infancy stage of the project. The methodology outlined herein provides a replicable methodology for creating an APDT that bridges a critical gap in early-stage design, enabling rapid embodied carbon comparisons and fostering consideration of mass timber as a viable low-carbon alternative. Full article

Conventional uses of building information modeling (BIM) in existing-building representation tend to prioritize geometric consistency and efficiency, but often at the expense of interpretive depth. This paper challenges BIM’s tendency to promote epistemic closure by proposing a method to foreground relational ambiguity, transforming view reconciliation from a default automated process into a generative act of critical inquiry. The method, implemented in Autodesk Revit, introduces a parametric reference frame within BIM sheets that foregrounds and manipulates reciprocal relationships between orthographic views (e.g., plans and sections) to promote interpretive ambiguity. Through a case study, the paper demonstrates how parameterized view relationships can resist oversimplification and encourage conflicting interpretations. By intentionally sacrificing efficiency for epistemic resilience, the method aims to expand BIM’s role beyond documentation, positioning it as a tool for architectural knowledge production. The paper concludes with implications for software development, pedagogy, and future research at the intersection of critical representation and computational tools. Full article

This study addresses the challenge of identifying heavy Building Information Modeling (BIM) library components that disproportionately degrade model performance. While BIM has become standard in the construction industry, heavy components characterized by excessive geometric complexity, numerous instances, or inefficient optimization—cause extended file loading times, interface lag, and coordination difficulties, particularly in large cross-industry projects. Current identification methods rely primarily on designer experience and manual inspection, lacking systematic evaluation frameworks. This research develops a multi-criteria evaluation method based on Multi-Criteria Decision Analysis (MCDA) that quantifies component performance impact through five weighted criteria: instance count (20%), geometry complexity (30%), face count (20%), edge count (10%), and estimated file size (20%). These metrics are aggregated into a composite Weight Score, with components exceeding a threshold of 200 classified as requiring optimization attention. The method was implemented as HeavyFamilies, a pyRevit plugin for Autodesk Revit featuring a graphical interface with tabular results, CSV export functionality, and direct model visualization. Validation on three real BIM projects of varying scales (133–680 families) demonstrated effective identification of heavy components within 8–165 s of analysis time. User validation with six BIM specialists achieved 100% task completion rate, with automatic color coding and direct model highlighting particularly valued. The proposed approach enables a shift from reactive troubleshooting to proactive quality control, supporting routine diagnostics and objective prioritization of optimization efforts in federated and multi-disciplinary construction projects. Full article

The construction industry faces challenges in estimating costs because the processes are time-consuming and involve a high likelihood of making errors. For instance, quantity take-offs are often inaccurate, and there is not a simple way to integrate data from Building Information Modeling (BIM) platforms and cost databases. This study introduces a framework that utilizes the Model Context Protocol (MCP) to ensure seamless integration between large language models (LLMs) and BIM models through Autodesk Revit in order to enable fully automated cost estimation workflows. The developed system combines an AI-powered MCP server with cost databases that are standard in the industry, such as the 2025 Craftsman National Building Cost Manual and the ZIP code-based location modifiers. This system enables LLMs to automatically obtain quantities from BIM models, match components to cost items, make regional changes, and make professional cost estimates. A case study of estimating the cost of an electrical system shows that the framework can reduce estimation time from 2.5–3.5 h (manual baseline) to 42.3 ± 3.7 s (n = 5 runs, warm start), representing a 98.6% efficiency gain, while being more accurate with respect to industry standards. The system processed 187 BIM elements in three component groups (receptacles, conduits, and panels). It automatically matched them to the right cost database items, used location-specific modifiers for ZIP code 01003, and made a full cost estimate of USD 13,945.81 with detailed breakdowns and a percent difference of %5.1 of the manual estimation. This research enhances automation in construction by developing a methodology for AI-BIM integration using standardized protocols, shows the practical application of AI in construction workflows, and provides empirical evidence of the advantages of automation in cost estimation processes. The results indicate that MCP-based AI integration presents a novel approach for construction automation, delivering improvements while applying professional standards of accuracy and availability. Full article

This study investigates the integration of eco-design strategies in the energy renovation of mid-20th century heritage buildings, using the Antonio Rueda Residential Complex in Valencia (Spain) as a representative case study. The research addresses the reconciliation between heritage conservation and contemporary environmental objectives by evaluating the building in terms of its construction and current performance. The multidisciplinary working methodology consists of creating a BIM-based workflow (Revit + Autodesk Insight) to generate an analytical energy model, quantify Operational Carbon, and evaluate the impact of lighting inside the homes to simulate the impacts of the intervention strategies. This is justified as existing buildings are energy intensive and heavily dependent on fossil fuels, largely due to insufficient façade insulation, obsolete window systems, and limited solar protection. Nine refurbishment scenarios were developed, ranging from reversible improvements to the building envelope to volumetric extensions inspired by the principles of eco-design and circularity. Comparative simulations suggest that specific improvements could significantly reduce energy demand while remaining compatible with the architectural identity of the complex. Full article

In a context in which the construction sector is significantly contributing to environmental degradation, LCA (Life Cycle Assessment) is a fundamental tool for analyzing the impact of materials and processes. This systematic literature review highlights the potential of integrating Building Information Modeling (BIM) with LCA to encourage sustainable practices in the construction sector. To this end, a systematic search was conducted in the Scopus and Web of Science (WoS) databases and, after a rigorous selection process, 65 peer-reviewed studies were chosen from an initial pool of 817 records for final analysis. The quantitative analysis of the 65 studies revealed a well-defined technological landscape, demonstrating that BIM–LCA integration can enhance decision-making. The main findings reveal that Autodesk Revit is the prevailing BIM authoring tool, used in 77% of the cases analyzed, establishing itself as the de facto standard for sustainability assessments. Regarding environmental data, the Ecoinvent database was the most cited Life Cycle Inventory (LCI) source, employed in 32% of the selected articles. This review highlights critical issues that hinder its adoption, including interoperability problems with software, a lack of standardized data, and high implementation costs. It is therefore necessary to overcome these barriers to fully exploit this approach and contribute to global sustainability goals, such as reducing CO₂ emissions and waste in the construction sector. Full article

Building Information Modeling (BIM) is increasingly used to support green building design practices, yet its alignment with established green building assessment (GBA) tools remains underexamined. This study evaluates the extent to which Autodesk Revit, as a BIM tool, supports the calculation of energy-related indicators in GBA tools such as the Leadership in Energy and Environmental Design (LEED) method. A quasi-empirical, multi-method approach was employed, combining content analysis, a Revit-based simulation of a residential building, and structured evaluation by a panel of four experts. Using both subjective and objective measures, the experts assessed Revit’s effectiveness and the role of Revit’s media channels—modeling, simulation, data integration, and text documentation—in supporting and calculating LEED Energy and Atmosphere (EA) indicators. Results reveal that Revit is capable of effectively supporting 7 out of 11 LEED EA indicators. The highly supported indicators included minimum energy performance, building-level energy metering, optimized energy performance, advanced energy metering, renewable energy production, and enhanced refrigerant management while the fundamental refrigerant management indicator was evaluated as a moderately supported indicator. These highly supported indicators are core energy-related indicators; three of them are prerequisite indicators, while the remaining are credit indicators that cover 66.7% of the weight assigned for the EA indicators. The results also demonstrated that the remaining four indicators—fundamental commissioning and verification, enhanced commissioning, demand response, green power, and carbon offsets—were evaluated as poorly supported by Revit. The consistency of results across two rounds of survey, along with the expert’s consensus on 73% (8 out of 11) of the examined indicators, provides empirical validation of Rivet’s capacity to support LEED GBA. Findings also showed that modeling and simulation, followed by data integration, are the most impactful channels in supporting and calculating LEED EA criteria and requirements, with significant statistical correlation confirmed through Kendall’s Tau correlation. The findings have theoretical and practical implications for designers, green building practitioners, and BIM developers and suggest areas for further research. Full article

Thermal insulation is essential in lowering the energy consumption of buildings. However, many fossil-based insulation and exterior cladding materials are derived from petrochemical components, which often have adverse ecological impacts. This study explores the effectiveness of integrating sustainable thermal insulation solutions into building design to reduce energy consumption and minimize ecological impact. Focusing on an energy-efficient breakfast house located in Van, Turkey, the project was modeled using Autodesk-Revit software (2023). A comprehensive analysis was conducted by generating eighty alternative scenarios, combining two distinct wall structures, eight fiber-based natural insulation materials, and five wood-based exterior cladding materials. The energy performance of each scenario was evaluated using IES-VE software (2024.1), focusing on annual total energy consumption and CO₂ emissions, while accounting for regional climatic conditions and targeted indoor comfort levels. To further refine the selection of optimal materials, a hybrid evaluation was performed using multi-attribute decision approaches, including LODECI, MAXC, and DEPART. These methods provided a systematic framework for comparing the performance of wood-based insulation materials across multiple criteria. In order to verify the accuracy of the proposed multi-attribute decision models, a comparative analysis has been undertaken with other multi-attribute decision methods (COPRAS, ARAS and WASPAS). The study highlights the technical feasibility of incorporating cost-effective, eco-friendly fiber-based and wood-based materials into building envelopes, demonstrating their potential to significantly enhance energy efficiency and reduce environmental impact. By combining advanced simulation tools with robust decision-making methodologies, this research offers a scientifically grounded approach to sustainable architectural design, providing important outputs for future applications in energy-efficient construction. Full article

This study presents a terrestrial-laser-scanning-based scan-to-BIM workflow that transforms point cloud data into a BIM-based digital twin and analyzes how data collected with LiDAR (Light Detection and Ranging) can be converted into an information-rich model using Autodesk ReCap and Revit. Point clouds provided by laser scanning were processed in the ReCap environment and imported into Revit in an application that took place within an industrial facility of approximately 240 m² in Izmir. The scans were registered and pre-processed in Autodesk ReCap 2022 and modeled in Autodesk Revit 2022, with visualization updates prepared in Autodesk Revit 2023. Geometric quality was evaluated using point-to-model distance checks, since the dataset was imported in a pre-registered form and ReCap did not provide station-level RMSE values. The findings indicate that the ReCap–Revit integration offers high geometric accuracy and visual detail for both building elements and production-line machinery, but that high data density and complex geometry limit processing performance and interactivity. The study highlights both the practical applicability and the current technical limitations of terrestrial-laser-scanning-based scan-to-BIM workflows in an industrial context, offering a replicable reference model for future digital twin implementations in Turkey. Full article

The construction industry is responsible for nearly one-third of global greenhouse gas emissions and consumes over 50% of the planet’s natural resources. As population growth continues, the demand for these resources is expected to rise. Within this context, where business models are still largely based on the Linear Economy (LE), the Circular Economy (CE) emerges as a strategy for promoting economic development while reducing dependence on natural resource consumption. To enable the transition from LE to CE, digital tools such as Material Passports (MP) are essential. An MP compiles data and information describing the characteristics of materials to facilitate their recovery and reuse. This study aims to model the MP of a wood-frame panel commercially produced by Tecverde in Brazil. The panel was designed for a building project using 2024 version of Autodesk Revit software. The proposed MP contains 49 parameters grouped into nine categories, and the data were obtained from open databases provided by the company. The results highlight existing challenges related to sustainability parameters, as well as opportunities to incorporate circular value principles into the construction industry. Full article

This study presents a novel low-cost workflow integrating smartphone-based photogrammetry, Building Information Modeling (BIM), infrared thermography, and real-time interactive visualization to create digital twins for comprehensive energy assessment of existing buildings. Unlike conventional approaches requiring expensive laser scanning equipment and specialized software, this methodology democratizes advanced building diagnostics through accessible technologies and academic licenses. The research aims to develop and validate a replicable workflow that enables architects, engineers, and educators to conduct detailed energy assessments without high-end equipment, while establishing technical criteria for accurate geometric reconstruction, thermal data integration, and interactive visualization. The workflow combines terrestrial photogrammetry using smartphone cameras for 3D reconstruction, BIM modeling in Autodesk Revit for semantic building representation, infrared thermography for thermal performance documentation, and Unreal Engine for immersive real-time visualization. The approach is validated through application to the historic control tower of the former Rabassa aerodrome at the University of Alicante, documenting data capture protocols, processing workflows, and integration criteria to ensure methodological replicability. Results demonstrate that functional digital twins can be generated using consumer-grade devices (high-end smartphones) and academically licensed software, achieving geometric accuracy sufficient for energy assessment purposes. The integrated platform enables systematic identification of thermal anomalies, heat loss patterns, and envelope deficiencies through intuitive three-dimensional interfaces, providing a robust foundation for evidence-based energy assessment and renovation planning. The validated workflow offers a viable, economical, and scalable solution for building energy analysis, particularly valuable in resource-constrained academic and professional contexts, advancing both scientific understanding of accessible digital twin methodologies and practical applications in building energy assessment. Full article

In the context of digital transformation for industrial heritage conservation propelled by China’s National Industrial Heritage Management Measures, evidence regarding the trade-offs among accuracy, completeness, and efficiency within the acquisition–registration–integration pipeline, as well as transferable methodologies, remains inadequate. Addressing key challenges in information integration for industrial architectural heritage in Inner Mongolia—such as fragile media, weak sustainability, and severe information silos—demands a systematic solution. This paper proposes a BIM-based three-dimensional digital preservation framework centered on “Space-Time-Value” and empirically validates its workflow effectiveness and database interoperability. Focusing on the Inner Mongolia University of Technology Architecture Building, a prime exemplar of adaptive reuse in the region, we employed terrestrial 3D laser scanning and Unmanned Aerial Vehicle (UAV) oblique photogrammetry to acquire a 13.8-billion-point cloud. Using Autodesk Revit, we developed an LOD400 model (comprising 12 component types and 349 parametric families), achieving systematic integration of structural data, spatial evolution information, and non-geometric attributes. Comparative evaluation shows that this workflow outperforms baselines in geometric accuracy, facade completeness, and processing efficiency, while significantly enhancing the integration and retrieval capabilities for heterogeneous data. The research establishes a “Multi-source Data Integration + Sustainable Utilization” digital paradigm for industrial architectural heritage, providing a replicable methodology for whole-life-cycle management and adaptive reuse. Full article

This research analyzes the implementation of terrestrial laser scanning (TLS) in Building Information Modeling for Bridges (BrIM) for the structural monitoring and analysis of the Villena Rey Bridge, considering that bridges undergo progressive deterioration due to environmental factors and dynamic loads, making advanced monitoring technologies essential. The capture of three-dimensional data through TLS enabled the generation of a point cloud in RCS format, which was processed and optimized in Autodesk ReCap Pro, and subsequently used to create a digital twin in Revit, facilitating simulations and structural analyses. Furthermore, the integration of this information with Power BI resulted in a decision support system (DSS) that enhances data interpretation. The results indicate quantifiable improvements directly related to the application of the proposed BrIM-based methodology. Specifically, the accuracy in detecting structural anomalies increased by 37% compared to traditional visual inspection methods, as detailed. Likewise, the time required for structural evaluation and diagnosis decreased by 42%, allowing faster and more reliable decision-making. Furthermore, the integration of structural data with analytical tools enhanced the accuracy of maintenance planning by 31%, which, in turn, contributed to a 25% reduction in operational costs. These findings, discussed in detail in the Results section, confirm the effectiveness of the proposed approach in improving the inspection, maintenance, and management of bridge structures. Finally, as highlighted in the Conclusions, the integration of technologies such as TLS, Revit, and Power BI represents a significant step forward in digital road infrastructure management and provides a foundation for future research focused on refining and expanding this methodology. Full article

State Departments of Transportation (DOTs) face challenges with traditional bridge inspections that are time-consuming, inconsistent, and paper-based. This study focused on an existing research gap regarding automated methods that streamline the bridge inspection process, prioritize maintenance effectively, and allocate resources efficiently. Thus, this paper introduces a digitalized bridge inspection framework by integrating Building Information Modeling (BIM) and Business Intelligence (BI) to enable near-real-time monitoring and digital documentation. This study adopts a Design Science Research (DSR) methodology, a recognized paradigm for developing and evaluating the innovative SmartBridge to address pressing bridge inspection problems. The method involved designing an Autodesk Revit-based plugin for data synchronization, element-specific comments, and interactive dashboards, demonstrated through an illustrative 3D bridge model. An illustrative example of the digitalized bridge inspection with the proposed framework is provided. The results show that SmartBridge streamlines data collection, reduces manual documentation, and enhances decision-making compared to conventional methods. This paper contributes to this body of knowledge by combining BIM and BI for digital visualization and predictive analytics in bridge inspections. The proposed framework has high potential for hybridizing digital technologies into bridge infrastructure engineering and management to assist transportation agencies in establishing a safer and efficient bridge inspection approach. Full article