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1. Automated Design Information Extraction from Construction Specifications to Support Wood Construction Cost Estimation

   https://doi.org/10.1061/9780784482889.069  

   Akanbi, Temitope; Zhang, Jiansong (November 2020, Construction Research Congress 2020)

   null (Ed.)

   In achieving full automation of construction cost estimation, the complete processes involved in computing cost estimates must be automated. The typical processes involved in achieving cost estimates are: (1) classification and matching of model elements to their various categories; (2) taking off quantities from design documents or building information models; (3) retrieving unit cost from a cost database; and (4) applying the unit costs and quantities in computing the cost estimate. Although, the level of automation in quantity takeoff has been relatively high, most commercial software programs still require manual inputs from estimators to: (1) match materials of building elements to work items; and/or (2) fulfill essential information requirements that may be missing from design models for accurate cost estimate computations. These missing information are usually obtained from the construction specifications in supplement to the design models. Automating the process of design information extraction from construction specifications can help reduce: (1) the time and cost of the estimation, (2) the manual inputs required in cost estimation computations, and (3) human errors in cost estimates. This paper explores the use of natural language processing techniques to help process construction specifications and the authors propose a new algorithmic method for extracting the needed design information from construction specifications to support wood construction cost estimation. A case study was conducted on a wood construction project to evaluate the authors’ proposed method. The results showed that the proposed method successfully searched for and found design details from construction specifications to fulfil essential information requirements for detailed wood construction cost estimation, with a 94.9% precision and a 97.4% recall. 

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2. Wood creep data collection and unbiased parameter identification of compliance functions

   https://doi.org/10.1515/hf-2019-0268  

   Tong, Danyang; Brown, Susan Alexis; Corr, David; Cusatis, Gianluca (April 2020, Holzforschung)

   Abstract Rising global emission have led to a renewed popularity of timber in building design, including timber-concrete tall buildings up to 18 stories. In spite of this surge in wood construction, there remains a gap in understanding of long-term structural behavior, particularly wood creep. Unlike concrete, code prescriptions for wood design are lacking in robust estimates for structural shortening. Models for wood creep have become increasingly necessary due to the potential for unforeseen shortening, especially with respect to differential shortening. These effects can have serious impacts as timber building heights continue to grow. This study lays the groundwork for wood compliance prediction models for use in timber design. A thorough review of wood creep studies was conducted and viable experimental results were compiled into a database. Studies were chosen based on correlation of experimental conditions with a realistic building environment. An unbiased parameter identification method, originally applied to concrete prediction models, was used to fit multiple compliance functions to each data curve. Based on individual curve fittings, statistical analysis was performed to determine the best fit function and average parameter values for the collective database. A power law trend in wood creep, with lognormal parameter distribution, was confirmed by the results. 

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3. Semi-Automated Conversion of 2D Orthographic Views of Wood Building Components to 3D Information Models

   https://doi.org/10.1061/9780784483961.104  

   Akanbi, Temitope; Chong, Oscar Wong; Zhang, Jiansong (March 2022, Construction Research Congress 2022)

   Offsite construction (e.g., wood modular houses) has many advantages over traditional stick-built construction, ranging from schedule/cost reduction to improvement in safety and quality of the built product. Unlike stick-built, offsite construction demands higher levels of design and planning coordination at the early stages of the construction project to avoid cost overruns and/or delays. However, most companies still rely on 2D drawings in the development of shop drawings, which are required for the fabrication of the building components such as walls and roofs. In practice, the process of developing shop drawings is usually based on manually interpreting the 2D drawings and specifications, which is time-consuming, costly, and prone to human errors. A 3D information model can improve the accuracy of this process. To help achieve this, the authors developed a semi-automated method that can process 2D orthographic views of building components and convert them to 3D models, which can be useful for fabrication. The developed 3D information model can be further transformed to building information models (BIMs) to support collaboration amongst users and data exchanges across platforms. The developed method was evaluated in the development of wall components of a student apartment project in Kalamazoo, MI. Experimental results showed that the developed method successfully generated the 3D information model of the wall components. A time comparison with the state-of-the-art practices in developing the wall components was performed. Results showed that the developed method utilized approximately 22% of the time it took the state-of-the-art manual method to generate the 3D models. 

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4. Probabilistic wind uplift resistance framework for the relative evaluation of wood-frame load paths

   https://doi.org/10.1016/j.engstruct.2023.116984  

   Rittelmeyer, Brandon M; Roueche, David B (January 2024, Engineering Structures)

   Past failure risk analyses of wind-impacted wood-frame structural load paths have tended to consider simplified resistance models that account for a few key load path connections, in which connection capacity distributions are generally based on benchmark experimental results. However, recent post-storm reconnaissance studies have demonstrated that connections in the load path of light wood-frame structures are themselves composed of multiple elements with many configurations and possible failure modes. This study presents a flexible approach for modeling wind uplift resistance in wood-frame load paths that includes a more exhaustive set of potential failure points yet is computationally efficient and readily adaptable to various load paths composed of different assemblages of structural members and connections. In this framework, ultimate capacities of connections and wood members are either based on design equations provided in the National Design Specification for Wood Construction or another applicable standard or computed from a comparable mechanics-based model. Analytical capacity estimates for roof sheathing, roof-to-wall connections, and wall-to-slab-foundation connections accord well with the range of published experimental results for these connections. Capacities of connections that act in parallel are summed to transform the load path into an analogous load chain of series components. System-level wind uplift resistance, defined by the weakest component in series, is evaluated by Monte Carlo simulation. By providing a more complete description of resistance than previous simplified models have done while avoiding the expense of a detailed finite-element or other solid mechanics model, the method proposed here holds promise as a rapid, consistent, and accurate way to quantify wind resistance in any arbitrary wood-frame load path, with applications including insurance risk analysis, hybrid data science frameworks utilizing post-storm reconnaissance data, and estimation of hazard intensity from structural damage observations. 

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5. Model Information Checking to Support Interoperable BIM Usage in Structural Analysis

   https://doi.org/10.1061/9780784482421.046  

   Ren, Ran; Zhang, Jiansong (June 2019, ASCE International Conference on Computing in Civil Engineering 2019)

   Building information modeling (BIM) is widely used in the architectural, engineering, and construction (AEC) domain to support different applications such as cost estimation, planning & scheduling, and structural analysis. Structural analysis is an essential way to ensure structural safety. However, different structural analysis software may not process all information from building information models (BIMs) correctly, which impedes BIM interoperability. To address this problem, the authors proposed a new method for automatically checking information completeness of BIMs to support BIM usage in structural analysis in an interoperable manner. The method was tested in an experimental implementation using python programs and a structural analysis software. The checking results using the proposed method was compared with results from a manual checking and a Model View Definition (MVD)-based checking, respectively. The experiment showed a comparable or better performance of the proposed method in accuracy and efficiency than manual checking and MVD-based checking. Furthermore, the proposed method overcomes the scope limitation possessed by MVD-based checking. Therefore, the proposed information checking method is expected to support BIM interoperability by helping people identify missing information from IFC-based BIMs. The authors also proposed a new system model for the BIM information checking domain [i.e., information, model, application, and application context (IMAAC) model]. 

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