Optimization-driven conceptual design of truss structures in a parametric modelling environment

He, Lihua; Li, Qingpeng; Gilbert, Matthew; Shepherd, Paul; Rankine, Catherine; Pritchard, Thomas J.; Reale, Vincenzo

doi:10.1016/j.istruc.2021.12.048

Cited by 18 publications

(9 citation statements)

References 38 publications

(49 reference statements)

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“…Along the same lines, manuscript [36] utilized Grasshopper to create geometry and developed a tool in C# to transfer the structure to SAP2000 to perform topology optimization. Grasshopper, together with Peregrine (Lim-itState, Sheffield, UK) plug-in, were employed to perform layout and geometry optimization methods in sequence for optimum designs in [37]. Furthermore, a framework that utilizes Dynamo (Autodesk, San Rafael, CA, USA) for Visual Programming and Open-Sees (UC Regents, Pacific Earthquake Engineering Research Center, CA, USA) for measuring structural performance by using the FEM of the created models was proposed in [38].…”

Section: Available Tools For Ai-based Structural Optimization In Bim ...mentioning

confidence: 99%

Structural Optimization of Trusses in Building Information Modeling (BIM) Projects Using Visual Programming, Evolutionary Algorithms, and Life Cycle Assessment (LCA) Tools

Yavan,

Maalek,

Toğan

2024

Buildings

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The optimal structural design is imperative in order to minimize material consumption and reduce the environmental impacts of construction. Given the complexity in the formulation of structural design problems, the process of optimization is commonly performed using artificial intelligence (AI) global optimization, such as the genetic algorithm (GA). However, the integration of AI-based optimization, together with visual programming (VP), in building information modeling (BIM) projects warrants further investigation. This study proposes a workflow by combining structure analysis, VP, BIM, and GA to optimize trusses. The methodology encompasses several steps, including the following: (i) generation of parametric trusses in Dynamo VP; (ii) performing finite element modeling (FEM) using Robot Structural Analysis (RSA); (iii) retrieving and evaluating the FEM results interchangeably between Dynamo and RSA; (iv) finding the best solution using GA; and (v) importing the optimized model into Revit, enabling the user to perform simulations and engineering analysis, such as life cycle assessment (LCA) and quantity surveying. This methodology provides a new interoperable framework with minimal interference with existing supply-chain processes, and it will be flexible to technology literacy and allow architectural, engineering and construction (AEC) professionals to employ VP, global optimization, and FEM in BIM-based projects by leveraging open-sourced software and tools, together with commonly used design software. The feasibility of the proposed workflow was tested on benchmark problems and compared with the open literature. The outcomes of this study offer insight into the opportunities and limitations of combining VP, GA, FEA, and BIM for structural optimization applications, particularly to enhance structural efficiency and sustainability in construction. Despite the success of this study in developing a workable, user-friendly, and interoperable framework for the utilization of VP, GA, FEM, and BIM for structural optimization, the results obtained could be improved by (i) increasing the callback function speed between Dynamo and RSA through specialized application programming interface (API); and (ii) fine-tuning the GA parameters or utilizing other advanced global optimization and supervised learning techniques for the optimization.

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Section: Available Tools For Ai-based Structural Optimization In Bim ...mentioning

confidence: 99%

Structural Optimization of Trusses in Building Information Modeling (BIM) Projects Using Visual Programming, Evolutionary Algorithms, and Life Cycle Assessment (LCA) Tools

Yavan,

Maalek,

Toğan

2024

Buildings

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“…Along the same lines, the manuscript [36] utilized Grasshopper to create geometry and developed a tool in C# to transfer the structure to SAP2000 to perform topology optimization. Grasshopper together with Peregrine plug-in were employed to perform layout and geometry optimization methods in sequence for optimum designs in [37]. Furthermore, a framework that utilizes Dynamo for Visual Programming and OpenSees for measuring structural performance by using the FEM of the created models was proposed in [38].…”

Section: Available Tools For Ai-based Structural Optimization In Bim ...mentioning

confidence: 99%

Structural Optimization in Building Information Modeling (BIM) Projects Using Visual Programming, Evolutionary Algorithms, and Sustainability Assessment Tools

Yavan,

Maalek,

Toğan

2024

Preprint

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The optimal structural design is imperative to minimize material consumption and reduce the environmental impact of construction. Given the complexity in the formulation of structural design problems, the process of optimization is commonly performed using artificial intelligence (AI) global optimization, such as Genetic Algorithm (GA). However, the integration of AI-based optimization together with visual programming (VP) in building information modeling (BIM) projects warrants further investigation. This study proposes a workflow by combining structure analysis, VP, BIM, and GA to optimize trusses. The methodology encompasses several steps including: (i) generation of parametric trusses in Dynamo VP; (ii) performing the finite element modeling (FEM) using Robot Structural Analysis (RSA); (iii) retrieving and evaluating the FEM results interchangeably between Dynamo and RSA; (iv) finding the best solution using GA; and (v) importing the optimized model into Revit, enabling the user to perform simulations and engineering analysis, such as life cycle assessment (LCA) and quantity surveying. The feasibility of the proposed workflow was tested on benchmark problems and compared with open literature. The outcomes of this study offer insight into the opportunities and limitations of combining VP, GA, FEA, and BIM for structural optimization applications, particularly to enhance structural efficiency and sustainability in construction.

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“…This paper uses continuous cross-section sizing variables, making the results inapplicable in practice. The authors in [ 10 , 11 , 12 , 13 ] also successfully showed the implementation of Euler buckling in truss optimization problems.…”

Section: Introductionmentioning

confidence: 99%

Effects of Limiting the Number of Different Cross-Sections Used in Statically Loaded Truss Sizing and Shape Optimization

Kostić,

Petrović,

Marjanović

et al. 2024

Materials

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This research aims to show the effects of adding cardinality constraints to limit the number of different cross-sections used in simultaneous sizing and shape optimization of truss structures. The optimal solutions for sizing and shape optimized trusses result in a generally high, and impractical, number of different cross-sections being used. This paper presents the influence of constraining the number of different cross-sections used on the optimal results to bring the scientific results closer to the applicable results. The savings achieved using the cardinality constraint are expected to manifest in more than just the minimization of weight but in all the other aspects of truss construction, such as labor, assembly time, total weld length, surface area to be treated, transport, logistics, and so on. It is expected that the optimal weight of the structures would be greater than when not using this constraint; however, it would still be below conventionally sized structures and have the added benefits derived from the simplicity and elegance of the solution. The results of standard test examples for each different cardinality constraint value are shown and compared to the same examples using only a single cross-section on all bars and the overall optimal solution, which does not have the cardinality constraint. An additional comparison is made with results of just the sizing optimization from previously published research where authors first used the same cardinality constraint.

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Optimization-driven conceptual design of truss structures in a parametric modelling environment

Cited by 18 publications

References 38 publications

Structural Optimization of Trusses in Building Information Modeling (BIM) Projects Using Visual Programming, Evolutionary Algorithms, and Life Cycle Assessment (LCA) Tools

Structural Optimization of Trusses in Building Information Modeling (BIM) Projects Using Visual Programming, Evolutionary Algorithms, and Life Cycle Assessment (LCA) Tools

Structural Optimization in Building Information Modeling (BIM) Projects Using Visual Programming, Evolutionary Algorithms, and Sustainability Assessment Tools

Effects of Limiting the Number of Different Cross-Sections Used in Statically Loaded Truss Sizing and Shape Optimization

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