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This paper presents a study on the characteristics of Pratt trusses under conditions of optimal or near-optimal weight. Trusses with varying numbers of panels, spans, and heights are selected for analysis. Several characteristics describing truss geometry and internal forces are examined. Four dimensioning approaches are developed to perform calculations and obtain data for analysis. A parametric model of truss geometry is developed and integrated with a finite element calculation algorithm in the Rhino8/Grasshopper software. The data are processed and analyzed using the machine learning software Weka and the statistical analysis software RStudio. Results show correlations between various truss characteristics. This study focuses on truss weight and height-span ratio to find the optimal weight. Based on truss height at optimal weight for each span, other characteristics are analyzed. It is observed that a larger number of panels increases the truss weight but also makes the results more consistent and predictable. The objective of this work is to better understand Pratt truss performance, which can be used to reduce the size of optimization tasks. | This paper presents a study on the characteristics of Pratt trusses under conditions of optimal or near-optimal weight. Trusses with varying numbers of panels, spans, and heights are selected for analysis. Several characteristics describing truss geometry and internal forces are examined. Four dimensioning approaches are developed to perform calculations and obtain data for analysis. A parametric model of truss geometry is developed and integrated with a finite element calculation algorithm in the Rhino8/Grasshopper software. The data are processed and analyzed using the machine learning software Weka and the statistical analysis software RStudio. Results show correlations between various truss characteristics. This study focuses on truss weight and height-span ratio to find the optimal weight. Based on truss height at optimal weight for each span, other characteristics are analyzed. It is observed that a larger number of panels increases the truss weight but also makes the results more consistent and predictable. The objective of this work is to better understand Pratt truss performance, which can be used to reduce the size of optimization tasks. | ||
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+ | == Full Paper == | ||
+ | <pdf>Media:Draft_Sanchez Pinedo_379191621105.pdf</pdf> |
This paper presents a study on the characteristics of Pratt trusses under conditions of optimal or near-optimal weight. Trusses with varying numbers of panels, spans, and heights are selected for analysis. Several characteristics describing truss geometry and internal forces are examined. Four dimensioning approaches are developed to perform calculations and obtain data for analysis. A parametric model of truss geometry is developed and integrated with a finite element calculation algorithm in the Rhino8/Grasshopper software. The data are processed and analyzed using the machine learning software Weka and the statistical analysis software RStudio. Results show correlations between various truss characteristics. This study focuses on truss weight and height-span ratio to find the optimal weight. Based on truss height at optimal weight for each span, other characteristics are analyzed. It is observed that a larger number of panels increases the truss weight but also makes the results more consistent and predictable. The objective of this work is to better understand Pratt truss performance, which can be used to reduce the size of optimization tasks.
Published on 01/07/24
Accepted on 01/07/24
Submitted on 01/07/24
Volume Inverse Problems, Optimization and Design, 2024
DOI: 10.23967/wccm.2024.105
Licence: CC BY-NC-SA license