The Computational Generation and Realization of Spatial Truss Structures

Zhao, Xianzhong; Wang, R. H.; Shea, Kristina

doi:10.1061/9780784413616.154

Cited by 3 publications

(3 citation statements)

References 13 publications

(12 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To further improve design quality and efficiency, plenty of automated design methods, which focused on performing conceptual design independently, have been developed in recent years. A representative one is Structural Topology and Shape Annealing (STSA) [1], which simulates the truss design process well and has been successfully used in engineering practice [2,3]. However, most automated methods such as STSA consider only quantitative objectives and constraints that can be defined mathematically, e.g., minimum weight or stress limit.…”

Section: Introductionmentioning

confidence: 99%

An Automated Design Method for Plane Trusses Based on User Preference Information

2023

View full text Add to dashboard Cite

Structural design is a complicated decision-making process involving multiple qualitative and quantitative factors. Currently, most automated design methods consider only quantitative objectives and constraints, ignoring the qualitative design information that is difficult define mathematically, such as the user preference for structural shapes. This limits the functionality and efficiency of such design methods. In this study, a design method named STSA-P is proposed for plane trusses to incorporate user preference into the automatic design process. Two main problems are addressed, i.e., how to quantify user preference information and how to coordinate it with other quantitative design objectives. A prediction model of user preference is developed for the first problem by generating the data set and selecting an appropriate machine learning (ML) algorithm. Specifically, a set of truss features quantitatively representing the structural shapes are identified for the truss sample population. Furthermore, an interactive system is developed for collecting user evaluation information as data labels. Strategies for reducing user fatigue are also considered during the evaluation process. A set of numerical experiments are conducted to select the suitable ML algorithm. Regarding the second problem, the physical programming method is modified to construct a new aggregate function which effectively coordinates user preference with other design objectives. A cost function is designed by considering the design constraints. On this basis, the prediction model is incorporated into the Structural Topology and Shape Annealing (STSA) method to form the STSA-P method. Two students are invited to perform a design case using the STSA-P method. It is demonstrated that the results verify the practicality and validity of the proposed method.

show abstract

Section: Introductionmentioning

confidence: 99%

An Automated Design Method for Plane Trusses Based on User Preference Information

2023

View full text Add to dashboard Cite

show abstract

“…The system was applied in architectural design, and it could automatically verify whether a design met specific requirements through the description in the CAD database. Zhao et al [5] programmed the performance-based structure generation algorithm structural topology and shape annealing (STSA), which applies computational synthesis theory to numerically realize the intelligent generation and conceptual design of spatial trusses. Engineers from General Motors Company and Autodesk collaborated to generate more than 150 feasible design alternatives for seat brackets utilizing derivative design, and eight different components were assembled into one integrated part that achieved a weight reduction of 40% and a strength increase of 20% [6].…”

Section: Introductionmentioning

confidence: 99%

Intelligent Generation Method of Innovative Structures Based on Topology Optimization and Deep Learning

Wang

et al. 2021

Materials

View full text Add to dashboard Cite

Computer-aided design has been widely used in structural calculation and analysis, but there are still challenges in generating innovative structures intelligently. Aiming at this issue, a new method was proposed to realize the intelligent generation of innovative structures based on topology optimization and deep learning. Firstly, a large number of structural models obtained from topology optimization under different optimization parameters were extracted to produce the training set images, and the training set labels were defined as the corresponding load cases. Then, the boundary equilibrium generative adversarial networks (BEGAN) deep learning algorithm was applied to generate numerous innovative structures. Finally, the generated structures were evaluated by a series of evaluation indexes, including innovation, aesthetics, machinability, and mechanical performance. Combined with two engineering cases, the application process of the above method is described here in detail. Furthermore, the 3D reconstruction and additive manufacturing techniques were applied to manufacture the structural models. The research results showed that the proposed approach of structural generation based on topology optimization and deep learning is feasible, and can not only generate innovative structures but also optimize the material consumption and mechanical performance further.

show abstract

“…Special shaped column have the advantage of avoiding column convex, not only can make the building structure more beautiful, but also can increase the building area, and in some measure it brings about economic benefit. It often use test [2][3][4][5][6][7] and numerical simulation [8][9][10] to research the mechanical behavior and deformation properties of special shaped section column joints in RC frame. The result of test is intuitive and reliable but it have a long test period and high-cost.…”

Section: Introductionmentioning

confidence: 99%

Numerical Simulation of Z-Shaped Column Joints in RC Frame Based on Damage Plasticity Model

Cui

2015

AMM

View full text Add to dashboard Cite

This research selected Z-shaped section column joints in RC frame as the investigating object and considered the mechanical parameters extracted from physical model test results, proposed the finite element model of concrete damaged plasticity. Combining concrete damage plasticity model parameters on ABAQUS of concrete constitutive relationship from appendix C of Code for design of concrete structures (GB50010-2010), add the concept of damage factor to Energy equivalence principle, construct finite element model of Z-shaped column joints in RC frame, and simulated the test process under horizontal cyclic loading. The analysis results indicate that the finite element model can perfectly simulate action. It can reflect the mechanical properties of Z-shaped column joints in frame under horizontal cyclic loading, which is proved correct and reliable.

show abstract

The Computational Generation and Realization of Spatial Truss Structures

Cited by 3 publications

References 13 publications

An Automated Design Method for Plane Trusses Based on User Preference Information

An Automated Design Method for Plane Trusses Based on User Preference Information

Intelligent Generation Method of Innovative Structures Based on Topology Optimization and Deep Learning

Numerical Simulation of Z-Shaped Column Joints in RC Frame Based on Damage Plasticity Model

Contact Info

Product

Resources

About