Introducing a New Method to Convert a 2D Hand-Drawn Perspective to a 3D Digital Model

Zargar, Seyed Hossein; Sadeghi, Jaleh; Hashemi, Mona; Motallebi, Narjes; Garmaroodi, Ali Andaji

doi:10.1007/s00004-019-00457-0

Cited by 3 publications

(1 citation statement)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…30 Designers rely on the latest software for modeling, modifying, and presenting their designs, especially as the concept of coding the design process in architecture has become more prominent. 31,32 Parametric design approaches are now widely taught at schools and used in design practices. 33 In the field of Generative Design (GD), Visual Programming Languages (VPLs) such as in Grasshopper are increasingly popular compared to TPLs.…”

Section: State Of Artmentioning

confidence: 99%

Agent-based modelling for early-stage optimization of spatial structures

Zargar

Sadeghi

Brown

2022

International Journal of Architectural Computing

Self Cite

View full text Add to dashboard Cite

Agent-based modelling (ABM) is a complex problem-solving approach that can be employed in early-stage parametric design, and certain design applications may benefit from such a bottom-up strategy. This research investigates the potential of ABM for structural design optimization. A case study of a form-found cantilevered truss is presented that has a doubly curved shape over a regular grid, resulting in individual members with different lengths across the structure. It is hypothesized that an agent-based approach might generate an irregular grid of similar or better structural performance, but with more uniform length of individual elements. This approach could be useful when designing a global structural form from a kit of parts or adaptively reusing a disassembled existing structure with regular member lengths. A series of ABM simulations are conducted with different hyperparameters, and the generated designs are compared to the original form-found shape in terms of structural performance.

show abstract

Section: State Of Artmentioning

confidence: 99%