TY - JOUR
T1 - Optimization-driven conceptual design of truss structures in a parametric modelling environment
AU - He, Linwei
AU - Li, Qingpeng
AU - Gilbert, Matthew
AU - Shepherd, Paul
AU - Rankine, Catherine
AU - Pritchard, T.
AU - Vincenzo, Reale
N1 - Funding Information:
The financial support provided by the Engineering and Physical Research Council (EPSRC) for projects EP/N023471/1 and EP/N023269/1 and a follow-up Knowledge Exchange project is gratefully acknowledged. The development of the Peregrine Rhino / Grasshopper plugin has also been supported by the INTEGRADDE project, funded from the European Union's Horizon 2020 research and innovation programme under grant agreement No 820776.
Funding Information:
The financial support provided by the Engineering and Physical Research Council (EPSRC) for projects EP/N023471/1 and EP/N023269/1 and a follow-up Knowledge Exchange project is gratefully acknowledged. The development of the Peregrine Rhino / Grasshopper plugin has also been supported by the INTEGRADDE project, funded from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 820776.
PY - 2022/3/31
Y1 - 2022/3/31
N2 - Structural optimization methods can be extremely powerful when used at the initial, conceptual, design stage of a building or bridge structure, potentially identifying materially efficient forms that are beyond the imagination of a human designer. This is particularly important at present, given the pressing need to reduce the carbon footprint associated with the built environment in the face of the current climate emergency. In this contribution, a computationally efficient global-local optimization framework is proposed, in which a linear programming-based truss layout optimization step is employed to generate initial (near-)optimal designs, with a non-linear optimization step then used to generate designs that take account of real-world complexity. To facilitate rapid exploration of design concepts, the proposed global-local optimization framework has been made available in the Peregrine plug-in for the popular Rhino-Grasshopper parametric modelling environment. The efficacy of the approach is demonstrated through its application to a range of case study problems.
AB - Structural optimization methods can be extremely powerful when used at the initial, conceptual, design stage of a building or bridge structure, potentially identifying materially efficient forms that are beyond the imagination of a human designer. This is particularly important at present, given the pressing need to reduce the carbon footprint associated with the built environment in the face of the current climate emergency. In this contribution, a computationally efficient global-local optimization framework is proposed, in which a linear programming-based truss layout optimization step is employed to generate initial (near-)optimal designs, with a non-linear optimization step then used to generate designs that take account of real-world complexity. To facilitate rapid exploration of design concepts, the proposed global-local optimization framework has been made available in the Peregrine plug-in for the popular Rhino-Grasshopper parametric modelling environment. The efficacy of the approach is demonstrated through its application to a range of case study problems.
KW - Layout optimization
KW - Parametric design
KW - Structural design
KW - Structural optimization
KW - Topology optimization
UR - http://www.scopus.com/inward/record.url?scp=85122996216&partnerID=8YFLogxK
U2 - 10.1016/j.istruc.2021.12.048
DO - 10.1016/j.istruc.2021.12.048
M3 - Article
SN - 2352-0124
VL - 37
SP - 469
EP - 482
JO - Structures
JF - Structures
ER -
