4.7 Article

A framework for parametric design optimization using isogeometric analysis

Journal

Publisher

ELSEVIER SCIENCE SA
DOI: 10.1016/j.cma.2016.10.048

Keywords

Isogeometric analysis; Parametric design optimization; Rhino and Grasshopper; NURBS; Wind turbine blade

Ask authors/readers for more resources

Isogeometric analysis (IGA) fundamentally seeks to bridge the gap between engineering design and high-fidelity computational analysis by using spline functions as finite element bases. However, additional computational design paradigms must be taken into consideration to ensure that designers can take full advantage of IGA, especially within the context of design optimization. In this work, we propose a novel approach that employs IGA methodologies while still rigorously abiding by the paradigms of advanced design parameterization, analysis model validity, and interactivity. The entire design lifecycle utilizes a consistent geometry description and is contained within a single platform. Because of this unified workflow, iterative design optimization can be naturally integrated. The proposed methodology is demonstrated through an IGA-based parametric design optimization framework implemented using the Grasshopper algorithmic modeling interface for Rhinoceros 3D. The framework is capable of performing IGA-based design optimization of realistic engineering structures that are practically constructed through the use of complex geometric operations. We demonstrate the framework's effectiveness on both an internally pressurized tube and a wind turbine blade, highlighting its applicability across a spectrum of design complexity. In addition to inherently featuring the advantageous characteristics of IGA, the seamless nature of the workflow instantiated in this framework diminishes the obstacles traditionally encountered when performing finite-element-analysis-based design optimization. (C) 2016 Elsevier B.V. All rights reserved.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available