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Reciprocal grid structure is a structural system consisting of mutually supporting bars. Its geometry should satisfy not only the demands of architectural intents but also the requirements of the lapping relationship of the bars. Thus, form generation is the key problem in its design. Inspired by the physical building process of a reciprocal grid structure, self‐adaptive form generation method is proposed. In this method, an initial plane grid with the topology of required structural configuration is created first. Next, elements are iteratively lapped to realize a self‐adaptive generation of structural form. Two new parameters, bar lapping factor and rotation angle, are proposed to describe reciprocal grid structures quantitatively and make the form generation process easy. The efficiency and accuracy of the method are illustrated by comparisons with other form generation methods. Numerical examples demonstrate the applicability of the proposed method in the complex and realistic reciprocal grid structures. [ABSTRACT FROM AUTHOR]

Abstract: Free‐form grid structure is a kind of structure whose shape cannot be expressed by analytical functions. Although this kind of structure has been widely used in practice, how to generate the structural shapes that not only satisfy architectural requirements but also have excellent mechanical properties is still a problem. This article focuses on the shape generation of complex grid structures and proposes a novel shape‐generation method for free‐form grid structures. The method integrates numerical inverse hanging method and multiobjective optimization. First, it uses numerical inverse hanging method to generate structural shapes in low bending moment level. Next, it uses dynamic weight multiobjective firefly optimization algorithm to adjust the parameters of the inverse hanging method adaptively so that the structural shape can satisfy architectural requirements. Comparisons with former shape‐generation methods show that the proposed method is more effective. Numerical examples based on real structures illustrate the applicability of the proposed method in practice. [ABSTRACT FROM AUTHOR]