Inheritance and Optimization of Mechanical Traits for Hybrid Girder Bridges: A Novel Bionic Perspective

Hybrid girder bridges can be likened to plant grafting, where mechanical traits are inherited from both rootstock and scion girders, enabling performance that exceeds that of the individual components. To quantitatively evaluate this inheritance and optimize hybrid girder performance, this study develops a bionic binary grafting model inspired by the genetic principles of quantitative trait inheritance. By analyzing the flexural behavior of hybrid girders through classical beam theory, the research explores two sequential phases: trait inheritance and trait optimization. In the inheritance phase, the bending moment is governed by the hybrid ratio and the positional advantage of scion girders. In the optimization phase, iterative refinements in girder height and internal force further enhance structural performance. The key contributions of this study are as follows: (1) a novel bionic framework is proposed to quantitatively characterize mechanical trait inheritance in hybrid girders, introducing inheritance ratios to describe the distribution of bending moment between rootstock and scion girders as functions of the hybrid ratio, stiffness ratio, and load ratio; (2) a design-oriented framework for mechanical trait optimization is developed, demonstrating that hybrid girders can achieve equivalent stress performance with reduced structural height; and (3) the proposed inheritance and optimization formulations are validated against representative engineering cases, confirming their accuracy in estimating the optimal inheritance ratio and girder height for hybrid girder bridges. This bio-inspired framework enhances our understanding of hybrid girder performance enhancement mechanisms, enabling the efficient optimization of structural systems during conceptual design by leveraging materials with diverse mechanical properties.