The topology optimization of reinforced-concrete (RC) building frames is relatively underexplored compared to steel structures, partly due to the lack of a systematic approach to generate and select ground structures (GS). Existing methods often use less systematic GS strategies, limiting efficient exploration of the vast and sparse design space shaped by large bay widths and story heights. This work addresses this gap by providing a comprehensive and systematic pipeline tailored for RC frames. The key contributions are: (1) development of a GS generation framework that systematically enumerates all feasible RC frame configurations within user-defined constraints, (2) introduction of a candidate GS selection map, a surrogate-based tool employing graph-based Latin hypercube sampling (LHS) and sparse Gaussian Process (GP) models, which predicts compliance early and strategically guides candidate selection, reducing computational cost by limiting full finite-element evaluations to the order of 103 out of up to 105 generated frames while serving as a reference for understanding design-parameter influences; and (3) implementation of an integrated topology-optimization pipeline applying particle swarm optimization (PSO) to selected candidates, achieving efficient compliance minimization with reduced computational effort. The complete workflow—which spans GS generation, surrogate-based candidate selection, and iterative optimization—is implemented and validated in two design domains with width-to-height aspect ratios of 1:1 and 1:1.5 and generates 438,984 and 104,032 different frame configurations, respectively. These selected candidates undergo PSO-based optimization, yielding designs with volume fractions below 0.55 and preserving critical floor beams, demonstrating the framework’s ability to identify structurally efficient stiffness-driven RC frame topologies for early-stage screening. The framework is designed as an extensible foundation that can be coupled with more detailed member-level design checks and nonlinear RC analysis in future work, rather than replacing full reinforced-concrete design procedures.
Alemu et al. (Sun,) studied this question.