Thermodynamically consistent damage-plasticity model for fire-resistant design and optimization of reinforced concrete beams

Current fire design methods of reinforced concrete structures are marred with inaccurate model representation, undisciplined parameter study, and limited optimization applications. In this study, a thermodynamically consistent temperature-dependent plasticity model for concrete damage is formulated, thoroughly examines design parameters, and proposes a multi-objective optimization platform. Using sequential thermal-mechanical coupled finite element analysis, the model produces average errors of 7.9% and 2.9% at the material and structural levels, respectively, which is far better than traditional approaches with 15%–20% errors. Parametric sensitivity analysis indicates that load ratio and concrete cover thickness alone contribute 71% of all the variance in fire resistance time. Increasing cover thickness from 25 to 45 mm enhances fire resistance by 94%, and increasing load ratio from 0.3 to 0.7 reduces fire resistance time by 58%. The non-dominated sorting genetic algorithm-based optimization model obtains 23 non-dominated solutions, of which three chosen representative designs achieve material savings of 31.4%, 23.7%, and 8.8%, respectively. In comparison with traditional code-based design methods, this approach yields significant improvements in three areas: accuracy of prediction, efficiency in the utilization of materials, and flexibility in design. The established framework offers an integrated solution to performance-based fire design and may be extended to other structural members like slabs, columns, and frame systems.