Mechanical foaming of asphalt can effectively reduce mixing and compaction temperatures, thereby ensuring the superior road performance of the resulting asphalt mixtures. However, current indicators for evaluating asphalt foaming performance are largely singular and fixed, failing to reflect the variable temperature, water content, and equipment conditions in actual asphalt plants. Similarly, existing methods for determining optimal foaming conditions rely on laboratory-fixed settings or single metrics, limiting their applicability and reliability for practical field production. In this study, the asphalt foam collapse test (AFCT) was conducted on 70# asphalt, 90# asphalt, and SBS-modified asphalt using a laser sensor system. Based on the four evaluation indicators—expansion ratio (ER), half-life (HL), foam index (FI), and surface area index (SAI)—the foaming performance of three types of asphalt was comprehensively analyzed. Subsequently, the effects of varying water content and foaming temperature on these two indicators were investigated. Unlike the monotonic trends observed in expansion ratio and half-life, both FI and SAI exhibited peak values under specific conditions. Building upon this analysis, interpolation and simulation methods using MATLAB were employed to develop an optimization approach for determining the optimal foaming conditions. Furthermore, the rationality of the proposed optimization method was verified through workability and coating tests of foamed asphalt mixtures. The results demonstrate that the proposed method yields a range of optimal foaming temperatures and water contents rather than a single fixed value, making it more consistent with practical engineering applications.
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