Optimizing Foamed Bitumen Mixtures: AI-Based Determination of Ideal RAP and FBC Percentages Using HWTT and ITS Data
Source abstract
Abstract
The combination of reclaimed asphalt pavement (RAP) and foamed bitumen content (FBC) in bitumen mixtures presents a viable and economically advantageous approach to asphalt pavement construction. This investigation delves into the optimal combinations of RAP and FBC to attain a perfect performance, particularly concerning rutting resistance and tensile strength, as assessed through the Hamburg Wheel Tracking Test (HWTT) and the Indirect Tensile Strength (ITS) test. Advanced artificial intelligence (AI) methodologies, such as Random Forest, Support Vector Regression (SVR), and Linear Regression, were utilized to check performance data and attain optimal mix designs. The findings indicate that RAP content ranging from 60% to 80%, in conjunction with FBC levels between 1.5% and 1.8%, yield the most adequate performance under both wet and dry conditions, confirming enhanced rutting resistance and tensile strength.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Asphalt Pavement Performance Evaluation · Infrastructure Maintenance and Monitoring · Drilling and Well Engineering
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Transport Construction and Water Management, Faculty of Civil Engineering, Széchenyi István University, Egyetem Square 1, H-9026 Győr, Hungary
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