Cold climates usually expose concrete structures to frequent freeze-thaw effects, the effects are likely to create microcracks, surface scaling, and gradual material erosion of the concrete matrix, which eventually compromises compressive and tensile strength. In order to increase the durability and structural performance in such a harsh environment, fiber reinforcement has been extensively used. This paper is an exploration of the freeze-thaw resistance of concrete reinforced using three types of fibers, namely steel, basalt, and polypropylene. Cubic samples (100 x 100 x 100 mm) were made with different types of fibers, contents, and lengths in a controlled manner of freeze-thaw cycles, following standard procedures. A Random Forest Regression (RFR) model was created so that it could be used to predict the number of freeze-thaw cycles each specimen could withstand depending on the type of fiber content as well as length. The model was highly predictive with a cross-validation R²=0.9648. The analysis of feature importance showed that the most significant factors influencing the durability were fiber type and content, and the fiber length had a moderating impact. The optimum combinations of fibers were determined using the predictive model whereby steel fibers with 2.0% content and 30 mm length demonstrated the highest predicted freeze-thaw resistance of 210 cycles. This combination of experimental and data-driven research represents the opportunity of using machine learning and laboratory testing to refine fiber-reinforced concrete to withstand temperatures in extreme cold conditions. The findings present a realistic guideline to engineers in choosing types of fibers, contents, and lengths of fibers so as to maximize the durability, minimize the cost of maintenance, and increase the service life of the structures in freeze-thaw conditions that are covered with concrete.
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