ABSTRACT

This paper presents a fuzzy logic-based deterioration prediction models for gap and open-graded asphalt surfaces when both dynamic loading and shallow flooding coincide. The impact of aggregate size, load frequency, compaction levels, and environmental conditions was evaluated in a controlled laboratory testing to measure cracking and rutting performance of each mixture. A set of fuzzy logic was developed using the experimental data and then tested against randomly selected samples. The predicted cracking and rutting showed excellent agreements (95% correlation) with the experimentally measured values. The validation and sensitivity analysis showed that irrespective of aggregate gradation, mixture parameters (aggregate size, void contents), traffic parameters (loading frequency) and environmental factors (wet and dry condition) have a significant impact on model performance. Overall, the Fuzzy-based prediction model showed the potential to differentiate the performance of different asphalt surfaces and can be further developed to use in practical applications.

摘要

本文提出了一种基于模糊逻辑的基于模糊逻辑的劣化预测模型，适用于动态加载和浅水泛滥同时发生时的间隙和开放级配沥青表面。在受控的实验室测试中评估骨料尺寸、加载频率、压实水平和环境条件的影响，以测量每种混合物的开裂和车辙性能。使用实验数据开发了一组模糊逻辑，然后针对随机选择的样本进行测试。预测的开裂和车辙与实验测量值显示出极好的一致性（95% 相关性）。验证和敏感性分析表明，无论骨料级配、混合参数（骨料尺寸、空隙含量）如何，交通参数（加载频率）和环境因素（潮湿和干燥条件）对模型性能有显着影响。总体而言，基于模糊的预测模型显示了区分不同沥青表面性能的潜力，并且可以进一步开发以用于实际应用。