Journal of Road Engineering最新文献_第2页

State of the art review on inorganic powders modified asphalt materials: Reducing the temperature of asphalt pavement 无机粉体改性沥青材料的研究进展：降低沥青路面温度

Journal of Road Engineering

Pub Date : 2025-06-01 DOI: 10.1016/j.jreng.2025.01.001

Chaohui Wang , Tonghao Zhang , Anquan Li , Dawei Zhao , Luqing Liu , Qian Chen

To reduce the temperature diseases of asphalt pavement, improve the service quality of road and extend service life, the research of inorganic powders that reduce the temperature of asphalt pavements was systematically sorted out. The common types, physicochemical properties and application methods of inorganic powders were defined. The road performances of modified asphalt and its mixture were evaluated. The modification mechanism of inorganic powders in asphalt was analyzed. On this basis, the cooling effect and cooling mechanism of inorganic powders was revealed. The results indicate that inorganic powders are classified into hollow, porous, and energy conversion types. The high-temperature performance of inorganic powders modified asphalt and its mixture is significantly improved, while there is no significant change in low-temperature performance and water stability. The average increase in rutting resistance factor (G∗/sin(δ)) and dynamic stability is 40%–72% and 30%–50%, respectively. The modification mechanism of inorganic powders in asphalt is physical blending. The thermal conductivity of hollow and porous inorganic powders modified asphalt mixture decreases by 30.05% and 43.14%, respectively. The temperature of hollow, porous and energy conversion inorganic powders modified asphalt mixture at 5 cm decreases by 2.3 °C–3.5 °C, 0.8 °C–3.7 °C and 4.1 °C–4.7 °C, respectively. Hollow and porous inorganic powders block heat conduction, while energy conversion inorganic powders achieve cooling through their functional properties.

为了减少沥青路面的温病，提高道路的使用质量，延长使用寿命，对沥青路面无机降温粉的研究进行了系统的梳理。介绍了无机粉体的常用种类、理化性质及应用方法。对改性沥青及其混合料的道路性能进行了评价。分析了无机粉体在沥青中的改性机理。在此基础上，揭示了无机粉体的冷却效果和冷却机理。结果表明，无机粉体可分为空心型、多孔型和能量转换型。无机粉体改性沥青及其混合料的高温性能明显提高，而低温性能和水稳定性无明显变化。车辙阻力因子（G∗/sin(δ)）和动力稳定性的平均增幅分别为40% ~ 72%和30% ~ 50%。无机粉体在沥青中的改性机理是物理共混。空心无机粉体和多孔无机粉体改性沥青混合料的导热系数分别降低了30.05%和43.14%。空心、多孔和能量转换无机粉体改性沥青混合料在5 cm处的温度分别降低2.3℃~ 3.5℃、0.8℃~ 3.7℃和4.1℃~ 4.7℃。空心多孔无机粉体阻断热传导，能量转换无机粉体通过其功能特性实现冷却。

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引用次数: 0

Advanced machine learning techniques for predicting mechanical properties of eco-friendly self-compacting concrete 预测生态友好型自密实混凝土力学性能的先进机器学习技术

Journal of Road Engineering

Pub Date : 2025-06-01 DOI: 10.1016/j.jreng.2024.12.002

Arslan Qayyum Khan , Syed Ghulam Muhammad , Ali Raza , Amorn Pimanmas

This study evaluates the performance of advanced machine learning (ML) models in predicting the mechanical properties of eco-friendly self-compacting concrete (SCC), with a focus on compressive strength, V-funnel time, L-box ratio, and slump flow. The motivation for this study stems from the increasing need to optimize concrete mix designs while minimizing environmental impact and reducing the reliance on costly physical testing. Six ML models-backpropagation neural network (BPNN), random forest regression (RFR), K-nearest neighbors (KNN), stacking, bagging, and eXtreme gradient boosting (XGBoost)-were trained and validated using a comprehensive dataset of 239 mix design parameters. The models' predictive accuracies were assessed using the coefficient of determination, mean squared error, root mean squared error, and mean absolute error. XGBoost consistently outperformed other models, achieving the coefficient of determination values of 0.999, 0.933, and 0.935 for compressive strength in the training, validation, and testing datasets, respectively. Sensitivity analysis revealed that cement, silica fume, coarse aggregate, and superplasticizer positively influenced compressive strength, while water content had a negative impact. These findings highlight the potential of ML models, particularly XGBoost and RFR, in optimizing SCC mix designs, reducing reliance on physical testing, and enhancing sustainability in construction. The application of these models can lead to more efficient and eco-friendly concrete mix designs, benefiting real-world construction projects by improving quality control and reducing costs.

本研究评估了先进的机器学习（ML）模型在预测环保自密实混凝土（SCC）力学性能方面的性能，重点关注抗压强度、v漏斗时间、l盒比和坍落度流动。这项研究的动机源于对优化混凝土配合比设计的日益增长的需求，同时最大限度地减少对环境的影响，减少对昂贵的物理测试的依赖。六个ML模型-反向传播神经网络（BPNN），随机森林回归（RFR）， k近邻（KNN），堆叠，袋装和极端梯度增强(XGBoost)-使用239个混合设计参数的综合数据集进行训练和验证。使用决定系数、均方误差、均方根误差和平均绝对误差来评估模型的预测准确性。XGBoost始终优于其他模型，在训练、验证和测试数据集的抗压强度决定系数分别为0.999、0.933和0.935。敏感性分析表明，水泥、硅灰、粗骨料和高效减水剂对抗压强度有正向影响，而含水量有负向影响。这些发现突出了ML模型，特别是XGBoost和RFR在优化SCC混合设计、减少对物理测试的依赖以及提高施工可持续性方面的潜力。这些模型的应用可以带来更高效和环保的混凝土混合设计，通过提高质量控制和降低成本，使现实世界的建筑项目受益。

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引用次数: 0

Deploying machine learning for long-term road pavement moisture prediction: A case study from Queensland, Australia 将机器学习用于长期道路路面湿度预测：来自澳大利亚昆士兰州的案例研究

Journal of Road Engineering

Pub Date : 2025-06-01 DOI: 10.1016/j.jreng.2024.12.007

Ayesh Dushmantha , Ruixuan Zhang , Yilin Gui , Jinjiang Zhong , Chaminda Gallage

Moisture accumulation within road pavements, particularly in unbound granular materials with or without thin sprayed seals, presents significant challenges in high-rainfall regions such as Queensland. This infiltration often leads to various forms of pavement distress, eventually causing irreversible damage to the pavement structure. The moisture content within pavements exhibits considerable dynamism and directly influenced by environmental factors such as precipitation, air temperature, and relative humidity. This variability underscores the importance of monitoring moisture changes using real-time climatic data to assess pavement conditions for operational management or incorporating these effects during pavement design based on historical climate data. Consequently, there is an increasing demand for advanced, technology-driven methodologies to predict moisture variations based on climatic inputs. Addressing this gap, the present study employs five traditional machine learning (ML) algorithms, K-nearest neighbors (KNN), regression trees, random forest, support vector machines (SVMs), and gaussian process regression (GPR), to forecast moisture levels within pavement layers over time, with varying algorithm complexities. Using data collected from an instrumented road in Brisbane, Australia, which includes pavement moisture and climatic factors, the study develops predictive models to forecast moisture content at future time steps. The approach incorporates current moisture content, rather than averaged values, along with seasonality (both daily and annual), and key climatic factors to predict next step moisture. Model performance is evaluated using R², MSE, RMSE, and MAPE metrics. Results show that ML algorithms can reliably predict long-term moisture variations in pavements, provided optimal hyperparameters are selected for each algorithm. The best-performing algorithms include KNN (the number of neighbours equals to 15), medium regression tree, medium random forest, coarse SVM, and simple GPR, with medium random forest outperforming the others. The study also identifies the optimal hyperparameter combinations for each algorithm, offering significant advancements in moisture prediction tools for pavement technology.

路面上的水分积累，特别是在未粘结的颗粒材料中，有或没有薄喷密封，在昆士兰等高降雨地区提出了重大挑战。这种渗透往往会导致各种形式的路面破损，最终对路面结构造成不可逆的破坏。路面含水率表现出相当大的动态性，并直接受到降水、气温、相对湿度等环境因素的影响。这种可变性强调了利用实时气候数据监测湿度变化的重要性，以评估路面状况的运营管理，或在基于历史气候数据的路面设计中纳入这些影响。因此，对基于气候输入预测湿度变化的先进技术驱动方法的需求日益增加。为了解决这一问题，本研究采用了五种传统的机器学习（ML）算法，即k近邻（KNN）、回归树、随机森林、支持向量机（svm）和高斯过程回归（GPR），以不同的算法复杂性预测路面层内的水分水平。该研究利用从澳大利亚布里斯班的一条仪表道路收集的数据，包括路面湿度和气候因素，开发了预测模型，以预测未来时间步骤的水分含量。该方法结合了当前的水分含量，而不是平均值，以及季节性（每日和每年）和关键的气候因素来预测下一步的水分。使用R2、MSE、RMSE和MAPE度量来评估模型性能。结果表明，只要为每个算法选择最优的超参数，ML算法可以可靠地预测路面的长期湿度变化。表现最好的算法包括KNN（邻居数等于15）、中等回归树、中等随机森林、粗SVM和简单GPR，其中中等随机森林的表现优于其他算法。该研究还确定了每种算法的最佳超参数组合，为路面技术的湿度预测工具提供了重大进展。

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引用次数: 0

Evaluation of HMA and WMA RAP mixture using hydrogenated castor oil flakes 氢化蓖麻油片对HMA和WMA RAP混合料的评价

Journal of Road Engineering

Pub Date : 2025-06-01 DOI: 10.1016/j.jreng.2024.10.002

Soumya Ranjan Baral, Anwesha Rath, Hemanta Kumar Behera, Sudhanshu Sekhar Das

In this study, reclaimed asphalt pavement (RAP) used in different percentages in hot mix asphalt (HMA) and warm mix asphalt (WMA) were tested for moisture, fracture and rutting resistance adding hydrogenated castor oil flakes (HCOF) as rejuvenating agent. Volumetric and Marshall parameters were evaluated for both types of mixtures. Addition of 5% of HCOF by weight of binder content in RAP found to restore properties of aged binder. WMA mix was made by adding 0.1% Zycotherm by weight of optimum binder content. Moisture, rutting and fracture damage performance were assessed utilizing indirect tensile strength, wheel tracking and semi-circular bending tests. The mix's tensile strength ratio increased by 2.3% in the HMA with RAP (HMA-R) mix compared to the WMA with RAP (WMA-R) mix at 10% RAP content. HMA mixes provide better resistance to rutting compared to WMA. However, 40% of RAP content HMA-R and WMA-R using HCOF rejuvenator shows greater rutting performance compared to other RAP mix. HMA-R mix fracture resistance increased by 18.14% compared to WMA-R mix when RAP content increases to 40%. Regression analyses were carried out to validate the strain energy found from fracture damage analysis of both HMA-R and WMA-R with R² value more than 0.9. HMA-R protected moisture and fracture damage better than WMA-R. The rejuvenating efficiency of HCOF was further validated using Fourier transform infrared and microscopic analysis.

在热拌沥青（HMA）和温拌沥青（WMA）中添加不同比例的再生沥青路面（RAP），并添加氢化蓖麻油片（HCOF）作为回春剂，测试了再生沥青路面（RAP）的抗湿性、抗断裂性和抗车辙性。对两种混合物的体积和马歇尔参数进行了评估。在RAP中加入5%的HCOF（按粘结剂重量计）可以恢复老化粘结剂的性能。以最佳粘结剂质量比为0.1%的Zycotherm配制WMA混合料。利用间接拉伸强度、车轮跟踪和半圆弯曲试验来评估水分、车辙和断裂损伤性能。当RAP含量为10%时，HMA与RAP （HMA- r）混合料的抗拉强度比WMA与RAP （WMA- r）混合料提高2.3%。与WMA相比，HMA混合物具有更好的抗车辙性。然而，与其他RAP组合相比，40% RAP含量的HMA-R和WMA-R使用HCOF恢复剂表现出更好的车辙性能。当RAP含量增加到40%时，HMA-R混合料的抗断裂性能比WMA-R混合料提高了18.14%。通过回归分析验证HMA-R和WMA-R断裂损伤分析得到的应变能，R2值均大于0.9。HMA-R比WMA-R更能保护水分和断裂损伤。利用傅里叶红外变换和显微分析进一步验证了HCOF的回春效果。

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引用次数: 0

RAP agglomeration and partial blending of recycled hot mix asphalt: A literature review RAP团聚与再生热混合沥青的部分共混：文献综述

Journal of Road Engineering

Pub Date : 2025-06-01 DOI: 10.1016/j.jreng.2024.12.006

Xinman Ai, Zhongshi Pei, Ke Xu, Wenyi Zhou, Ying Wang, Decheng Feng, Junyan Yi

Current mix design practices typically assume total blending and use the white curve of reclaimed asphalt pavement (RAP) to determine the gradation and optimum asphalt content (OAC) of recycled hot mix asphalt (HMA), often overlooking the effects of RAP agglomeration and partial blending. This oversight can result in unsatisfactory performance, particularly when higher RAP content is used. Therefore, this paper reviews and discusses strategies for adjusting the mix design of recycled HMA to enhance its in-service performance. The discussion begins with RAP particle agglomeration, a significant phenomenon that significantly impacts the aggregate gradation of recycled HMA. Subsequently, detection methods to clarify the blending between virgin and RAP binders are described. Partial blending between RAP and virgin binders is common, and various indexes have been proposed to quantify the blending degree. Finally, the adjusted mix design method of recycled HMA is presented, emphasizing gradation optimization and corrected OAC. Gradation optimization should account for RAP agglomeration, while the corrected OAC should consider particle blending. Recycled HMA using the adjusted mix design exhibits improved crack resistance and fatigue life without substantially impairing rutting performance. This review aims to help both academics and highway agencies maximize the utilization of RAP materials within sustainable pavement frameworks.

目前的配合比设计实践通常假设完全共混，并使用再生沥青路面（RAP）的白曲线来确定再生热混合沥青（HMA）的级配和最佳沥青含量（OAC），往往忽略RAP团聚和部分共混的影响。这种疏忽可能导致不满意的性能，特别是当使用更高的RAP内容时。因此，本文回顾和探讨了调整回收HMA的混合设计策略，以提高其使用性能。讨论从RAP颗粒团聚开始，这是一种显著影响再生HMA骨料级配的重要现象。随后，描述了澄清原生粘结剂和RAP粘结剂之间共混的检测方法。RAP与原生粘结剂之间的部分共混是常见的，并提出了各种指标来量化共混程度。最后，提出了再生HMA的调整配合比设计方法，强调级配优化和修正OAC。级配优化应考虑RAP团聚，而修正后的OAC应考虑颗粒共混。使用调整混合设计的回收HMA显示出更好的抗裂性和疲劳寿命，而不会大大损害车辙性能。本综述旨在帮助学术界和公路机构在可持续路面框架内最大限度地利用RAP材料。

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引用次数: 0

Application of isocyanate-based materials in asphalt pavement: A review 异氰酸酯基材料在沥青路面中的应用综述

Journal of Road Engineering

Pub Date : 2025-06-01 DOI: 10.1016/j.jreng.2024.12.005

Xing Gong , Quantao Liu , Haiqin Xu , Huan Wang , Shaopeng Wu

Isocyanate and its products are playing an increasingly important role in the high-performance development of asphalt pavement, but researchers have always focused on polyurethane (PU), one of the isocyanate products, and neglected the other roles of isocyanate-based materials in asphalt pavement. The application of isocyanate-based materials in asphalt pavement is still in the exploratory stage, and the research direction is not clear. It is necessary to summarize and propose research directions for the application of isocyanate-based materials in asphalt pavement. Therefore, this paper reviews the application of isocyanate-based materials in asphalt pavement, classifies the products synthesized from isocyanate for asphalt binder, introduces the application effects of different isocyanate-based materials in asphalt binder, and analyzes the limitations of each material. Meanwhile, the other roles of isocyanate-based materials in asphalt pavement, such as coating materials and adhesive materials, are summarized. Finally, the development direction of isocyanate-based materials in asphalt pavement is prospected. Isocyanate-based materials are expected to significantly increase the service life of asphalt pavement because of their excellent properties. With the advancement of technology, the application of isocyanate-based materials will become more and more common, promoting the sustainable development of road construction. This paper can provide a reference for the development and application of isocyanate-based materials in asphalt pavement.

异氰酸酯及其制品在沥青路面高性能发展中发挥着越来越重要的作用，但研究人员一直将重点放在异氰酸酯产品之一聚氨酯（PU）上，而忽视了异氰酸酯基材料在沥青路面中的其他作用。异氰酸酯基材料在沥青路面中的应用尚处于探索阶段，研究方向尚不明确。有必要对异氰酸酯基材料在沥青路面中的应用进行总结并提出研究方向。因此，本文综述了异氰酸酯基材料在沥青路面中的应用，对由异氰酸酯合成的沥青粘结剂产品进行了分类，介绍了不同异氰酸酯基材料在沥青粘结剂中的应用效果，并分析了每种材料的局限性。同时，总结了异氰酸酯基材料在沥青路面中的其他作用，如涂层材料和粘结材料。最后，展望了异氰酸酯基材料在沥青路面中的发展方向。异氰酸酯基材料由于其优异的性能，有望显著提高沥青路面的使用寿命。随着技术的进步，异氰酸酯基材料的应用将越来越普遍，促进道路建设的可持续发展。本文可为异氰酸酯基材料在沥青路面中的开发和应用提供参考。

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引用次数: 0

Soft computing applications in asphalt pavement: A comprehensive review of data-driven techniques using response surface methodology and machine learning 软计算在沥青路面上的应用：使用响应面方法和机器学习的数据驱动技术的全面回顾

Journal of Road Engineering

Pub Date : 2025-06-01 DOI: 10.1016/j.jreng.2024.12.003

Nura Shehu Aliyu Yaro , Muslich Hartadi Sutanto , Mohd Rosli Hainin , Noor Zainab Habib , Aliyu Usman , Muhammad Sani Bello , Surajo Abubakar Wada , Abiola Usman Adebanjo , Ahmad Hussaini Jagaba

The asphalt pavement industry is transforming because of the growing influence of artificial intelligence and industrial digitization. As a result of this shift, there is a stronger emphasis on advanced statistical approaches like optimization tools like response surface methodology (RSM) and machine learning (ML) techniques. The goal of this paper is to provide a scientometric and systematic review of the application of RSM and ML applications in data-driven approaches such as optimizing, modeling, and predicting asphalt pavement performance to achieve sustainable asphalt pavements in support of numerous sustainable development goals (SDGs). These include Goals 9 (sustainable infrastructure), 11 (urban resilience), 12 (sustainable construction strategies), 13 (climate action through optimized materials), and 17 (multidisciplinary interaction). A thorough search of the ScienceDirect, Web of Science, and Scopus databases from 2010 to 2023 yielded 1249 relevant records, with 125 studies closely examined. Over the last thirteen years, there has been significant research growth in RSM and ML applications, particularly in ML-based pavement optimization. The study shows that the topic has a global presence, with notable contributions from Asia, North America, Europe, and other continents. Researchers have concentrated on utilizing sophisticated ML models such as support vector machines (SVM), artificial neural networks (ANN), and Bayesian networks for prediction. Also, the integration of RSM and ML provides a faster and more efficient method for analyzing large datasets to optimize asphalt pavement performance variables. Key contributors include the United States, China, and Malaysia, with global efforts focused on sustainable materials and approaches to reduce impact on the environment. Furthermore, the review demonstrates the integrated use of RSM and ML as transformative tools for improving sustainability, which contributes significantly to SDGs 9, 11, 12, 13, and 17. Providing valuable insights for future research and guiding decision-making for soft computing applications for asphalt pavement projects.

由于人工智能和工业数字化的影响越来越大，沥青路面行业正在转型。由于这种转变，人们更加重视先进的统计方法，如响应面方法（RSM）和机器学习（ML）技术等优化工具。本文的目标是对RSM和ML在数据驱动方法（如优化、建模和预测沥青路面性能）中的应用进行科学计量和系统回顾，以实现可持续沥青路面，支持众多可持续发展目标（sdg）。其中包括目标9（可持续基础设施）、11（城市韧性）、12（可持续建筑战略）、13（通过优化材料采取气候行动）和17（多学科互动）。从2010年到2023年，对ScienceDirect、Web of Science和Scopus数据库进行了彻底的搜索，得出了1249条相关记录，其中125项研究得到了仔细检查。在过去的13年里，在RSM和ML应用方面的研究有了显著的增长，特别是在基于ML的路面优化方面。研究表明，这个话题在全球范围内都存在，亚洲、北美、欧洲和其他大洲都有显著的贡献。研究人员专注于利用复杂的ML模型，如支持向量机（SVM）、人工神经网络（ANN）和贝叶斯网络进行预测。此外，RSM和ML的集成提供了一种更快、更有效的方法来分析大型数据集，以优化沥青路面性能变量。主要贡献者包括美国、中国和马来西亚，全球努力的重点是可持续材料和减少对环境影响的方法。此外，该报告还展示了RSM和ML作为改善可持续性的变革性工具的综合使用，这对可持续发展目标9、11、12、13和17做出了重大贡献。为沥青路面工程软计算应用的未来研究和指导决策提供有价值的见解。

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引用次数: 0

Learning models for predicting pavement friction based on non-contact texture measurements: Comparative assessment 基于非接触纹理测量预测路面摩擦的学习模型：比较评估

Journal of Road Engineering

Pub Date : 2025-06-01 DOI: 10.1016/j.jreng.2024.11.003

Xiuquan Lin , You Zhan , Zilong Nie , Joshua Qiang Li , Xinyu Zhu , Allen A. Zhang

Ensuring highway safety relies heavily on pavement friction resistance. To enable network-level pavement skid resistance monitoring and management, this study proposes a non-contact three-dimensional laser surface testing method to obtain detailed aggregate surface data. The existing contact-based skid resistance measurement methods suffer from poor reproducibility and repeatability, hindering their application for network-level management. In this research, traditional multiple linear regression and four machine learning methods, support vector machine (SVM), random forest (RF), gradient boosting decision tree (GBDT), and convolutional neural network (CNN), are utilized to evaluate and predict pavement frictional performance. To assess the proposed methods, data from 45 pavement sites in Oklahoma, including 6 major preventive maintenance (PM) treatments and 7 typical types of aggregates, are collected. Parallel data acquisition is conducted at highway speeds using a grip tester and a high-speed texture profiler to measure pavement skid resistance and surface macro-texture, respectively. Aggregate properties are captured in 3D using a portable ultra-high-resolution 3D laser imaging scanner, leading to the calculation of four types of 3D aggregate parameters characterizing the micro-texture of aggregate surfaces. The relationship between pavement surface friction and texture is explored using machine learning models. The results reveal that the random forest and gradient boosting decision tree models exhibit the highest accuracy, SVM and CNN perform moderately, while the traditional linear regression method fares the worst. By assessing the importance of the 38 parameter variables, the most critical 21 variables were selected for model development. Test results demonstrate that the GBDT model exhibits the best predictive performance, with an explanatory capability of 87.4% for road friction performance. The findings demonstrate the feasibility of replacing contact-based pavement friction evaluation with non-contact texture measurements, offering promising prospects for a network-level pavement skid resistance monitoring and management system.

保证公路安全在很大程度上依赖于路面摩擦阻力。为了实现网级路面防滑监测和管理，本研究提出了一种非接触式三维激光路面检测方法，以获得详细的路面汇总数据。现有的接触式防滑性测量方法存在再现性和可重复性差的问题，阻碍了其在网络级管理中的应用。本研究利用传统的多元线性回归和支持向量机（SVM）、随机森林（RF）、梯度增强决策树（GBDT）和卷积神经网络（CNN）四种机器学习方法对路面摩擦性能进行评估和预测。为了评估所提出的方法，收集了俄克拉荷马州45个路面站点的数据，包括6种主要的预防性养护（PM）处理和7种典型的骨料类型。采用高速抓地力测定仪和高速纹理测定仪在高速公路上进行并行数据采集，分别测量路面防滑性和路面宏观纹理。使用便携式超高分辨率3D激光成像扫描仪以3D方式捕获骨料特性，从而计算出表征骨料表面微观纹理的四种3D骨料参数。使用机器学习模型探索路面表面摩擦与纹理之间的关系。结果表明，随机森林和梯度增强决策树模型的准确率最高，SVM和CNN的准确率中等，而传统线性回归方法的准确率最差。通过评估38个参数变量的重要性，选择最关键的21个变量进行模型开发。试验结果表明，GBDT模型对路面摩擦性能的解释能力为87.4%，具有较好的预测效果。研究结果表明，用非接触式纹理测量取代接触式路面摩擦评价是可行的，为网络级路面防滑监测和管理系统提供了广阔的前景。

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引用次数: 0

Research progress of intelligent testing technology and evaluation methods for subgrade engineering 路基工程智能检测技术与评价方法研究进展

Journal of Road Engineering

Pub Date : 2025-06-01 DOI: 10.1016/j.jreng.2025.03.001

Guojun Cai , Hongliang Tian , Lulu Liu , Xiaoyan Liu , Songyu Liu

Subgrade engineering is a fundamental aspect of infrastructure construction in China. As the primary structural element responsible for bearing and distributing traffic loads, the subgrade must not only withstand the substantial pressures exerted by vehicles, trains, and other forms of transportation, but also efficiently transfer these loads to the underlying foundation, ensuring the stability and longevity of the roadway. In recent years, advancements in subgrade engineering technology have propelled the industry towards smarter, greener, and more sustainable practices, particularly in the areas of intelligent monitoring, disaster management, and innovative construction methods. This paper reviews the application and methodologies of intelligent testing equipment, including cone penetration testing (CPT) devices, soil resistivity testers, and intelligent rebound testers, in subgrade engineering. It examines the operating principles, advantages, limitations, and application ranges of these tools in subgrade testing. Additionally, the paper evaluates the practical use of advanced equipment from both domestic and international perspectives, addressing the challenges encountered by various instruments in real-world applications. These devices enable precise, comprehensive testing and evaluation of subgrade conditions at different stages, providing real-time data analysis and intelligent early warnings. This supports effective subgrade health management and maintenance. As intelligent technologies continue to evolve and integrate, these tools will increasingly enhance the accuracy, efficiency, and sustainability of subgrade monitoring.

路基工程是中国基础设施建设的一个基本方面。路基作为承载和分配交通荷载的主要结构构件，不仅要承受车辆、火车和其他运输方式施加的巨大压力，而且要将这些荷载有效地传递给下层基础，确保道路的稳定性和寿命。近年来，路基工程技术的进步推动了该行业朝着更智能、更环保、更可持续的方向发展，特别是在智能监控、灾害管理和创新施工方法等领域。本文综述了智能测试设备在路基工程中的应用及其方法，包括锥突探深仪、土壤电阻率测试仪、智能回弹测试仪等。它考察了这些工具在路基测试中的工作原理、优点、局限性和应用范围。此外，本文还从国内外的角度评估了先进设备的实际应用，解决了各种仪器在实际应用中遇到的挑战。这些设备可以精确、全面地测试和评估不同阶段的路基状况，提供实时数据分析和智能预警。这支持有效的路基健康管理和维护。随着智能技术的不断发展和整合，这些工具将日益提高路基监测的准确性、效率和可持续性。

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引用次数: 0

Hydrogen peroxide activation of waste tire crumb rubber for improving compatibility with bitumen: Laboratory and molecular dynamics insights 过氧化氢活化废轮胎碎橡胶以改善与沥青的相容性：实验室和分子动力学见解

Journal of Road Engineering

Pub Date : 2025-06-01 DOI: 10.1016/j.jreng.2024.12.004

Nie Tian, Piergiorgio Tataranni, Cesare Sangiorgi

Enhancing rubber-bitumen compatibility is crucial to improve pavement performance and durability. To investigate the compatibility improvement between H₂O₂-activated waste crumb rubber (AWCR) and bitumen, coarse and fine waste crumb rubber (WCR) were treated and analyzed through multi-scale characterization and molecular simulation. Microstructure and chemical changes of WCR and AWCR were analyzed with scanning electron microscope (SEM), contact angle tests and Fourier transform infrared spectroscopy (FTIR). Compatibility was also indirectly evaluated through modified boiling tests and storage stability tests. Besides, molecular dynamics was used to explore the interaction between WCR/AWCR and bitumen. SEM, contact angle, and FTIR results showed bond breakage of CC and C–C and increased polar groups like –OH and –COOH in AWCR, resulting in a rougher texture and higher surface energy. Compared with WCR, AWCR showed a lower bitumen stripping rate after boiling, and the binder with AWCR also had a lower softening point difference and segregation rate after storage. Molecular dynamics simulations further confirmed that AWCR has a closer solubility parameter and higher binding energy to bitumen than WCR, reflected in a relatively slower diffusion rate. This study provides comprehensive evidence for an eco-friendly method of WCR surface treatment for more efficient recycling of tire rubber in asphalt pavements.

提高橡胶与沥青的相容性是提高路面性能和耐久性的关键。为研究h2o2活化废橡胶颗粒（AWCR）与沥青的相容性改善情况，采用多尺度表征和分子模拟的方法对粗粒和细粒废橡胶颗粒（WCR）进行了处理和分析。采用扫描电镜（SEM）、接触角测试和傅里叶红外光谱（FTIR）分析了WCR和AWCR的微观结构和化学变化。通过改良沸腾试验和贮存稳定性试验间接评价相容性。此外，利用分子动力学方法研究了WCR/AWCR与沥青的相互作用。SEM、接触角和FTIR结果表明，AWCR中CC和C-C键断裂，-OH和-COOH等极性基团增加，使得AWCR的织构更粗糙，表面能更高。与WCR相比，AWCR在煮沸后的沥青汽提率更低，与WCR相结合的粘结剂在储存后的软化点差和离析率也更低。分子动力学模拟进一步证实了AWCR比WCR具有更接近于沥青的溶解度参数和更高的结合能，体现在相对较慢的扩散速率上。本研究为环保的WCR表面处理方法提供了全面的证据，以更有效地回收沥青路面轮胎橡胶。

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引用次数: 0