Pub Date : 2023-11-22DOI: 10.1080/14680629.2023.2281956
Helena Miera-Domínguez, Pedro Lastra-González, Irune Indacoechea-Vega, Daniel Castro-Fresno
Pollution of the environment by microplastics is a problem that is increasingly visible and worrisome, with tyre wear particles (TWPs) being considered, after several studies, as one of the major s...
{"title":"What is known and unknown concerning microplastics from tyre wear?","authors":"Helena Miera-Domínguez, Pedro Lastra-González, Irune Indacoechea-Vega, Daniel Castro-Fresno","doi":"10.1080/14680629.2023.2281956","DOIUrl":"https://doi.org/10.1080/14680629.2023.2281956","url":null,"abstract":"Pollution of the environment by microplastics is a problem that is increasingly visible and worrisome, with tyre wear particles (TWPs) being considered, after several studies, as one of the major s...","PeriodicalId":21475,"journal":{"name":"Road Materials and Pavement Design","volume":null,"pages":null},"PeriodicalIF":3.7,"publicationDate":"2023-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138530105","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
AbstractThis study presented the investigation on the microstructure characteristics and the interaction among asphalt, crumb rubber (CR) and modifiers (softener, activator, and cross-linking agent) of crumb rubber compound modified asphalt (CRCMA) at process phases by microscopic testing techniques. The results showed that CRCMA had excellent rheological properties at high or low-temperature. The softener was only physically mixed with asphalt and did not change the microscopic morphology of the asphalt. The activator can break some of the chemical bonds of CR and promote the desulphurization degradation reaction which makes the asphalt show a large number of small-body type mesh structures and a small amount of chains in microscopic morphology. The crosslinking agent provided a source of sulphur to induce the crosslinking reaction which resulted in an increase in the reticulation of CRCMA. Finally, a modification mechanism model and the evolution mechanisms based on the microstructure characteristics at preparation phases of CRCMA were proposed.KEYWORDS: Crumb rubber compound modified asphaltmicroscopic testinterfacial microstructure characteristicsmechanism analysisevolution laws Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThis work was supported by the National Key Research and Development Program of China [grant number 2021YFB2600900]; the Postgraduate Scientific Research Innovation Project of Changsha University of Science and Technology [grant number CX2021SS110]; the Science and Technology Planning Project of Hunan Transportation Department of China [grant number 201825,B202112,202209]; the Changsha Natural Science Foundation of China [grant number kq2202205]; the National Natural Science Foundation of China [grant number 52178411].
{"title":"Investigation on microstructure characteristics of crumb rubber compound modified asphalt at preparation process","authors":"Hui Wang, Jia Li, Yufeng Tang, Jingpu Zhu, Weilin Huang, Xu Wang, Juan Xie","doi":"10.1080/14680629.2023.2278142","DOIUrl":"https://doi.org/10.1080/14680629.2023.2278142","url":null,"abstract":"AbstractThis study presented the investigation on the microstructure characteristics and the interaction among asphalt, crumb rubber (CR) and modifiers (softener, activator, and cross-linking agent) of crumb rubber compound modified asphalt (CRCMA) at process phases by microscopic testing techniques. The results showed that CRCMA had excellent rheological properties at high or low-temperature. The softener was only physically mixed with asphalt and did not change the microscopic morphology of the asphalt. The activator can break some of the chemical bonds of CR and promote the desulphurization degradation reaction which makes the asphalt show a large number of small-body type mesh structures and a small amount of chains in microscopic morphology. The crosslinking agent provided a source of sulphur to induce the crosslinking reaction which resulted in an increase in the reticulation of CRCMA. Finally, a modification mechanism model and the evolution mechanisms based on the microstructure characteristics at preparation phases of CRCMA were proposed.KEYWORDS: Crumb rubber compound modified asphaltmicroscopic testinterfacial microstructure characteristicsmechanism analysisevolution laws Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThis work was supported by the National Key Research and Development Program of China [grant number 2021YFB2600900]; the Postgraduate Scientific Research Innovation Project of Changsha University of Science and Technology [grant number CX2021SS110]; the Science and Technology Planning Project of Hunan Transportation Department of China [grant number 201825,B202112,202209]; the Changsha Natural Science Foundation of China [grant number kq2202205]; the National Natural Science Foundation of China [grant number 52178411].","PeriodicalId":21475,"journal":{"name":"Road Materials and Pavement Design","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135136681","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-07DOI: 10.1080/14680629.2023.2278150
Lukuan Ma, Chenchen Li, Mu Guo, Zefeng Tao
AbstractOn the 2nd runway of Shanghai Pudong International Airport, the field assessment was conducted for rigid pavement stabilization using cementitious grout. The support performance of underlying layers and voids beneath slabs were considered, and the deflection testing was performed before and after grouting. The performance of pre-treatment and post-treatment pavements, and effects of injecting depth and curing time on grouting treatment were statistically analyzed. Results indicated that the support performance of underlying layers along the wheelpath was gradually getting deteriorated and non-uniform during the service period, and the number of voids beneath slabs would also increase annually. The injecting depth at 10 cm under subbase layer was proposed for rigid pavements with the crushed stone subbase layer. Besides, the performance evaluation of cementitious grouting stabilization for rigid pavement was recommended after 60-day curing. Finally, results demonstrated that the objective of pavement stabilization for the 2nd runway was successfully achieved.KEYWORDS: Cementitious groutDeflection testingSupporting performanceVoids beneath slabsInjecting depthCuring time AcknowledgementThis work was sponsored by the National Natural Science Foundation of China (ID: 52008310).Disclosure statementNo potential conflict of interest was reported by the author(s).Author contribution statementThe authors confirm contribution to the paper as follows: study conception and design: Lukuan Ma and Mu Guo; data collection: Chenchen Li and Zefeng Tao; analysis and interpretation of results: Lukuan Ma and Zefeng Tao; draft manuscript preparation: Lukuan Ma and Mu Guo. All authors reviewed the results and approved the final version of the manuscript.Additional informationFundingThis work was supported by the National Natural Science Foundation of China: [Grant Number 52008310].
{"title":"Field assessment of rigid pavement stabilisation using cementitious grout: case study","authors":"Lukuan Ma, Chenchen Li, Mu Guo, Zefeng Tao","doi":"10.1080/14680629.2023.2278150","DOIUrl":"https://doi.org/10.1080/14680629.2023.2278150","url":null,"abstract":"AbstractOn the 2nd runway of Shanghai Pudong International Airport, the field assessment was conducted for rigid pavement stabilization using cementitious grout. The support performance of underlying layers and voids beneath slabs were considered, and the deflection testing was performed before and after grouting. The performance of pre-treatment and post-treatment pavements, and effects of injecting depth and curing time on grouting treatment were statistically analyzed. Results indicated that the support performance of underlying layers along the wheelpath was gradually getting deteriorated and non-uniform during the service period, and the number of voids beneath slabs would also increase annually. The injecting depth at 10 cm under subbase layer was proposed for rigid pavements with the crushed stone subbase layer. Besides, the performance evaluation of cementitious grouting stabilization for rigid pavement was recommended after 60-day curing. Finally, results demonstrated that the objective of pavement stabilization for the 2nd runway was successfully achieved.KEYWORDS: Cementitious groutDeflection testingSupporting performanceVoids beneath slabsInjecting depthCuring time AcknowledgementThis work was sponsored by the National Natural Science Foundation of China (ID: 52008310).Disclosure statementNo potential conflict of interest was reported by the author(s).Author contribution statementThe authors confirm contribution to the paper as follows: study conception and design: Lukuan Ma and Mu Guo; data collection: Chenchen Li and Zefeng Tao; analysis and interpretation of results: Lukuan Ma and Zefeng Tao; draft manuscript preparation: Lukuan Ma and Mu Guo. All authors reviewed the results and approved the final version of the manuscript.Additional informationFundingThis work was supported by the National Natural Science Foundation of China: [Grant Number 52008310].","PeriodicalId":21475,"journal":{"name":"Road Materials and Pavement Design","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135540327","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-07DOI: 10.1080/14680629.2023.2278149
Fardzanela Suwarto, Tony Parry, Gordon Airey
AbstractDifferent approaches continue to be used to evaluate the environmental and financial impacts of road pavements throughout their life cycle. This paper aims to provide a methodological review of published studies of asphalt pavement Life Cycle Assessment (LCA) and Life Cycle Cost Analysis (LCCA) and make recommendations for future studies. The results indicate that LCA studies limitations are related to functional units (FUs), chosen life cycle phases, maintenance schedules decision, and uncertainty. In comparison, the use of LCCA is limited to assessing maintenance strategies, is largely focused on agency cost, and usually ignores the possibility of current or future uncertainty. Accordingly, it is recommended to incorporate both LCA and LCCA, define a standard set of FUs, include the complete life cycle (including for new materials), consider pavement performance predictions in determining realistic maintenance schedules, include both short- and long-term costs and environmental impacts, and emphasise on probabilistic analysis of uncertainty.KEYWORDS: Economic analysisenvironmental analysislife cycle assessmentlife cycle cost analysisasphalt pavement AcknowledgementsThe authors of this paper would like to express their gratitude to Diponegoro University for the support provided during the research conducted.Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThe study was sponsored and fully funded by the Diponegoro University [grant number 5172/UN7.P2/KP/2020].
{"title":"Review of methodology for life cycle assessment and life cycle cost analysis of asphalt pavements","authors":"Fardzanela Suwarto, Tony Parry, Gordon Airey","doi":"10.1080/14680629.2023.2278149","DOIUrl":"https://doi.org/10.1080/14680629.2023.2278149","url":null,"abstract":"AbstractDifferent approaches continue to be used to evaluate the environmental and financial impacts of road pavements throughout their life cycle. This paper aims to provide a methodological review of published studies of asphalt pavement Life Cycle Assessment (LCA) and Life Cycle Cost Analysis (LCCA) and make recommendations for future studies. The results indicate that LCA studies limitations are related to functional units (FUs), chosen life cycle phases, maintenance schedules decision, and uncertainty. In comparison, the use of LCCA is limited to assessing maintenance strategies, is largely focused on agency cost, and usually ignores the possibility of current or future uncertainty. Accordingly, it is recommended to incorporate both LCA and LCCA, define a standard set of FUs, include the complete life cycle (including for new materials), consider pavement performance predictions in determining realistic maintenance schedules, include both short- and long-term costs and environmental impacts, and emphasise on probabilistic analysis of uncertainty.KEYWORDS: Economic analysisenvironmental analysislife cycle assessmentlife cycle cost analysisasphalt pavement AcknowledgementsThe authors of this paper would like to express their gratitude to Diponegoro University for the support provided during the research conducted.Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThe study was sponsored and fully funded by the Diponegoro University [grant number 5172/UN7.P2/KP/2020].","PeriodicalId":21475,"journal":{"name":"Road Materials and Pavement Design","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135540257","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-05DOI: 10.1080/14680629.2023.2278184
Yu Zhao, Xiaoming Liu, Daxiong Yan
AbstractMicrowave deicing is an efficient and environment-friendly technology for asphalt pavement. Previous studies have shown that silicon carbide can improve the deicing efficiency of pavement, but the influence of drastic temperature change during microwave deicing on the temperature stress and temperature fatigue life is undefined. In this study, the temperature stress during heating and cooling were analysed by numerical simulation, and the mechanism of stress change was discussed. Finally, the temperature fatigue performance of pavement was evaluated. The simulation results showed that an increase in the temperature rising rate did not necessarily increase the temperature stress, and there was no stress accumulation after microwave deicing. The temperature stress was affected by both the temperature change rate and the heat transfer performance, and good heat transfer performance of asphalt mixture could reduce the temperature stress. Besides, the drastic temperature change did not necessarily reduce the temperature fatigue life of pavement.KEYWORDS: Asphalt mixture containing silicon carbide aggregatetemperature change ratetemperature stress and straintemperature fatigue lifemicrowave heating AcknowledgementsThe authors are grateful for technical support from the High Performance Computing Center of Central South University and thank Yecheng Fan from Shiyanjia Lab (www.shiyanjia.com) for the electromagnetic parameters of SiC analysis.Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThis work was supported by National Natural Science Foundation of China: [Grant Number 52078499]; Natural Science Foundation of Hunan Province: [Grant Number 2022JJ30730]; Science and Technology Program of Hunan Province: [Grant Number No. 202246].
{"title":"Evaluation of drastic temperature change on temperature stress of asphalt mixture during microwave deicing","authors":"Yu Zhao, Xiaoming Liu, Daxiong Yan","doi":"10.1080/14680629.2023.2278184","DOIUrl":"https://doi.org/10.1080/14680629.2023.2278184","url":null,"abstract":"AbstractMicrowave deicing is an efficient and environment-friendly technology for asphalt pavement. Previous studies have shown that silicon carbide can improve the deicing efficiency of pavement, but the influence of drastic temperature change during microwave deicing on the temperature stress and temperature fatigue life is undefined. In this study, the temperature stress during heating and cooling were analysed by numerical simulation, and the mechanism of stress change was discussed. Finally, the temperature fatigue performance of pavement was evaluated. The simulation results showed that an increase in the temperature rising rate did not necessarily increase the temperature stress, and there was no stress accumulation after microwave deicing. The temperature stress was affected by both the temperature change rate and the heat transfer performance, and good heat transfer performance of asphalt mixture could reduce the temperature stress. Besides, the drastic temperature change did not necessarily reduce the temperature fatigue life of pavement.KEYWORDS: Asphalt mixture containing silicon carbide aggregatetemperature change ratetemperature stress and straintemperature fatigue lifemicrowave heating AcknowledgementsThe authors are grateful for technical support from the High Performance Computing Center of Central South University and thank Yecheng Fan from Shiyanjia Lab (www.shiyanjia.com) for the electromagnetic parameters of SiC analysis.Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThis work was supported by National Natural Science Foundation of China: [Grant Number 52078499]; Natural Science Foundation of Hunan Province: [Grant Number 2022JJ30730]; Science and Technology Program of Hunan Province: [Grant Number No. 202246].","PeriodicalId":21475,"journal":{"name":"Road Materials and Pavement Design","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135725504","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
AbstractThe abandoned carbonaceous mudstone has caused severe environmental problems such as land occupation and landslides. For the consideration of economic and ecological factors, carbonaceous mudstone soil-rock mixture (CMSRM) is used as an embankment material assessed by California bearing ratio (CBR) and unconfined compression strength (UCS). A series of experiments were conducted to measure the CBR and UCS of the CMSRM with different wet-dry cycles (0, 2, 4, 6 and 8) and different rock contents (0, 20, 40, 60 and 80%). The experimental results were predicted and analysed by a convolutional neural network (CNN). The experiment results show that the CBR and UCS of CMSRM increased at first and then decreased with the increase of rock content and were negatively correlated with wet-dry cycles. The CNN predicted values were highly correlated with the measured values. The CNN model enables variable parameter analysis of the experiment results via deep learning, which provides a new method to the CMSRM embankment road performance prediction.KEYWORDS: Carbonaceous mudstonewet-dry cyclesCalifornia bearing ratiounconfined compressive strengthconvolution neural networkprediction model Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThe authors gratefully acknowledge the financial support offered by the National Natural Science Foundation of China (52078066, 52004036, 42207204, 52378440), the Postgraduate Scientific Research Innovation Project of Hunan Province (CX20210738), the Changsha City Outstanding Innovative Youth Training Program (kq1905043), the Hunan young scientific and technological innovation talents (2020RC306), the Natural Science Foundation of Hunan Province Outstanding Youth Fund Project (2023JJ10045), the ‘Double First-class’ International Cooperation project of Changsha University of Science and Technology (2019IC04), the 2021 Bridge Engineering Safety Control Key Laboratory of Ministry of Education Open Fund Project (21KB12), the National Natural Science Foundation of Hunan Province Projects (2021JJ40572), the Open Fund of Key Laboratory of Bridge Engineering Safety Control by Department of Education (Changsha University of Science & Technology) (15KB01) and the Research Foundation of Education Bureau of Hunan Province Project (20B040).
{"title":"Road performance and prediction model for carbonaceous mudstone soil-rock mixtures under wet-dry cycles","authors":"Qiyi Yang, Wei Wen, Ling Zeng, Hongyuan Fu, Qianfeng Gao, Lu Chen, Hanbing Bian","doi":"10.1080/14680629.2023.2278146","DOIUrl":"https://doi.org/10.1080/14680629.2023.2278146","url":null,"abstract":"AbstractThe abandoned carbonaceous mudstone has caused severe environmental problems such as land occupation and landslides. For the consideration of economic and ecological factors, carbonaceous mudstone soil-rock mixture (CMSRM) is used as an embankment material assessed by California bearing ratio (CBR) and unconfined compression strength (UCS). A series of experiments were conducted to measure the CBR and UCS of the CMSRM with different wet-dry cycles (0, 2, 4, 6 and 8) and different rock contents (0, 20, 40, 60 and 80%). The experimental results were predicted and analysed by a convolutional neural network (CNN). The experiment results show that the CBR and UCS of CMSRM increased at first and then decreased with the increase of rock content and were negatively correlated with wet-dry cycles. The CNN predicted values were highly correlated with the measured values. The CNN model enables variable parameter analysis of the experiment results via deep learning, which provides a new method to the CMSRM embankment road performance prediction.KEYWORDS: Carbonaceous mudstonewet-dry cyclesCalifornia bearing ratiounconfined compressive strengthconvolution neural networkprediction model Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThe authors gratefully acknowledge the financial support offered by the National Natural Science Foundation of China (52078066, 52004036, 42207204, 52378440), the Postgraduate Scientific Research Innovation Project of Hunan Province (CX20210738), the Changsha City Outstanding Innovative Youth Training Program (kq1905043), the Hunan young scientific and technological innovation talents (2020RC306), the Natural Science Foundation of Hunan Province Outstanding Youth Fund Project (2023JJ10045), the ‘Double First-class’ International Cooperation project of Changsha University of Science and Technology (2019IC04), the 2021 Bridge Engineering Safety Control Key Laboratory of Ministry of Education Open Fund Project (21KB12), the National Natural Science Foundation of Hunan Province Projects (2021JJ40572), the Open Fund of Key Laboratory of Bridge Engineering Safety Control by Department of Education (Changsha University of Science & Technology) (15KB01) and the Research Foundation of Education Bureau of Hunan Province Project (20B040).","PeriodicalId":21475,"journal":{"name":"Road Materials and Pavement Design","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135725544","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-02DOI: 10.1080/14680629.2023.2276421
Deise Trevizan Pelissaro, Aédnor Antonio Casado Zago, Suéllen Tonatto Ferrazzo, Giovani Jordi Bruschi, Francisco Dalla Rosa
AbstractThe stabilization of recycled asphalt pavement (RAP) with alkali-activated cement (AAC) is a topic of growing interest for sustainable engineering, especially those containing alternative activators produced from waste. This study evaluated the effect of curing temperature on the stabilization of RAP with a metakaolin AAC and rice husk ash-derived activator for potential use in base and subbase layers in flexible pavement systems. Unconfined compressive strength (UCS), X-ray diffraction, and scanning electron microscopy tests were performed. Higher strength values were associated with higher temperatures and curing times. Curing oven time presented no influence over UCS and mineralogy. Blends cured at 20°C exhibited efflorescence formation and prolonged curing time at high temperatures negatively affected the mechanical performance. Curing temperature of 80°C up to 24 h promoted the formation and uniform distribution of cementing gels and a dense and compact structure, improving the compressive strength.KEYWORDS: Recycled asphalt pavementalkali-activated cementalternative alkaline activatorstrength developmentmineralogymicrostructure AcknowledgementsThe authors wish to explicit their appreciation to National Council for Scientific and Technological Development -CNPq for the support to the research group.Disclosure statementNo potential conflict of interest was reported by the author(s).Authors’ contributionsAll authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Aednor Antonio Casado Zago and Deise Trevizan Pelissaro. The first draft of the manuscript was written by Deise Trevizan Pelissaro and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. In addition, Francisco Dalla Rosa was responsible for the supervision of the research.Data availability statementSome or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
摘要碱活化水泥(AAC)稳定再生沥青路面(RAP)是可持续工程日益关注的课题，特别是那些含有从废物中产生的替代活化剂的再生沥青路面。本研究评估了固化温度对偏高岭土AAC和稻壳灰衍生活化剂在柔性路面系统基层和亚基层中的潜在应用对RAP稳定性的影响。进行无侧限抗压强度(UCS)、x射线衍射和扫描电镜测试。较高的强度值与较高的温度和固化时间有关。焙烧时间对矿物学和单束强度无明显影响。在20°C下固化的共混物表现出开花现象，高温下延长固化时间对其力学性能产生负面影响。80℃~ 24 h的养护温度促进了胶凝凝胶的形成和均匀分布，结构致密致密，提高了抗压强度。关键词:再生沥青路面碱活化水泥替代碱活化剂强度发展矿物学微观结构感谢国家科学技术发展委员会对课题组的支持。披露声明作者未报告潜在的利益冲突。作者的贡献所有作者都对研究的构思和设计做出了贡献。材料准备、数据收集和分析由Aednor Antonio Casado Zago和Deise Trevizan Pelissaro完成。手稿的初稿由Deise Trevizan Pelissaro撰写，所有作者都对之前的手稿版本进行了评论。所有作者都阅读并批准了最终的手稿。此外，弗朗西斯科·达拉·罗莎负责监督这项研究。数据可用性声明支持本研究结果的部分或全部数据、模型或代码可根据通讯作者的合理要求获得。
{"title":"Curing conditions effect on the stabilization of recycled asphalt pavement with alkali-activated metakaolin and rice husk ash-derived activator","authors":"Deise Trevizan Pelissaro, Aédnor Antonio Casado Zago, Suéllen Tonatto Ferrazzo, Giovani Jordi Bruschi, Francisco Dalla Rosa","doi":"10.1080/14680629.2023.2276421","DOIUrl":"https://doi.org/10.1080/14680629.2023.2276421","url":null,"abstract":"AbstractThe stabilization of recycled asphalt pavement (RAP) with alkali-activated cement (AAC) is a topic of growing interest for sustainable engineering, especially those containing alternative activators produced from waste. This study evaluated the effect of curing temperature on the stabilization of RAP with a metakaolin AAC and rice husk ash-derived activator for potential use in base and subbase layers in flexible pavement systems. Unconfined compressive strength (UCS), X-ray diffraction, and scanning electron microscopy tests were performed. Higher strength values were associated with higher temperatures and curing times. Curing oven time presented no influence over UCS and mineralogy. Blends cured at 20°C exhibited efflorescence formation and prolonged curing time at high temperatures negatively affected the mechanical performance. Curing temperature of 80°C up to 24 h promoted the formation and uniform distribution of cementing gels and a dense and compact structure, improving the compressive strength.KEYWORDS: Recycled asphalt pavementalkali-activated cementalternative alkaline activatorstrength developmentmineralogymicrostructure AcknowledgementsThe authors wish to explicit their appreciation to National Council for Scientific and Technological Development -CNPq for the support to the research group.Disclosure statementNo potential conflict of interest was reported by the author(s).Authors’ contributionsAll authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Aednor Antonio Casado Zago and Deise Trevizan Pelissaro. The first draft of the manuscript was written by Deise Trevizan Pelissaro and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. In addition, Francisco Dalla Rosa was responsible for the supervision of the research.Data availability statementSome or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.","PeriodicalId":21475,"journal":{"name":"Road Materials and Pavement Design","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135974272","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-02DOI: 10.1080/14680629.2023.2276412
Rabea AL-Jarazi, Ali Rahman, Changfa Ai, Zaid Al-Huda, Hamza Ariouat
AbstractThe interlayer bonding condition in asphalt pavement significantly affects pavement performance. This study employed machine learning techniques to predict interlayer shear strength (ISS). Feed-forward artificial neural networks (ANN) and random forest (RF) models were developed and compared with traditional multiple linear regression (MLR). Utilizing 156 datasets, divided into 70% training and 30% testing, model performance was assessed using R-squared, mean squared error (MSE), root mean squared error (RMSE), and mean absolute error (MAE). SHapley Additive exPlanations (SHAP) was utilized for model interpretation. The results indicated that the ANN and RF models outperformed MLR, explaining over 95% of experimental data. RF exhibited superior performance with lowest MSE, RMSE, and MAE (0.0029, 0.0538, and 0.0376 MPa). SHAP analysis highlighted the significance of temperature, normal stress, shear deformation rate, and curing time as influential variables in ISS prediction. Elevated temperature adversely influenced ISS, while normal stress, shear deformation rate, and curing time positively contributed to ISS.KEYWORDS: Asphalt pavementinterlayer shear strengthmachine learningANNrandom forest (RF)SHAP AcknowledgmentsThis work was supported by the Fundamental Research Funds for the Central Universities, SWJTU [grant number 2682022CX002], National Natural Science Foundation of China [grant number 52278462], and Sichuan Youth Science and Technology Innovation Research Team (grant number 2021JDTD0023).Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThis work was supported by the Fundamental Research Funds for the Central Universities, SWJTU [grant number 2682022CX002], National Natural Science Foundation of China [grant number 52278462], and Sichuan Youth Science and Technology Innovation Research Team (grant number 2021JDTD0023).
{"title":"Development of prediction models for interlayer shear strength in asphalt pavement using machine learning and SHAP techniques","authors":"Rabea AL-Jarazi, Ali Rahman, Changfa Ai, Zaid Al-Huda, Hamza Ariouat","doi":"10.1080/14680629.2023.2276412","DOIUrl":"https://doi.org/10.1080/14680629.2023.2276412","url":null,"abstract":"AbstractThe interlayer bonding condition in asphalt pavement significantly affects pavement performance. This study employed machine learning techniques to predict interlayer shear strength (ISS). Feed-forward artificial neural networks (ANN) and random forest (RF) models were developed and compared with traditional multiple linear regression (MLR). Utilizing 156 datasets, divided into 70% training and 30% testing, model performance was assessed using R-squared, mean squared error (MSE), root mean squared error (RMSE), and mean absolute error (MAE). SHapley Additive exPlanations (SHAP) was utilized for model interpretation. The results indicated that the ANN and RF models outperformed MLR, explaining over 95% of experimental data. RF exhibited superior performance with lowest MSE, RMSE, and MAE (0.0029, 0.0538, and 0.0376 MPa). SHAP analysis highlighted the significance of temperature, normal stress, shear deformation rate, and curing time as influential variables in ISS prediction. Elevated temperature adversely influenced ISS, while normal stress, shear deformation rate, and curing time positively contributed to ISS.KEYWORDS: Asphalt pavementinterlayer shear strengthmachine learningANNrandom forest (RF)SHAP AcknowledgmentsThis work was supported by the Fundamental Research Funds for the Central Universities, SWJTU [grant number 2682022CX002], National Natural Science Foundation of China [grant number 52278462], and Sichuan Youth Science and Technology Innovation Research Team (grant number 2021JDTD0023).Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThis work was supported by the Fundamental Research Funds for the Central Universities, SWJTU [grant number 2682022CX002], National Natural Science Foundation of China [grant number 52278462], and Sichuan Youth Science and Technology Innovation Research Team (grant number 2021JDTD0023).","PeriodicalId":21475,"journal":{"name":"Road Materials and Pavement Design","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135974884","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
AbstractThis paper proposes a new concept of single-direction water-blocking for waterproof membranes in silt subgrades to meet the demands of inhibiting capillary rising and allowing subgrade water downward through the waterproof membrane. Furthermore, a new approach to determine the total pore area in water-repellent soil is proposed using a contact angle test. The relationship between the water repellence of the waterproof membrane and the consumption of Sodium Methyl Silicate per unit Area (SMSA) is obtained for different levels of compactness. When SMSA consumption is less than 4 g/m2, the water repellence of the waterproof membrane is extremely poor, whereas, in the range of 4–10 g/m2, its water repellence is greatly enhanced. When the SMSA consumption is more than 10 g/m2, the water repellence becomes stable. The total pore area of the waterproof membrane decreases when the SMSA consumption is increased.KEYWORDS: Silt subgradewaterproof membranefluid potential equationwater repellencesingle-direction water-blocking Disclosure statementNo potential conflict of interest was reported by the author(s).
{"title":"Study on single-direction water-blocking of waterproof membrane in silt subgrade","authors":"Wenliang Wan, Chunpeng Han, Botong Chen, Wei Jin, Qingjie Dong, Yushu Wang","doi":"10.1080/14680629.2023.2278145","DOIUrl":"https://doi.org/10.1080/14680629.2023.2278145","url":null,"abstract":"AbstractThis paper proposes a new concept of single-direction water-blocking for waterproof membranes in silt subgrades to meet the demands of inhibiting capillary rising and allowing subgrade water downward through the waterproof membrane. Furthermore, a new approach to determine the total pore area in water-repellent soil is proposed using a contact angle test. The relationship between the water repellence of the waterproof membrane and the consumption of Sodium Methyl Silicate per unit Area (SMSA) is obtained for different levels of compactness. When SMSA consumption is less than 4 g/m2, the water repellence of the waterproof membrane is extremely poor, whereas, in the range of 4–10 g/m2, its water repellence is greatly enhanced. When the SMSA consumption is more than 10 g/m2, the water repellence becomes stable. The total pore area of the waterproof membrane decreases when the SMSA consumption is increased.KEYWORDS: Silt subgradewaterproof membranefluid potential equationwater repellencesingle-direction water-blocking Disclosure statementNo potential conflict of interest was reported by the author(s).","PeriodicalId":21475,"journal":{"name":"Road Materials and Pavement Design","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135974000","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-01DOI: 10.1080/14680629.2023.2276422
Parisa Setayesh Valipour, Amir Golroo, Afarin Kheirati, Mohammadsadegh Fahmani, Mohammad Javad Amani
AbstractRoads are one of the most critical infrastructures, which should be maintained at a high quality of service. For this purpose, road pavement should be assessed cost-effectively. In the past, image processing methods were used to analyze pavement conditions. In recent years, machine learning methods have been employed, while now deep learning methods are applied. Deep learning has outperformed other methods regarding the accuracy and speed of pavement distress evaluation. In this research, a deep learning algorithm called YOLOv5 is deployed to detect pavement block cracking and estimate its severity using images taken from the right of way via a road surface profiler. Two models are successfully trained and tested, one to detect block cracking and the other to predict its severity with a sufficient level of accuracy of 84.5% and 76.6%, respectively. It is concluded that the model not only can detect block cracking but also predict its severity.KEYWORDS: Pavement management systemdeep learningblock crackingobject detectionYOLOannotation Disclosure statementNo potential conflict of interest was reported by the author(s).
{"title":"Automatic pavement distress severity detection using deep learning","authors":"Parisa Setayesh Valipour, Amir Golroo, Afarin Kheirati, Mohammadsadegh Fahmani, Mohammad Javad Amani","doi":"10.1080/14680629.2023.2276422","DOIUrl":"https://doi.org/10.1080/14680629.2023.2276422","url":null,"abstract":"AbstractRoads are one of the most critical infrastructures, which should be maintained at a high quality of service. For this purpose, road pavement should be assessed cost-effectively. In the past, image processing methods were used to analyze pavement conditions. In recent years, machine learning methods have been employed, while now deep learning methods are applied. Deep learning has outperformed other methods regarding the accuracy and speed of pavement distress evaluation. In this research, a deep learning algorithm called YOLOv5 is deployed to detect pavement block cracking and estimate its severity using images taken from the right of way via a road surface profiler. Two models are successfully trained and tested, one to detect block cracking and the other to predict its severity with a sufficient level of accuracy of 84.5% and 76.6%, respectively. It is concluded that the model not only can detect block cracking but also predict its severity.KEYWORDS: Pavement management systemdeep learningblock crackingobject detectionYOLOannotation Disclosure statementNo potential conflict of interest was reported by the author(s).","PeriodicalId":21475,"journal":{"name":"Road Materials and Pavement Design","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135371826","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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