Article(id=1212410689059201845, tenantId=1146029695717560320, journalId=1146031591421210625, issueId=1212410683682099946, articleNumber=null, orderNo=23, doi=10.3981/j.issn.1000-7857.2023.07.01076, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=research-article, receivedDate=1690387200000, receivedDateStr=2023-07-27, revisedDate=1737302400000, revisedDateStr=2025-01-20, acceptedDate=null, acceptedDateStr=null, onlineDate=1766990833773, onlineDateStr=2025-12-29, pubDate=1762963200000, pubDateStr=2025-11-13, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1766678400000, onlineIssueDateStr=2025-12-26, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1766990833773, creator=13701087609, updateTime=1774080253921, updator=sys-migrate, issue=Issue{id=1212410683682099946, tenantId=1146029695717560320, journalId=1146031591421210625, year='2025', volume='43', issue='21', pageStart='1', pageEnd='136', issueExtLink='null', onlineDate='null', pubDate='1762963200000', pubDateStr='2025-11-13', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1766990832490, creator='13701087609', updateTime=1774330578192, updator='13041195026', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1243195808502366441, tenantId=1146029695717560320, journalId=1146031591421210625, issueId=1212410683682099946, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1243195808502366442, tenantId=1146029695717560320, journalId=1146031591421210625, issueId=1212410683682099946, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=118, endPage=126, ext={EN=ArticleExt(id=1212410689822565182, articleId=1212410689059201845, tenantId=1146029695717560320, journalId=1146031591421210625, language=EN, title=Research progress on fatigue performance of machine−made sand concrete, columnId=1150494644690366681, journalTitle=Science & Technology Review, columnName=Papers, runingTitle=null, highlight=null, articleAbstract=

In the last decade, the fatigue damage of machine-made sand concrete caused by cyclic loading has gradually started to attract attention, but the test results are diverse and discrete due to the influence of test equipment, test conditions, and environment, etc. No uniform standard has been reached. To further analyze the fatigue performance of machine-made sand concrete and improve the accuracy of fatigue life prediction, this paper starts from the influencing factors of its mechanical properties—such as the content of stone powder, stress level, and machine-made sand replacement ratio, summarizes the underlying mechanisms and patterns, and analyzes the relationship between the static properties and fatigue life of concrete with the Aas–Jakobsen equation. An empirical fatigue life prediction formula is proposed, which considers the transformation relationships among the compressive, flexural, and tensile strengths of machine-made sand concrete. In addition, for the first time, this study conducted a microscopic analysis of the composition and microstructure of the interfacial transition zone (ITZ) and hydration products in concrete at different machine-made sand replacement rates, using scanning electron microscopy (SEM) and microhardness. Afterward, fatigue tests were carried out on concrete specimens at different replacement rates (0, 30 %, 70 %, and 100 %) of machine-made sand and the optimal replacement rate of machine-made sand for C30 concrete mix ratio was around 50%. Based on the experimental data, a fatigue life prediction model incorporating the machine-made sand replacement rates was developed. The proposed model avoids the need for extensive additional experiments and demonstrates greater applicability in engineering scenarios with significant variations in material composition or limited on-site experiment conditions.

, authors=null, authorsList=Qingling MENG, Genping OUYANG, Xiaofeng JING, Hailiang WANG, Xiaoyu GUO, authorCompany=null, correspAuthors=Hailiang WANG, authorNote=null, correspAuthorsNote=null, copyrightStatement=All rights reserved. Unauthorized reproduction is prohibited., copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1212410692410450829, articleId=1212410689059201845, tenantId=1146029695717560320, journalId=1146031591421210625, language=CN, title=机制砂混凝土疲劳性能研究进展, columnId=1146540929516700224, journalTitle=科技导报, columnName=研究论文, runingTitle=null, highlight=null, articleAbstract=

近10年来由循环荷载而引起的机制砂混凝土疲劳破坏问题已经逐渐开始引起人们的重视,但受试验设备、试验条件与环境等因素的影响,致使试验结果呈现多样性和离散性,未达成统一标准。为进一步分析机制砂混凝土的疲劳性能,提高疲劳寿命预测准确度,从机制砂混凝土力学性能影响因素(如石粉掺量、应力水平、机制砂替代率等)出发,总结其影响机制与规律,同时引入Aas-Jakobsen公式分析归纳了混凝土静力性能与疲劳寿命之间的联系,从而给出了考虑机制砂混凝土抗压、抗弯和抗拉强度间转化关系的疲劳寿命经验性预测公式。此外,首次采用扫描电镜与显微硬度对不同机制砂替代率下混凝土界面过渡区及水化物的组成结构进行微观分析,并进行了不同机制砂替代率(0、30%、70%、100%)下混凝土试件疲劳试验,证明了C30混凝土配合比下机制砂最佳替代率为50%左右,利用试验数据建立起考虑机制砂替代率的混凝土疲劳寿命预测模型,所构建的模型避免了重复开展大量试验的成本,在材料组分差异较大或现场试验条件受限的工程环境中具有更强的可推广性。

, authors=

孟庆领,副教授,研究方向为材料力学性能模拟与测试,电子信箱:

, authorsList=孟庆领, 欧阳根平, 敬骁锋, 王海良, 郭晓宇, authorCompany=null, correspAuthors=王海良, authorNote=null, correspAuthorsNote=
王海良(通信作者),教授,研究方向为桥梁结构施工过程控制,电子信箱:
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试验
参数
混凝土
强度
等级
试验
类型
混凝土
试件
类型
试件
尺寸/mm
加载
形式
加载
波形
机制砂
掺量/%
最大
应力
水平
应力
加载
频率/
Hz
石粉
含量/%
预应力
施工
工艺
结论
何盛东等[16] C50 弯曲疲劳试验 预应力
混凝土梁
750×200×
400
三分点加载 正弦波加载 50,100 3 4.3 先张法、
后张法
在影响因素某一变化范围内,机制砂混凝土疲劳性能优于普通混凝土疲劳性能
李倩倩等[17] C50 弯曲疲劳试验 预应力
混凝土梁
750×200×
400
两分点加载 正弦波加载 50,100 3 4.3 先张法、
后张法
李北星等[14] C60 弯曲疲劳试验 素混凝土 100×100×
400
三分点加载 正弦波加载 100,0 0.55,0.60,0.65,0.70 0.1 10 7.0
赵书平等[15] C60 弯曲疲劳试验 素混凝土 100×100×
400
三分点加载 正弦波加载 70 0.60,0.65,0.70 10 7.0
孙哲理等[13] C40 弯曲疲劳试验 碾压
混凝土
100×100×
400
三分点加载 正弦波加载 100 0.70,0.75,0.80 0.1 10 0,5,10,15,20
), ArticleFig(id=1242145917424443521, tenantId=1146029695717560320, journalId=1146031591421210625, articleId=1212410689059201845, language=CN, label=表1, caption=

机制砂混凝土疲劳性能研究成果对比

, figureFileSmall=null, figureFileBig=null, tableContent=
试验
参数
混凝土
强度
等级
试验
类型
混凝土
试件
类型
试件
尺寸/mm
加载
形式
加载
波形
机制砂
掺量/%
最大
应力
水平
应力
加载
频率/
Hz
石粉
含量/%
预应力
施工
工艺
结论
何盛东等[16] C50 弯曲疲劳试验 预应力
混凝土梁
750×200×
400
三分点加载 正弦波加载 50,100 3 4.3 先张法、
后张法
在影响因素某一变化范围内,机制砂混凝土疲劳性能优于普通混凝土疲劳性能
李倩倩等[17] C50 弯曲疲劳试验 预应力
混凝土梁
750×200×
400
两分点加载 正弦波加载 50,100 3 4.3 先张法、
后张法
李北星等[14] C60 弯曲疲劳试验 素混凝土 100×100×
400
三分点加载 正弦波加载 100,0 0.55,0.60,0.65,0.70 0.1 10 7.0
赵书平等[15] C60 弯曲疲劳试验 素混凝土 100×100×
400
三分点加载 正弦波加载 70 0.60,0.65,0.70 10 7.0
孙哲理等[13] C40 弯曲疲劳试验 碾压
混凝土
100×100×
400
三分点加载 正弦波加载 100 0.70,0.75,0.80 0.1 10 0,5,10,15,20
), ArticleFig(id=1242145917499940994, tenantId=1146029695717560320, journalId=1146031591421210625, articleId=1212410689059201845, language=EN, label=null, caption=null, figureFileSmall=null, figureFileBig=null, tableContent=
混凝土强度 混凝土材料用量/(kg·m−3
水泥 机制砂 : 河砂 粗骨料 粉煤灰 减水剂
C30 293 0/825.0 1093 170 69 4.1
C30 293 247.5/577.5 1093 170 69 4.1
C30 293 577.5/247.5 1093 170 69 4.1
C30 293 825.0/0 1093 170 69 4.1
), ArticleFig(id=1242145917588021379, tenantId=1146029695717560320, journalId=1146031591421210625, articleId=1212410689059201845, language=CN, label=表2, caption=

机制砂混凝土配合比

, figureFileSmall=null, figureFileBig=null, tableContent=
混凝土强度 混凝土材料用量/(kg·m−3
水泥 机制砂 : 河砂 粗骨料 粉煤灰 减水剂
C30 293 0/825.0 1093 170 69 4.1
C30 293 247.5/577.5 1093 170 69 4.1
C30 293 577.5/247.5 1093 170 69 4.1
C30 293 825.0/0 1093 170 69 4.1
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机制砂混凝土疲劳性能研究进展
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孟庆领 1, 2, 3 , 欧阳根平 1 , 敬骁锋 2 , 王海良 2, 3, * , 郭晓宇 2, 3
科技导报 | 研究论文 2025,43(21): 118-126
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科技导报 |研究论文 2025 , 43 (21) : 118 -126
机制砂混凝土疲劳性能研究进展
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孟庆领1, 2, 3 , 欧阳根平1, 敬骁锋2, 王海良2, 3, * , 郭晓宇2, 3
作者信息
  • 1江西赣粤高速公路股份有限公司,南昌 330025
  • 2天津城建大学土木工程学院,天津 300384
  • 3天津市土木建筑结构防护与加固重点实验室,天津 300384
通讯作者:
王海良(通信作者),教授,研究方向为桥梁结构施工过程控制,电子信箱:
Research progress on fatigue performance of machine−made sand concrete
Qingling MENG1, 2, 3 , Genping OUYANG1, Xiaofeng JING2, Hailiang WANG2, 3, * , Xiaoyu GUO2, 3
Affiliations
  • 1Jiangxi Ganyue Expressway Co., Ltd., Nanchang 330025, China
  • 2School of Civil Engineering, Tianjin Chengjian University, Tianjin 300384, China
  • 3Key Laboratory of Civil Building Structure Protection and Reinforcement of Tianjin, Tianjin 300384, China
出版时间: 2025-11-13 doi: 10.3981/j.issn.1000-7857.2023.07.01076
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近10年来由循环荷载而引起的机制砂混凝土疲劳破坏问题已经逐渐开始引起人们的重视,但受试验设备、试验条件与环境等因素的影响,致使试验结果呈现多样性和离散性,未达成统一标准。为进一步分析机制砂混凝土的疲劳性能,提高疲劳寿命预测准确度,从机制砂混凝土力学性能影响因素(如石粉掺量、应力水平、机制砂替代率等)出发,总结其影响机制与规律,同时引入Aas-Jakobsen公式分析归纳了混凝土静力性能与疲劳寿命之间的联系,从而给出了考虑机制砂混凝土抗压、抗弯和抗拉强度间转化关系的疲劳寿命经验性预测公式。此外,首次采用扫描电镜与显微硬度对不同机制砂替代率下混凝土界面过渡区及水化物的组成结构进行微观分析,并进行了不同机制砂替代率(0、30%、70%、100%)下混凝土试件疲劳试验,证明了C30混凝土配合比下机制砂最佳替代率为50%左右,利用试验数据建立起考虑机制砂替代率的混凝土疲劳寿命预测模型,所构建的模型避免了重复开展大量试验的成本,在材料组分差异较大或现场试验条件受限的工程环境中具有更强的可推广性。

混凝土  /  静力性能  /  机制砂替代率  /  疲劳寿命预测  /  Weibull分布

In the last decade, the fatigue damage of machine-made sand concrete caused by cyclic loading has gradually started to attract attention, but the test results are diverse and discrete due to the influence of test equipment, test conditions, and environment, etc. No uniform standard has been reached. To further analyze the fatigue performance of machine-made sand concrete and improve the accuracy of fatigue life prediction, this paper starts from the influencing factors of its mechanical properties—such as the content of stone powder, stress level, and machine-made sand replacement ratio, summarizes the underlying mechanisms and patterns, and analyzes the relationship between the static properties and fatigue life of concrete with the Aas–Jakobsen equation. An empirical fatigue life prediction formula is proposed, which considers the transformation relationships among the compressive, flexural, and tensile strengths of machine-made sand concrete. In addition, for the first time, this study conducted a microscopic analysis of the composition and microstructure of the interfacial transition zone (ITZ) and hydration products in concrete at different machine-made sand replacement rates, using scanning electron microscopy (SEM) and microhardness. Afterward, fatigue tests were carried out on concrete specimens at different replacement rates (0, 30 %, 70 %, and 100 %) of machine-made sand and the optimal replacement rate of machine-made sand for C30 concrete mix ratio was around 50%. Based on the experimental data, a fatigue life prediction model incorporating the machine-made sand replacement rates was developed. The proposed model avoids the need for extensive additional experiments and demonstrates greater applicability in engineering scenarios with significant variations in material composition or limited on-site experiment conditions.

concrete  /  static performance  /  the replacement rate of machine−made sand  /  fatigue life prediction  /  Weibull distribution
孟庆领, 欧阳根平, 敬骁锋, 王海良, 郭晓宇. 机制砂混凝土疲劳性能研究进展. 科技导报, 2025 , 43 (21) : 118 -126 . DOI: 10.3981/j.issn.1000-7857.2023.07.01076
Qingling MENG, Genping OUYANG, Xiaofeng JING, Hailiang WANG, Xiaoyu GUO. Research progress on fatigue performance of machine−made sand concrete[J]. Science & Technology Review, 2025 , 43 (21) : 118 -126 . DOI: 10.3981/j.issn.1000-7857.2023.07.01076
机制砂是将机械破碎、筛分出粒径小于4.75 mm的不包括软质岩、风化岩的岩石颗粒。具有来源丰富、性能优良以及制备工艺成熟等的优点,其作为细骨料替代河砂在工程建设领域的应用日渐常态化。在车辆、地震和风等循环荷载长期作用下,机制砂混凝土在服役周期内产生的疲劳开裂问题日益突出,而西部地区复杂多变的环境(高温、严寒、极干燥以及高湿度等)更加剧了这种损伤劣化,并对机制砂混凝土抗疲劳性能提出了更高的要求及挑战。现有普通混凝土疲劳研究体系已较为完备,与之相比,当前机制砂混凝土疲劳研究较少,且主要关注点在现象学分析下不同因素对机制砂混凝土性能的影响上,虽取得了一定的成果,但尚未有系统性分析与总结。本文基于机制砂混凝土力学性能影响因素,系统梳理了相关研究成果,总结其影响机制与规律,并在此基础上补充进行了不同机制砂替代率下的混凝土弯曲疲劳试验,为后续机制砂混凝土疲劳性能研究提供了思路与参考。
本文创新点包括:(1) 讨论了给定应力下机制砂混凝土静力性能与疲劳性能的关系,利用多达345组机制砂混凝土静力性能相关数据,给出了考虑机制砂混凝土抗压、抗弯和抗拉强度间转化关系的疲劳寿命经验性预测公式,并首次采用扫描电镜(SEM)与显微硬度(MH)对不同机制砂替代率下混凝土界面过渡区及水化物的组成与结构进行微观分析,发现随着机制砂替代率超过70%后,水泥砂浆内部有害孔隙增多,显微硬度下降是混凝土静力及疲劳性能下降的重要原因;(2) 在现有文献的基础上,利用多种函数拟合后发现40%~70%机制砂替代率下混凝土疲劳性能最佳,并补充了不同机制砂替代率下混凝土疲劳试验验证,通过定义折减系数K对Aas−Jakobsen提出的疲劳寿命预测方程进行改进,实现了在已知应力水平下,机制砂混凝土疲劳寿命预测,同时结合Weibull分布对不同机制砂替代率下混凝土疲劳极限强度折减系数进行了讨论。
机制砂由于其特殊的制备方法,与天然砂相比存在颗粒形状粗糙锐利、孔隙率大、比表面积大及石粉含量高等特点,导致机制砂混凝土与天然河砂混凝土在各项性能上存在一定差异。国外早在20世纪三四十年代就己经开始将机制砂混凝土投入使用,而中国直到20世纪60年代初才开始对机制砂混凝土展开研究,近10年机制砂混凝土的各项力学性能特别是疲劳性能已引起相关学者的关注。
国内外研究人员已对混凝土疲劳性能展开了大量的理论及试验研究,研究表明:混凝土疲劳与静力性能息息相关,一般而言,混凝土静态强度越大,其疲劳寿命也越高[14],可见混凝土静态强度的研究对疲劳寿命预测有一定的参考价值。
机制砂对混凝土静力性能的改善效果受机制砂特性如石粉含量[57]、机制砂粒形[8]与机制砂替代率[911]等条件的制约,从而表现出不同的静力性能特征。当前普遍认为,综合力学性能与工作性能考虑,C30、C40和C50机制砂混凝土的最佳石粉含量分别为15%、10%、5%;棱角状机制砂较针片状更有利于性能提升;而最佳替代率多集中在40%~70%。此外,母岩种类、泥粉含量及颗粒级配等亦会影响其静力性能,因此合理控制机制砂特性并选择高品质机制砂,是提升混凝土静力性能的关键[12]
目前国内外研究人员对机制砂混凝土的疲劳性能研究较少,且对机制砂混凝土疲劳性能影响因素与相关作用机理尚未有系统性的分析与总结,因此由不合理掺配引起的机制砂混凝土疲劳性能劣化问题逐渐成为亟待解决的难题。总结了当前影响机制砂混凝土疲劳性能因素,并在此基础上补充探讨了混凝土静力性能与机制砂替代率对机制砂混凝土疲劳性能的影响。
孙哲理[13]结合粉煤灰含量综合探讨了不同石粉掺量下机制砂碾压混凝土疲劳寿命,发现适量石粉能改善机制砂混凝土疲劳性能,且最佳石粉掺量阈值与粉煤灰含量密切相关,在达到阈值之前,机制砂含量与疲劳寿命呈正相关关系,超过阈值后2者呈现出负相关关系;李北星等[14]通过SEM发现机制砂混凝土的界面过渡区较为致密,认为石粉凭借填充作用改善了混凝土界面过渡区的结构;除石粉掺量外,部分学者发现应力水平也是影响机制砂混凝土疲劳性能的重要因素,且随着应力水平的提高,机制砂混凝土构件的弯曲疲劳寿命逐渐降低[1315]。何盛东[16]和李倩倩[17]认为预应力梁的施工工艺也能影响机制砂混凝土疲劳性能,并通过试验证明了先张法机制砂混凝土预应力梁的抗疲劳性能明显优于后张法机制砂混凝土预应力梁。综上所述可知,石粉掺量、应力水平与施工工艺对机制砂混凝土疲劳性能的影响是当前主要的3个研究方向,而混凝土静力性能及机制砂替代率的影响尚未得到充分考虑。
为直观表示混凝土静力性能对疲劳寿命的影响,引入Aas−Jakobsen[18]开展混凝土压缩疲劳试验时,建立混凝土疲劳寿命预测方程
$ S=\frac{\sigma_{\max}}{f_{\text{c}}}=1-(1-R)\beta \lg N $
式中,$ S $为应力水平,$ \,{f}_{{\mathrm{c}}} $是混凝土立方体抗压强度,$ {\sigma }_{\max} $是上限应力,R是应力比,$ \,\beta $是材料系数,代表混凝土材料抗疲劳性能的优劣,一般为0.069。
为验证该公式的准确性,统计了多篇混凝土抗压疲劳性能相关文献(上限应力在20~40 MPa范围内),利用指数函数成功拟合出混凝土静力性能与疲劳寿命的关系曲线,并与Aas−Jakobsen公式计算出的数据拟合曲线进行了对比,拟合后效果良好,可见该公式能在一定程度上评估混凝土疲劳寿命,其中材料系数$ \,\beta $ 取0.069,应力比R取0.1,最大应力取各应力区间的中间值[1929],如图1所示。可以看出,如果上限应力保持不变,混凝土抗压强度越高,其疲劳性能越强,且此优势会伴随上限应力的提高而增强。值得注意的是,随着混凝土抗压强度的提高,Aas−Jakobsen公式计算出的疲劳寿命曲线比实际数据拟合出的曲线增长幅度更大,造成这种现象的原因可能因为混凝土是准脆性材料,随着材料强度的增加,会表现出更强的脆性特征,从而造成实际统计的疲劳寿命数据偏低。
根据何盛东等[3031]和徐彦帆等[32]针对机制砂与砂混凝土抗压、抗拉及抗弯性能的对比研究结果,在相同配合比条件下,机制砂混凝土的静力性能指标显著优于天然砂混凝土。上述研究结论与当前学术界的主流观点相一致,即机制砂在一定程度上能够有效提升混凝土的力学性能[3335]。为进一步探讨这种性能提升对混凝土疲劳性能的潜在影响,可依据图1中“混凝土抗压强度越高,其疲劳性能越强”的规律,推测机制砂在改善混凝土静力性能的同时也显著增强了其疲劳寿命,而Aas−Jakobsen 公式在预测机制砂混凝土疲劳寿命方面具有较高的适用性。然而,该推论尚需结合后续的大量试验数据进行进一步验证,以确保其科学性与可靠性。
由前文可知选用Aas−Jakobsen提出的疲劳寿命预测方程可以较好评估混凝土的疲劳性能,然而上述研究主要适用于已知材料系数$ \beta $的普通混凝土,由于当前对机制砂混凝土疲劳研究较少,因此暂不明确机制砂用量与$ \beta $值的关系。结合1.1节可知,即使机制砂对混凝土的具体改善效果随石粉含量、施工工艺、应力水平等的不同而改变,大多研究人员仍发现机制砂替代率达到40%~70%时,混凝土静力性能最佳,同时考虑1.2.2节混凝土静力性能与疲劳寿命的正相关关系,可假设机制砂替代率达到40%~70%时,混凝土疲劳寿命最大。为验证机制砂替代率对混凝土疲劳性能产生影响,根据李北星[14]和赵书平[15]文献中疲劳数据计算出了不同机制砂替代率下混凝土材料系数$ \beta $值,并利用材料系数$ \beta $评估了不同替代率下机制砂混凝土的疲劳性能,如图2所示。通过选取Holliday、LogNormal、二次多项式以及分段线性等多种相关系数较高的拟合方式拟合后发现,机制砂最佳替代率在40%~70%。
与机制砂有关的疲劳研究始于20世纪初,随后研究人员逐渐对预应力机制砂混凝土梁或普通机制砂混凝土试件的疲劳性能退化问题产生兴趣,研究方式大多是在具体工作环境下针对某一特定的工程结构提出合适的研究方法[1317, 36]。何盛东[16]和李倩倩[17]通过对比机制砂和河砂混凝土梁在受力过程中以及疲劳试验后裂缝和挠度的变化规律,首次发现机制砂混凝土梁抗疲劳性能更佳;随后,李北星等[14]在疲劳试验中发现机制砂混凝土棱柱体弯曲疲劳极限强度折减系数为53%,疲劳寿命符合两参数Weibull分布,并因此获得了等幅载荷下机制砂混凝土弯曲疲劳寿命的P−S−N方程,最后结合HV与SEM从微观角度对机制砂混凝土疲劳性能优于河砂混凝土进行了解释;赵书平[15]将机制砂与河砂混凝土以2.3∶1比例制成混合砂,并开展了弯曲疲劳试验,发现混合砂混凝土抗弯强度折减系数为58%;孙哲理[13]对机制砂碾压混凝土的静力性能、工作性能和疲劳性能进行了充分研究,试验发现,应力水平与石粉含量都对机制砂碾压混凝土疲劳性能有显著影响。综上可知,当前研究主要聚焦于机制砂混凝土梁的弯曲疲劳性能,并采用Palmgren−Miner线性累积损伤理论进行现象学研究,从而达到预测机制砂混凝土疲劳寿命的目的,具体研究成果如表1所示。
鉴于目前暂无统一的公式描述机制砂混凝土抗压、抗弯和抗拉性能间的转化关系,基于《普通混凝土力学性能试验方法标准》(GB/T 50081—2002)[37],统计了国内外研究中机制砂混凝土抗压、抗弯与抗拉试验数据共345组,欲建立起机制砂混凝土抗压、抗弯和抗拉强度间的转化关系,其中抗压强度处于C60以下的非标准机制砂混凝土试件的实验结果数据已通过换算系数将其换算成标准值(非标准尺寸为100 mm × 100 mm × 100 mm立方体抗压试件与100 mm × 100 mm × 400 mm棱柱体抗折试件的换算系数分别取0.95和 0.85)。由于当前大多数研究人员认为应该用幂指数函数评价普通混凝土抗压、抗弯和抗拉强度之间的关系,具体公式如下
$ f = bf_{\mathrm{c}}^{\;a} $
式中,f是混凝土抗弯或抗拉强度;fc是混凝土抗压强度;ab是相关系数,对普通混凝土,ab主要与材料性质有关,a值与b值通常在0.5~0.67与0.33~0.94[3840],因此,同样使用幂指数函数对机制砂混凝土抗压、抗弯(或抗折)和抗拉强度进行拟合并得出经验性公式,拟合结果如式(3)和式(4)分子部分表达式。拟合过程中发现:由于受石粉含量、机制砂替代率、颗粒级配和母岩种类等因素以及混凝土离散性影响,拟合后整体相关系数不高,而与抗折强度相比,机制砂混凝土的劈裂抗拉强度与抗压强度之间的相关系数明显更高,拟合效果更好,这可能是由于统计过程中抗压与劈裂抗拉试验大多采用150 mm尺寸下标准立方体试件,极大程度上减少了因混凝土试件的尺寸不同而导致试验结果出现差异。此外相同抗压强度条件下,机制砂混凝土抗折强度与劈裂抗拉强度往往高于普通混凝土,伴随着抗压强度增加,这种趋势愈发明显。
最后,结合1.2.2节Aas−Jakobsen提出的混凝土疲劳寿命预测式(1),将式(1)中机制砂混凝土抗压强度转化成抗弯强度$ {f}_{{\mathrm{r}}} $和抗拉强度$ {f}_{{\mathrm{t}}} $,从而计算出给定最大应力下的机制砂混凝土弯曲和抗拉疲劳寿命,见式(3)与式(4)。由于相关数据缺乏,式中机制砂混凝土材料系数$ \,\beta $有待进一步研究。
$ S=\frac{\sigma_{\max}}{0.368{f}\;_{{\mathrm{r}}}^{0.722}}=1-(1-R)\beta \lg N $
$ S=\frac{\sigma_{\max}}{0.217{f}\;_{\text{t}}^{0.739}}=1-(1-R)\beta \lg N $
考虑到目前暂无合适的$ \beta $值描述不同机制砂替代率下混凝土材料特性,并为进一步确定机制砂替代率对混凝土疲劳性能的影响,在相同条件下进行了不同机制砂替代率的混凝土疲劳试验。
试验根据《普通混凝土配合比设计规程》(JGJ 55–2011)对基准混凝土的配合比进行设计,试验配合比如表2所示,其中机制砂与河砂级配曲线如图3所示。机制砂与河砂级配区均属于II类砂,其中机制砂中大于0.15 mm与小于2.36 mm的颗粒分别占比为15.7%与24.3%,远高于河砂的6.8%与14.8%;而0.3~1.18 mm颗粒河砂占比为35.4%,低于机制砂的53.8%,可见机制砂颗粒呈现典型的“两头大”“中间小”的级配特征,而通过机制砂对河砂进行部分置换可以有效改善“级配不均”的情况,从而使级配得到优化。
试验所用试块尺寸为100 mm×100 mm×400 mm的混凝土棱柱体,具体加载边界条件如图4所示。所有棱柱体分为A、B、C、D 4组,相应的机制砂替代率分别为0、30%、70%、100%。疲劳实验设备是PWS−300电液伺服动静万能试验机。采用三分点(50+3×100+50)弯曲恒幅疲劳载荷,波形为正弦波,负载频率为 l0 Hz,疲劳试验循环应力比为0.1。
通过Aas−Jakobsen提出的疲劳寿命预测方程,可计算出不同机制砂替代率(0、30%、70%、100%)下混凝土材料系数$ \beta $值(图5)。可以发现,代表不同应力水平的3条曲线走向趋势基本相同,随着机制砂替代率的增加,$ \beta $值均呈现先减小后增大的趋势,而机制砂替代率为0时,材料系数$ \beta $值最大,可见含有机制砂的混凝土疲劳性能明显优于传统河砂混凝土,且存在一个使得混凝土疲劳寿命最高的最优机制砂替代率。相较于单条曲线的变化,同一机制砂替代率下,不同曲线间$ \beta $值差距明显更大,说明与机制砂替代率相比,应力水平对机制砂混凝土疲劳性能影响更大,因此对不同的应力水平下$ \beta $的变化情况宜分开进行讨论。通过利用Holiday、二次多项式、三次多项式对不同机制砂替代率下混凝土材料系数$ \beta $进行拟合,发现机制砂替代率为40%~70%,材料系数$ \beta $值达到最小,此时机制砂对混凝土抗疲劳性能的提升最大,结论与1.2.3节一致。由于二次多项式与Holiday拟合后相关系数处于0.6~0.8,相关性不高,因此建议采用三次多项式计算不同机制砂替代率下混凝土的材料系数$ \beta $,并代入式(3)可得:
$ \left\{ \begin{aligned}& N = {10^{\tfrac{{1 - S}}{{(1 - R)( - 1.42 \times {{10}^{ - 8}}{X^3}+3.29 \times {{10}^{ - 6}}{X^2}- 2.08 \times {{10}^{ - 4}}X+0.075)}}}},{\text{ }}S = 0.65 \\& N = {10^{\tfrac{{1 - S}}{{(1 - R)( - 1.73 \times {{10}^{ - 8}}{X^3}+3.54 \times {{10}^{ - 6}}{X^2}- 2.06 \times {{10}^{ - 4}}{\text{ }}X+0.063)}}}},{\text{ }}S = 0.75 \\& N = {10^{\tfrac{{1 - S}}{{(1 - R)( - 1.82 \times {{10}^{ - 8}}{X^3}+3.62 \times {{10}^{ - 6}}{X^2}- 2.11 \times {{10}^{ - 4}}{\text{ }}X+0.054)}}}},{\text{ }}S = 0.85 \\ \end{aligned} \right. $
式中, X代表机制砂替代率,利用式(5)可对不同机制砂替代率下混凝土疲劳寿命进行预测。
然而实际工程中,河砂混凝土疲劳寿命通常是变化的,而非一个定值,此时式(5)不再适用。为进一步拓展式(5)的实际运用范围,利用无量纲化处理定义一个与机制砂替代率相关的折减系数$ K={\beta /\beta }_{0} $,其中$ \beta $为不同替代率下机制砂混凝土材料系数,$ {\beta }_{0} $为普通河砂混凝土材料系数,将折减系数$ K $代入式(1),即可得考虑机制砂替代率的混凝土疲劳寿命表达式(8),其中折减系数与机制砂替代率的关系如图6所示。
$ S=\frac{\sigma_{\max}}{f_{\text{c}}}=1-(1-R)K{\beta }\lg N $
利用三次多项式拟合后,可得折减系数与机制砂替代率的关系表达式为:
$ \left\{\begin{aligned}K=&-1.89\times {10}^{-7}{X}^{3}+4.38\times {10}^{-5}{X}^{2}-\\&2.77\times {10}^{-3}X+1\text{,}S=0.65\\ K=&-2.76\times {10}^{-7}{X}^{3}+5.67\times {10}^{-5}{X}^{2}-\\&3.30\times {10}^{-3}\text{ }X+1\text{,}S=0.75\\ K=&-3.34\times {10}^{-7}{X}^{3}+6.65\times {10}^{-5}{X}^{2}-\\&3.88\times {10}^{-3}\text{ }X+1\text{,}S=0.85\end{aligned}\right. $
将式(7)代入(6)后,整理后即得:
$ \left\{ \begin{aligned}& N = {10^{\tfrac{{1 - S}}{{(1 - R)( - 1.89 \times {{10}^{ - 7}}{X^3}+4.38 \times {{10}^{ - 5}}{X^2} - 2.77 \times {{10}^{ - 3}}X+1)\beta }}}},{\text{ }}S = 0.65 \\& N = {10^{\tfrac{{1 - S}}{{(1 - R)( - 2.76 \times {{10}^{ - 7}}{X^3}+5.67 \times {{10}^{ - 5}}{X^2} - 3.30 \times {{10}^{ - 3}}{\text{ }}X+1)\beta }}}},{\text{ }}S = 0.75 \\& N = {10^{\tfrac{{1 - S}}{{(1 - R)( - 3.34 \times {{10}^{ - 7}}{X^3}+6.65 \times {{10}^{ - 5}}{X^2} - 3.88 \times {{10}^{ - 3}}{\text{ }}X+1)\beta }}}},{\text{ }}S = 0.85 \\ \end{aligned} \right. $
式中,X为机制砂替代率,$ \beta $为普通混凝土材料系数,R为应力比,S为应力水平。在实际应用中,对于已知河砂混凝土构件的疲劳寿命,可利用式(8)预测不同机制砂替代率下混凝土构件的疲劳寿命。
为验证上述模型的准确性,选用李北星等[14]混凝土抗弯疲劳试验数据,利用式(8)进行计算,计算结果如图7所示(其中S=0.7时,$ K $值取S=0.65与S=0.75计算结果的平均值)。
图7可知,混凝土疲劳寿命试验数据与计算数据差距不大,整体误差在15%范围之内,可见以普通河砂混凝土疲劳数据为基础,利用本研究模型,可较好地预测100%替代率下机制砂混凝土疲劳寿命。图8是利用本研究模型对不同机制砂替代率下的混凝土疲劳寿命预测进行模拟。进行二次多项式拟合后,发现机制砂替代率在50%左右混凝土疲劳性能最佳,可供实际工程应用参考。
为探究机制砂对混凝土疲劳性能的影响,对机制砂混凝土疲劳性能研究进行了综述,总结与展望如下。
(1) 通过大量试验数据探讨了混凝土静力性能对疲劳性能的影响,并统计345组数据建立起机制砂混凝土抗压、抗弯、抗拉强度间转化公式,通过与河砂混凝土进行对比,证明了机制砂对混凝土静力与疲劳性能的改善作用,最后结合Aas−Jakobsen提出的疲劳寿命预测方程,给出了考虑机制砂混凝土抗压、抗弯以及抗拉强度转化关系的疲劳寿命预测方程。
(2) 目前缺乏对机制砂混凝土疲劳性能影响因素的系统研究,从而导致实际工程应用中可能存在安全隐患并影响推广。在初步归纳机制砂混凝土疲劳性能影响因素的基础上,利用材料系数$ \beta $对比了多篇文献中不同替代率下机制砂混凝土的疲劳性能,发现与100%机制砂替代率下的混凝土相比,在40%~70%掺量范围内机制砂与河砂组成的混合砂混凝土疲劳寿命更高,并在试验基础上给予了论证,发现C30混凝土配合比下机制砂最佳替代率为50%左右。
(3) 为验证不同机制砂替代率对混凝土疲劳寿命的影响,定义了考虑机制砂替代率的折减系数K,并结合疲劳试验数据对Aas−Jakobsen提出的疲劳寿命预测公式进行了改进,同时进行了Weibull概率分布验证,发现当机制砂替代率为0、30%、70%与100%时,混凝土疲劳极限强度折减系数分别为0.578、0.600、0.593以及0.590,并实现不同应力比以及不同机制砂替代率下的混凝土疲劳寿命预测。
(4) 相较于普通河砂混凝土,机制砂替代率达到30%~100%时,石粉充分发挥了“填充”“成核”“化学”作用,大量针棒状的钙矾石与团簇状的C—S—H凝胶等水化物的填充致使界面过渡区更加密实,然而这种“增益”现象随着机制砂替代率达到70%以上后逐渐减弱,由于大量使用机制砂,致使机制砂棱角分明、形状不规则、级配不良的特性凸显出来,此时砂浆内部开始出现较多微裂缝与微孔隙,混凝土疲劳性能降低。
(1) 现有机制砂混凝土疲劳研究多停留在试验现象分析,忽视疲劳损伤机理和断裂发展过程。未来可结合断裂力学、损伤力学与能量耗散原理开展多学科交叉研究,或采用双尺度方法将细观分析与宏观行为结合,在深入分析疲劳破坏形态、损伤机理及强度刚度退化规律的基础上,建立演变方程或本构模型,更合理地预测机制砂混凝土疲劳寿命。
(2) 目前,环境因素对机制砂混凝土疲劳性能的研究仍空白,尤其是在西部大温差、极干燥和低气压等恶劣环境下的性能退化问题亟待解决。未来可结合极端环境特点探究机制砂混凝土疲劳性能退化机理,对促进机制砂混凝土在西部地区基础设施建设上的应用具有重大的理论价值和现实意义。
  • 国家自然科学基金项目(52108163)
  • 国家自然科学基金项目(52278268)
  • 国家自然科学基金项目(52278269)
  • 天津市科技特派员项目(21YDTPJC00710)
  • 天津市交通运输科技发展计划项目(2022−22)
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2025年第43卷第21期
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doi: 10.3981/j.issn.1000-7857.2023.07.01076
  • 接收时间:2023-07-27
  • 首发时间:2025-12-29
  • 出版时间:2025-11-13
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  • 收稿日期:2023-07-27
  • 修回日期:2025-01-20
基金
国家自然科学基金项目(52108163)
国家自然科学基金项目(52278268)
国家自然科学基金项目(52278269)
天津市科技特派员项目(21YDTPJC00710)
天津市交通运输科技发展计划项目(2022−22)
作者信息
    1江西赣粤高速公路股份有限公司,南昌 330025
    2天津城建大学土木工程学院,天津 300384
    3天津市土木建筑结构防护与加固重点实验室,天津 300384

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王海良(通信作者),教授,研究方向为桥梁结构施工过程控制,电子信箱:
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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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