Article(id=1243879844417745749, tenantId=1146029695717560320, journalId=1240685776644648972, issueId=1243879841024553767, articleNumber=null, orderNo=null, doi=10.3969/j.issn.1007-7294.2024.09.012, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1711382400000, receivedDateStr=2024-03-26, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1774493665078, onlineDateStr=2026-03-26, pubDate=1726761600000, pubDateStr=2024-09-20, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1774493665078, onlineIssueDateStr=2026-03-26, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1774493665078, creator=13701087609, updateTime=1774493665078, updator=13701087609, issue=Issue{id=1243879841024553767, tenantId=1146029695717560320, journalId=1240685776644648972, year='2024', volume='28', issue='9', pageStart='1297', pageEnd='1462', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1774493664270, creator=13701087609, updateTime=1774493987725, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1243881197806404366, tenantId=1146029695717560320, journalId=1240685776644648972, issueId=1243879841024553767, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1243881197806404367, tenantId=1146029695717560320, journalId=1240685776644648972, issueId=1243879841024553767, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=1420, endPage=1429, ext={EN=ArticleExt(id=1243879844740707168, articleId=1243879844417745749, tenantId=1146029695717560320, journalId=1240685776644648972, language=EN, title=Analysis and prediction of ultra-low cycle fatigue fracture of offshore steel based on cyclic void growth model, columnId=1242129251223274417, journalTitle=Journal of Ship Mechanics, columnName=Structural Mechanics, runingTitle=null, highlight=null, articleAbstract=

The cyclic void growth model (CVGM) based on microscopic fracture mechanism is an effective method to analyze and predict ultra-low cycle fatigue (ULCF) fracture. In this method, the void growth index and damage degradation parameters are important parameters to control the crack propagation process. Due to the influence of production technology, the void growth index and damage degradation parameters of different batches of steels are often unfixed, which leads to the insufficient accuracy of the ultra-low cycle fatigue fracture analysis. In order to solve this problem, smooth round bar, smooth notch round bar and notch samples were used to carry out experiments, the ultra-low cycle fatigue characteristics of steel were studied, and the cracking mechanism and damage evolution law of the samples were explored. Secondly, the VUSDFLD program based on the cyclic void growth model was written, and the finite element analysis was carried out based on the results of test to calibrate the void growth index and damage degradation parameters. Finally, the ultra-low cycle fatigue fracture of notched samples was studied, the crack initiation and crack propagation rates were analyzed, and the ultra-low cycle fatigue fracture life of the samples was predicted. The results show that the fracture process of ultra-low cycle fatigue matches well with the experimental results, which is suitable for the prediction of ultra-low cycle fatigue fracture life.

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基于微观断裂机理的循环孔洞扩张模型是一种进行超低周疲劳断裂分析及预测的有效方法。在该方法中,孔洞扩张指数与损伤退化参数是控制裂纹扩展进程的重要参数。受生产工艺的影响,不同批次钢材的孔洞扩张指数与损伤退化参数往往存在较大差异,使得对结构的超低周疲劳断裂分析存在准确性不足的问题。为解决上述问题,本文采用光滑圆棒、平滑槽口圆棒及缺口试样开展试验,进行钢材超低周疲劳特性研究,探索试样开裂机制和损伤演化规律;其次,编写基于循环孔洞扩张模型的VUSDFLD程序,结合圆棒试验结果进行有限元分析,校准孔洞扩张指数及损伤退化参数;最后,基于前述理论和程序,开展缺口试样超低周疲劳断裂研究,分析裂纹萌生及裂纹扩展速率,并就试样的超低周疲劳断裂寿命展开预测。结果表明,基于循环孔洞扩张模型的超低周疲劳断裂进程与试验结果比对良好,适用于超低周疲劳断裂寿命预测。

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通讯作者,E-mail:
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刘焕才(1998-),男,硕士

何文涛(1986-),男,副教授,通讯作者,E-mail:

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Extremely low cycle fatigue prediction of steel beam-to-column connection by using a micromechanics-based fracture model[J]. Int J Fatigue, 2013, 48: 90-100., articleTitle=Extremely low cycle fatigue prediction of steel beam-to-column connection by using a micromechanics-based fracture model, refAbstract=null), Reference(id=1243879863153701424, tenantId=1146029695717560320, journalId=1240685776644648972, articleId=1243879844417745749, doi=null, pmid=null, pmcid=null, year=2010, volume=null, issue=null, pageStart=null, pageEnd=null, url=null, language=null, rfNumber=[2], rfOrder=1, authorNames=廖芳芳, 王伟, journalName=中国科技论文在线, refType=null, unstructuredReference=廖芳芳,王伟. 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基于循环孔洞扩张模型的海工钢超低周疲劳断裂分析与预测
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刘焕才 1 , 刘亚平 1 , 杜君峰 1 , 王春光 2 , 王昌梓 1 , 何文涛 1
船舶力学 | 结构力学 2024,28(9): 1420-1429
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船舶力学 | 结构力学 2024, 28(9): 1420-1429
基于循环孔洞扩张模型的海工钢超低周疲劳断裂分析与预测
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刘焕才1, 刘亚平1, 杜君峰1, 王春光2, 王昌梓1, 何文涛1
作者信息
  • 1.中国海洋大学 工程学院,山东 青岛 266000
  • 2.山东理工大学 建筑工程学院,山东 淄博 255000
  • 刘焕才(1998-),男,硕士

    何文涛(1986-),男,副教授,通讯作者,E-mail:

通讯作者:

通讯作者,E-mail:
Analysis and prediction of ultra-low cycle fatigue fracture of offshore steel based on cyclic void growth model
Huan-cai LIU1, Ya-ping LIU1, Jun-feng DU1, Chun-guang WANG2, Chang-zi WANG1, Wen-tao HE1
Affiliations
  • 1.College of Engineering, Ocean University of China, Qingdao 266000, China
  • 2.School of Civil Architecture and Engineering, Shandong University of Technology, Zibo 255000, China
出版时间: 2024-09-20 doi: 10.3969/j.issn.1007-7294.2024.09.012
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基于微观断裂机理的循环孔洞扩张模型是一种进行超低周疲劳断裂分析及预测的有效方法。在该方法中,孔洞扩张指数与损伤退化参数是控制裂纹扩展进程的重要参数。受生产工艺的影响,不同批次钢材的孔洞扩张指数与损伤退化参数往往存在较大差异,使得对结构的超低周疲劳断裂分析存在准确性不足的问题。为解决上述问题,本文采用光滑圆棒、平滑槽口圆棒及缺口试样开展试验,进行钢材超低周疲劳特性研究,探索试样开裂机制和损伤演化规律;其次,编写基于循环孔洞扩张模型的VUSDFLD程序,结合圆棒试验结果进行有限元分析,校准孔洞扩张指数及损伤退化参数;最后,基于前述理论和程序,开展缺口试样超低周疲劳断裂研究,分析裂纹萌生及裂纹扩展速率,并就试样的超低周疲劳断裂寿命展开预测。结果表明,基于循环孔洞扩张模型的超低周疲劳断裂进程与试验结果比对良好,适用于超低周疲劳断裂寿命预测。

超低周疲劳断裂  /  循环孔洞扩张模型  /  参数校准  /  裂纹萌生  /  裂纹扩展

The cyclic void growth model (CVGM) based on microscopic fracture mechanism is an effective method to analyze and predict ultra-low cycle fatigue (ULCF) fracture. In this method, the void growth index and damage degradation parameters are important parameters to control the crack propagation process. Due to the influence of production technology, the void growth index and damage degradation parameters of different batches of steels are often unfixed, which leads to the insufficient accuracy of the ultra-low cycle fatigue fracture analysis. In order to solve this problem, smooth round bar, smooth notch round bar and notch samples were used to carry out experiments, the ultra-low cycle fatigue characteristics of steel were studied, and the cracking mechanism and damage evolution law of the samples were explored. Secondly, the VUSDFLD program based on the cyclic void growth model was written, and the finite element analysis was carried out based on the results of test to calibrate the void growth index and damage degradation parameters. Finally, the ultra-low cycle fatigue fracture of notched samples was studied, the crack initiation and crack propagation rates were analyzed, and the ultra-low cycle fatigue fracture life of the samples was predicted. The results show that the fracture process of ultra-low cycle fatigue matches well with the experimental results, which is suitable for the prediction of ultra-low cycle fatigue fracture life.

ultra-low cycle fatigue fracture  /  CVGM  /  parameter calibration  /  crack initiation  /  crack propagation
刘焕才, 刘亚平, 杜君峰, 王春光, 王昌梓, 何文涛. 基于循环孔洞扩张模型的海工钢超低周疲劳断裂分析与预测. 船舶力学, 2024 , 28 (9) : 1420 -1429 . DOI: 10.3969/j.issn.1007-7294.2024.09.012
Huan-cai LIU, Ya-ping LIU, Jun-feng DU, Chun-guang WANG, Chang-zi WANG, Wen-tao HE. Analysis and prediction of ultra-low cycle fatigue fracture of offshore steel based on cyclic void growth model[J]. Journal of Ship Mechanics, 2024 , 28 (9) : 1420 -1429 . DOI: 10.3969/j.issn.1007-7294.2024.09.012
超低周疲劳破坏是一种常见的钢结构损伤破坏模式。海工领域中,在地震、风、浪、流等极端循环载荷的作用下,海工结构极易发生超低周疲劳破坏,造成人员及财产等方面的损失。因此超低周疲劳断裂分析及寿命预测对于海工结构安全性评估至关重要。超低周疲劳(ULCF)通常表现为低周次的载荷循环(通常情况下Nf < 100),同时引起较大的局部塑性应变,导致延性断裂萌生[1]。1968年,McClintock指出整个应力应变过程中孔洞扩张是材料发生延性断裂的主要因素,并提出了圆柱形孔洞扩张模型;Rice和Tracy基于McClintock的研究成果提出在简单应力状态下,延性材料孔洞扩张的速率与应力三轴度呈指数关系,并据此提出了适用于单调加载过程的孔洞扩张模型;Kanvinde等继续引入了材料损伤退化参数,将适用于单调加载的孔洞扩张模型扩展到循环加载过程中,提出了循环孔洞扩张模型;基于循环孔洞扩张模型,廖芳芳等[2-3]利用Q345钢板焊接节点抽取的圆棒试样,通过单调加载和循环加载试验,完成了钢板母材、熔敷金属和热影响区的循环孔洞扩张模型断裂韧性参数校准,校准结果适用于钢结构焊接节点的断裂预测;周晖[4]同样利用试验对孔洞扩张模型参数进行了校准,并利用梁柱节点单调拉伸试验进行参数验证,在此基础上,考虑循环加载作用下的结构累计损伤,在ABAQUS软件中编写了基于循环孔洞扩张模型的USDFLD子程序,实现了对梁柱节点循环加载试验的模拟,验证了循环孔洞扩张模型的准确性;Yin等[5]开展了高强钢焊接接头超低周疲劳断裂试验,通过试验结果与有限元结果分析对比,标定了Q460C高强钢及其焊缝金属基于VGM、CVGM和SMCS模型的断裂韧性参数,结果表明,高强钢材料的断裂韧性参数普遍低于普通强度钢,在梁柱焊接节点中,热影响区受应力集中和材料性能的影响,更易发生超低周疲劳破坏。
现阶段基于循环孔洞扩张模型的超低周疲劳断裂理论中,孔洞扩张指数η及损伤退化参数λ是控制裂纹扩展进程的重要参数。然而研究表明,受生产规范及生产工艺的影响,不同强度及不同批次钢材的断裂韧性参数存在较大差异,影响了超低周疲劳断裂分析准确性。因此在进行海工钢超低周疲劳断裂分析之前,对孔洞扩张指数η及损伤退化参数λ进行校准具有十分重要的意义。同时对于钢材发生韧性断裂,即裂纹萌生后,裂纹的扩展形貌及结构内部应力-应变演化情况尚不明确,基于循环孔洞扩张模型的超低周疲劳断裂仍有待进一步研究。
本文选取海工AH36钢母材,制备了光滑圆棒及平滑槽口圆棒试样,依次开展光滑圆棒单调拉伸试验、平滑槽口圆棒单调拉伸试验及超低周疲劳加载试验,结合有限元分析完成海工钢基本材料参数、混合强化模型参数、孔洞扩张指数及损伤退化参数校准;其次开展V型单边缺口试样超低周疲劳加载试验,分析超低周疲劳加载过程中试样整体荷载-变形响应、裂纹萌生初期试样表面应变分布、裂纹扩展形貌及扩展速度,结合有限元分析完成超低周疲劳断裂全过程数值模拟,验证基于循环孔洞扩张模型的超低周疲劳断裂模拟的有效性,可为工程应用中超低周疲劳断裂分析提供指导。
当钢材经历三轴应力状态时,孔洞倾向于在材料基体中的夹杂物(以碳化物为主)周围形核和扩张并聚合,直到材料中形成宏观裂纹。Rice和Tracy[6]的分析研究表明,孔洞的扩张高度依赖于等效塑性应变εp和应力三轴度T
式中,σm为静水应力,等于三个方向上的主应力之和;σe为Von Mises应力。尽管在经典金属塑性假设中,静水应力不影响无孔洞连续体在宏观水平上的屈服,但其与对应的应力三轴度造成了孔洞周围的局部屈服,导致了孔洞的扩张。
无限连续体中的孔洞扩张速率可以表示为
式中,R为平均孔洞半径,C为常数,为等效塑性应变增量。
对上式两边同时积分,孔洞半径相对于初始孔洞半径R0可以表示为
假定孔洞扩张是断裂过程的控制因素,那么当断裂出现时,上式达到一个临界值,临界状态用式(4)表示:
将式中等式右边的常数项C移至左边,并引入孔洞扩张指数η
式中,ηmonotonic为延性断裂过程中的孔洞扩张指数,为临界孔洞扩张指数。当上式满足时,认为发生了断裂。在针对特定材料进行临界孔洞扩张指数校准后,即可应用孔洞扩张模型进行结构断裂预测。
在孔洞扩张模型(VGM)[7]的基础上,Kanvinde等[8]考虑应力与应变演化过程,提出了适用于循环加载过程的循环孔洞扩张模型(CVGM)。与VGM模型相比,CVGM模型充分考虑了应力三轴度为负,即材料处于压缩阶段时,孔洞体积的压缩对材料造成的影响,此时的孔洞半径可以表示为
式中,右侧第一项反映了在整个循环加载过程中由拉伸造成的孔洞扩张,第二项反映了应力三轴度为负时塑性应变将导致孔洞收缩。进一步整理为
将等式右边的常数项移至左边,并引入孔洞扩张指数η
由于孔洞收缩与孔洞间延性段的循环拉伸,循环加载的临界孔洞扩张指数与单调拉伸的临界孔洞扩张指数相比更小。为确定循环加载过程的临界孔洞扩张指数,Kanvinde提出累计损伤变量,即在加载过程中每次“拉伸”偏移开始时的等效塑性应变,这样既保证了在当前的拉伸循环中累积的等效塑性应变只有助于在该循环中孔洞的扩张,同时也确保材料的延性断裂只会在拉伸过程中发生。
根据试验数据与有限元分析,选取指数衰减函数将联系起来:
式中,λ为损伤退化参数,是材料本身固有属性。
本文编写了基于CVGM的VUSDFLD子程序,实现了超低周疲劳断裂参数输出及有限元模拟,其流程如图1所示。
为确保试验参数一致,本文试样均由同一母材经切割、加工而成。光滑圆棒试样尺寸如图2所示。采用光滑圆棒试样进行单调拉伸试验,获取试样载荷-位移数据,计算应力-应变、弹性模量等基本材料参数。
试验加载采用引伸计进行应变控制,引伸计标距25 mm,量程±15%。数据采集由试样标距段的引伸计位移与试验机数据采集器组成,试验装置与引伸计安装如图3所示。试验过程中准静态加载,在加载到引伸计最大量程后摘除引伸计并继续加载,直至试样发生断裂。根据试样荷载-位移曲线计算材料应力-应变,数据结果如图4~5所示。
制备3种不同开槽口径的平滑槽口圆棒试样,开展了平滑槽口圆棒单调拉伸试验,结合有限元分析进行孔洞扩张指数η校准,试样尺寸如图6所示。
在单调加载下试样发生延性变形,当变形到达一定程度后试样内部裂纹萌生,出现延性断裂。通过单调拉伸试验,获取荷载-变形(标距段)曲线。
采用与2.1节相同尺寸的3种平滑槽口圆棒试样,进行两种不同加载制度[9]下的超低周疲劳加载试验:试样在固定幅值下进行循环加载,直至发生断裂,该幅值为相应尺寸平滑槽口圆棒单调拉伸试验中标距段变形量的0.5倍;试样首先在较低幅值下循环加载5周,该幅值为相应尺寸平滑槽口圆棒单调拉伸试验中标距段变形量的0.25倍,其次施加一个拉力直至试样发生断裂失效。
采用有限元软件ABAQUS[10]进行单调拉伸有限元模拟,针对平滑槽口圆棒试样建立三维模型,材料参数参考2.1节。如图7所示,在槽口区域划分0.2 mm细密网格[11],网格类型为C3D8R。此外,编写了基于VGM的变量输出程序,用于获取单调拉伸过程中孔洞扩张指数。为避免延性断裂模拟中由于隐式计算造成的不收敛问题,本文采用动态显式算法,通过调整计算时间实现准静态分析。
在单调拉伸试验中,试样发生延性断裂,载荷-变形曲线上存在斜率突变点,对应标距段变形量Δf。根据有限元分析结果获取3种试样在标距段变形量为Δf时刻的孔洞扩张指数,并依据孔洞扩张模型进行单元失效判定,当某一单元的孔洞扩张指数达到临界值时,实现单元删除,模拟材料的延性断裂。3种试样的荷载-变形曲线如图8所示。根据图9可知,槽口内部出现单元失效时刻,荷载-变形曲线上出现斜率突变点,随着加载继续进行,裂纹由槽口中心向外发展,荷载-变形曲线下降明显。可见,基于孔洞扩张模型的有限元分析能有效模拟平滑槽口圆棒的延性断裂过程。根据有限元分析结果获取该批母材的孔洞扩张指数η = 2.74。
对超低周疲劳加载试验进行有限元模拟,在有限元分析过程中,混合强化模型参数[12]取值以与试验最为接近为准,有限元分析与试验结果对比如图10所示,试验试样与有限元模型均表现出良好的滞回特性,且曲线吻合良好。
依据各平滑槽口试样循环周次n与标距段变形量Δf获取循环加载下临界孔洞扩张指数,建立损伤比函数:
式中,λ为损伤退化参数,ε为循环加载过程中最后一次“拉伸”偏移开始时的等效塑性应变。将每一组ε与对应的损伤比绘制在同一张散点图中,以最小二乘法对该散点图进行拟合,如图11所示,获取该批母材的损伤退化参数λ = 0.405。
为验证基于CVGM模型的裂纹萌生及裂纹扩展过程,进行了缺口试样超低周疲劳断裂试验及全过程数值模拟[13]。试样尺寸如图12所示,加载制度采用引伸计控制对称循环加载,加载频率为0.0048 Hz。
试验试样见图13,加载第7周时在试样表面缺口尖端出现裂纹,裂纹沿试样对称轴发展,继续进行3周加载后裂纹发展至试样宽度的一半。在整个延性断裂发展过程中,试样缺口处沿45°方向出现了明显的塑性变形区,利用DIC[14]获取试样变形过程的应变情况,结果如图14所示。
为验证ABAQUS进行超低周疲劳断裂模拟[16-18]的有效性,建立了缺口试样有限元模型,网格类型为C3D8R,并将试样缺口尖端处沿断裂路径划分0.2 mm细密网格,确保仿真模型能准确捕获材料的延性断裂过程[15]。仿真结果见图15,通过数值分析获得的滞回曲线与试验曲线基本吻合,验证了循环本构关系的适用性。
采用CVGM判据对缺口试样进行超低周疲劳断裂预测。由图16可知,各单元节点孔洞扩张指数随循环加载的进行呈周期性变化,峰值不断提升,临界孔洞扩张指数随循环加载的进行不断减小。在加载第5周时,缺口位置处部分单元节点孔洞扩张指数超过临界孔洞扩张指数,出现单元失效,裂纹萌生。由图17可知,该情况首先出现在试样受拉过程中,缺口处等向塑性应变最大位置处,表明在循环加载作用下缺口位置处首先发生延性断裂,产生裂纹。这一预测与试验中观察到的现象吻合良好。
为验证超低周疲劳断裂全过程数值模拟的准确性,对比了有限元及试验试样表面裂纹扩展速率曲线。由图18可知,表面裂纹在萌生初期扩展速率较慢,在扩展中期扩展速率加快,扩展末期速率再次变慢。
观察图19中缺口试样裂纹扩展过程,裂纹首先出现在缺口中间部分,在加载至第6周时扩展至试样表面,在试样表面沿对称轴方向发展。扩展至第8周时,裂纹达到试样宽度的一半。
整体上有限元分析扩展进度较试验扩展进度提前一周,扩展速率相近,因此可认为使用循环孔洞扩张模型可以有效预测钢材的超低周疲劳断裂。
基于微观断裂机理的循环孔洞扩张模型是进行超低周疲劳断裂分析及预测的有效方法。本文开展了AH36钢圆棒及缺口试样试验,具体结论如下:
(1)依次开展了光滑圆棒单调拉伸试验、平滑槽口圆棒单调拉伸试验、平滑槽口圆棒超低周疲劳加载试验。根据试验过程中试样荷载-变形曲线获取了材料弹性模量、应力-应变曲线等基本材料信息,确定了平滑槽口圆棒单调拉伸过程中韧性断裂时刻标距段变形以及超低周疲劳加载过程中韧性断裂时刻循环周次与标距段变形。试验结果为有限元分析提供了数据支撑。
(2)在ABAQUS框架中编写了变量输出VUSDFLD子程序,实现了有限元分析增量步迭代过程中的变量输出及单元失效判定,校准了孔洞扩张指数。采用最小二乘法完成了超低周疲劳加载中损伤比-损伤变量的数据拟合,校准了损伤退化参数。
(3)设计并制作了V型单边缺口试样,开展了缺口试样超低周疲劳加载试验,进行了钢材超低周疲劳特性研究,探索了试样开裂机制和损伤演化规律;基于前述理论和程序,开展了缺口试样超低周疲劳断裂有限元模拟,分析了裂纹萌生形式及裂纹扩展速率,进行了试样超低周疲劳断裂寿命预测,与试验结果吻合良好。结果表明,基于循环孔洞扩张模型可以有效实现对钢材的超低周疲劳断裂预测。
  • 国家自然科学基金资助项目(52071308; 51879248; 51609089)
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2024年第28卷第9期
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doi: 10.3969/j.issn.1007-7294.2024.09.012
  • 接收时间:2024-03-26
  • 首发时间:2026-03-26
  • 出版时间:2024-09-20
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  • 收稿日期:2024-03-26
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国家自然科学基金资助项目(52071308; 51879248; 51609089)
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    1.中国海洋大学 工程学院,山东 青岛 266000
    2.山东理工大学 建筑工程学院,山东 淄博 255000

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2种不同金属材料的力学参数

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种数
Number of
species
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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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