Article(id=1241321692845364056, tenantId=1146029695717560320, journalId=1235980550691926019, issueId=1241321691524158287, articleNumber=null, orderNo=null, doi=10.3969/j.issn.0253-6099.2025.02.012, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1729267200000, receivedDateStr=2024-10-19, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773883754215, onlineDateStr=2026-03-19, pubDate=1743436800000, pubDateStr=2025-04-01, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773883754215, onlineIssueDateStr=2026-03-19, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773883754215, creator=13701087609, updateTime=1773883754215, updator=13701087609, issue=Issue{id=1241321691524158287, tenantId=1146029695717560320, journalId=1235980550691926019, year='2025', volume='45', issue='2', pageStart='1', pageEnd='204', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773883753901, creator=13701087609, updateTime=1773884632018, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1241325374676726363, tenantId=1146029695717560320, journalId=1235980550691926019, issueId=1241321691524158287, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1241325374676726364, tenantId=1146029695717560320, journalId=1235980550691926019, issueId=1241321691524158287, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=69, endPage=75, ext={EN=ArticleExt(id=1241321693164131168, articleId=1241321692845364056, tenantId=1146029695717560320, journalId=1235980550691926019, language=EN, title=Optimization of Lifter Bar in Semi-Autogenous Grinding Mill Liner Design Based on Discrete Element Method, columnId=1236276106932842717, journalTitle=Mining and Metallurgical Engineering, columnName=MINERAL PROCESSING, runingTitle=null, highlight=null, articleAbstract=

The parameters of lifter bars in the design of a Φ12.2 m×6.7 m semi-autogenous grinding (SAG) mill liner for the Las Bambas concentrator in Peru were optimized by employing discrete element method, and a quadratic regression model was constructed based on response surface analysis to investigate the effect of various factors on total collision energy and energy dispersion. The results indicate that lifter height has a significant impact on particle motion behavior, and it can alter drop height, particle trajectory and moving range, thereby impacting the collision energy during grinding process. The face angle and width of lifter can influence the distribution of collision energy by adjusting particle positions in the cascading and grinding zones. Based on a comprehensive consideration, the optimal lifter parameters are finally determined as follows: height of 380 mm, width of 100 mm, and face angle of 30°.

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采用离散元法对秘鲁拉斯邦巴斯选矿厂Φ12.2 m×6.7 m半自磨机衬板提升条参数进行优化。基于响应曲面分析,构建二次回归模型,研究各因子对碰撞总能量和能量离散程度的影响。结果表明:提升条高度对颗粒运动行为具有显著影响,它通过改变颗粒抛落高度、抛出范围和运动轨迹,进而影响磨矿过程中碰撞能量的形成;提升条面角和宽度通过调整颗粒在抛落区域和研磨区域的运行位置进而影响碰撞能量的分布。综合考量,确定适宜的衬板提升条参数为:高度380 mm、宽度100 mm、面角30°。

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方鑫(1998—),男,江西鄱阳人,博士研究生,主要研究方向为碎磨原理。E-mail:

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方鑫(1998—),男,江西鄱阳人,博士研究生,主要研究方向为碎磨原理。E-mail:

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方鑫(1998—),男,江西鄱阳人,博士研究生,主要研究方向为碎磨原理。E-mail:

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(a)衬板机械图;(b)衬板结构;(c)几何建模

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(a)抛落高度;(b)抛出范围

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(a)最大碰撞能量;(b)最小碰撞能量

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Physical properties and contact parameters of steel balls and mineral particles

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仿真颗粒参数数值
钢球密度/(kg·m-37 800
泊松比0.3
弹性模量/MPa70 000
矿物密度/(kg·m-32 700
泊松比0.25
弹性模量/MPa1 000
钢球-钢球恢复系数0.5
静摩擦因数0.5
动摩擦因数0.01
钢球-矿物恢复系数0.4
静摩擦因数0.6
动摩擦因数0.02
矿物-矿物恢复系数0.25
静摩擦因数0.8
动摩擦因数0.05
), ArticleFig(id=1241327693313135353, tenantId=1146029695717560320, journalId=1235980550691926019, articleId=1241321692845364056, language=CN, label=表1, caption=

钢球和矿物颗粒的物理属性及接触参数

, figureFileSmall=null, figureFileBig=null, tableContent=
仿真颗粒参数数值
钢球密度/(kg·m-37 800
泊松比0.3
弹性模量/MPa70 000
矿物密度/(kg·m-32 700
泊松比0.25
弹性模量/MPa1 000
钢球-钢球恢复系数0.5
静摩擦因数0.5
动摩擦因数0.01
钢球-矿物恢复系数0.4
静摩擦因数0.6
动摩擦因数0.02
矿物-矿物恢复系数0.25
静摩擦因数0.8
动摩擦因数0.05
), ArticleFig(id=1241327693426381564, tenantId=1146029695717560320, journalId=1235980550691926019, articleId=1241321692845364056, language=EN, label=Table 2, caption=

Control parameters and level values of liner

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水平值提升条高度/mm提升条宽度/mm提升条面角/(°)
13408020
238010030
342012040
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衬板控制参数和水平值

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水平值提升条高度/mm提升条宽度/mm提升条面角/(°)
13408020
238010030
342012040
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Experimental scheme and result of BBD

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试验次数提升条高度H/mm提升条宽度W/mm提升条面角A/(°)碰撞总能量/J能量离散程度
1340100205 0170.288
2340120304 8780.271
334080304 8240.311
4340100404 6500.229
5380120205 3680.343
638080205 6250.366
7380100305 6840.159
8380100305 5540.157
9380100305 7050.159
10380100305 5490.159
11380100305 8080.153
1238080405 2460.361
13380120405 3180.328
14420100205 7490.347
15420120305 6260.390
1642080305 8320.407
17420100405 6700.405
), ArticleFig(id=1241327693665456903, tenantId=1146029695717560320, journalId=1235980550691926019, articleId=1241321692845364056, language=CN, label=表3, caption=

BBD实验方案及结果

, figureFileSmall=null, figureFileBig=null, tableContent=
试验次数提升条高度H/mm提升条宽度W/mm提升条面角A/(°)碰撞总能量/J能量离散程度
1340100205 0170.288
2340120304 8780.271
334080304 8240.311
4340100404 6500.229
5380120205 3680.343
638080205 6250.366
7380100305 6840.159
8380100305 5540.157
9380100305 7050.159
10380100305 5490.159
11380100305 8080.153
1238080405 2460.361
13380120405 3180.328
14420100205 7490.347
15420120305 6260.390
1642080305 8320.407
17420100405 6700.405
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ANOVA analysis results of quadratic regression model

, figureFileSmall=null, figureFileBig=null, tableContent=
模型平方和自由度均方FP
碰撞总能量2.160×10692.400×10534.73<0.000 1
提升条高度1.54×10611.54×106222.52<0.000 1
提升条宽度14 058.29114 058.292.030.196 8
提升条面角95 613.46195 613.4613.840.007 5
拟合不足170.59356.860.004 70.999 5
能量离散程度0.146 990.016 3885.75<0.000 1
提升条高度0.025 310.025 31 372.76<0.000 1
提升条宽度0.001 610.001 686.12<0.000 1
提升条面角0.000 110.000 13.120.120 8
拟合不足0.000 130.000 14.590.087 5
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二次回归模型ANOVA分析结果

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模型平方和自由度均方FP
碰撞总能量2.160×10692.400×10534.73<0.000 1
提升条高度1.54×10611.54×106222.52<0.000 1
提升条宽度14 058.29114 058.292.030.196 8
提升条面角95 613.46195 613.4613.840.007 5
拟合不足170.59356.860.004 70.999 5
能量离散程度0.146 990.016 3885.75<0.000 1
提升条高度0.025 310.025 31 372.76<0.000 1
提升条宽度0.001 610.001 686.12<0.000 1
提升条面角0.000 110.000 13.120.120 8
拟合不足0.000 130.000 14.590.087 5
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基于离散元法的半自磨机衬板提升条参数优化研究
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方鑫 1 , 刘瑜 2, 3 , 李茂林 2, 3 , 黄礼龙 2, 3 , 罗聪 1 , 李良伟 1 , 吴彩斌 1
矿冶工程杂志 | 选矿 2025,45(2): 69-75
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矿冶工程杂志 | 选矿 2025, 45(2): 69-75
基于离散元法的半自磨机衬板提升条参数优化研究
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方鑫1 , 刘瑜2, 3, 李茂林2, 3, 黄礼龙2, 3, 罗聪1, 李良伟1, 吴彩斌1
作者信息
  • 1.江西理工大学 资源与环境工程学院,江西 赣州 341000
  • 2.长沙矿冶研究院有限责任公司,湖南 长沙 410012
  • 3.湖南金磨科技有限责任公司,湖南 长沙 400012
  • 方鑫(1998—),男,江西鄱阳人,博士研究生,主要研究方向为碎磨原理。E-mail:

Optimization of Lifter Bar in Semi-Autogenous Grinding Mill Liner Design Based on Discrete Element Method
Xin FANG1 , Yu LIU2, 3, Maolin LI2, 3, Lilong HUANG2, 3, Cong LUO1, Liangwei LI1, Caibin WU1
Affiliations
  • 1.School of Resources and Environmental Engineering, Jiangxi University of Science and Technology, Ganzhou 341000, Jiangxi, China
  • 2.Changsha Research Institute of Mining and Metallurgy Co., Ltd., Changsha 410012, Hunan, China
  • 3.Hunan Jinmo Technology Co., Ltd., Changsha 400012, Hunan, China
出版时间: 2025-04-01 doi: 10.3969/j.issn.0253-6099.2025.02.012
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采用离散元法对秘鲁拉斯邦巴斯选矿厂Φ12.2 m×6.7 m半自磨机衬板提升条参数进行优化。基于响应曲面分析,构建二次回归模型,研究各因子对碰撞总能量和能量离散程度的影响。结果表明:提升条高度对颗粒运动行为具有显著影响,它通过改变颗粒抛落高度、抛出范围和运动轨迹,进而影响磨矿过程中碰撞能量的形成;提升条面角和宽度通过调整颗粒在抛落区域和研磨区域的运行位置进而影响碰撞能量的分布。综合考量,确定适宜的衬板提升条参数为:高度380 mm、宽度100 mm、面角30°。

磨机  /  衬板  /  磨矿  /  半自磨  /  离散元法  /  响应曲面  /  提升条  /  结构优化

The parameters of lifter bars in the design of a Φ12.2 m×6.7 m semi-autogenous grinding (SAG) mill liner for the Las Bambas concentrator in Peru were optimized by employing discrete element method, and a quadratic regression model was constructed based on response surface analysis to investigate the effect of various factors on total collision energy and energy dispersion. The results indicate that lifter height has a significant impact on particle motion behavior, and it can alter drop height, particle trajectory and moving range, thereby impacting the collision energy during grinding process. The face angle and width of lifter can influence the distribution of collision energy by adjusting particle positions in the cascading and grinding zones. Based on a comprehensive consideration, the optimal lifter parameters are finally determined as follows: height of 380 mm, width of 100 mm, and face angle of 30°.

mill  /  liner  /  grinding  /  semi-autogenous grinding (SAG)  /  discrete element method  /  response surface  /  lifter bar  /  structural optimization
方鑫, 刘瑜, 李茂林, 黄礼龙, 罗聪, 李良伟, 吴彩斌. 基于离散元法的半自磨机衬板提升条参数优化研究. 矿冶工程杂志, 2025 , 45 (2) : 69 -75 . DOI: 10.3969/j.issn.0253-6099.2025.02.012
Xin FANG, Yu LIU, Maolin LI, Lilong HUANG, Cong LUO, Liangwei LI, Caibin WU. Optimization of Lifter Bar in Semi-Autogenous Grinding Mill Liner Design Based on Discrete Element Method[J]. Mining and Metallurgical Engineering, 2025 , 45 (2) : 69 -75 . DOI: 10.3969/j.issn.0253-6099.2025.02.012
半自磨机是一种重要的矿石磨碎设备,广泛应用于现代矿石加工流程中。1932年,世界第一台自磨机问世,开启了矿石自磨技术的应用之路,并在20世纪50年代末在全球各大矿山得到应用[1-2]。20世纪60年代起,加拿大、美国、苏联、澳大利亚、挪威等国的大型冶金矿山纷纷引入了半自磨机,用于提升矿石的磨碎效率[3-4]。同期,中国也刮起了一股自磨技术应用潮[5-6]。直至1997年,铜陵冬瓜山铜矿决定采用半自磨-球磨工艺,开启了半自磨技术在国内矿山选矿厂的应用新时代。
尽管半自磨技术已经相当成熟,但传统研究方法如实验研究和经验公式,往往难以准确描述磨矿过程中复杂的颗粒运动行为。尤其在衬板提升条的设计与优化方面,传统研究方法难以揭示其对磨矿效率的深层影响。本文采用离散元法,通过数值模拟技术深入分析提升条参数对半自磨机磨矿性能的影响机制。离散元法能够在虚拟环境中准确模拟磨机内部的颗粒运动和相互作用,为提升条的优化设计提供科学依据。
离散元法是一种用于模拟颗粒材料和颗粒系统动力学行为的数值计算方法,已广泛应用于研究各种颗粒系统的动力学过程,尤其是在矿石破碎和磨矿领域,表现出强大的分析能力[7-8]
离散元法中,颗粒的运动遵循牛顿第二定律。离散元法的颗粒计算核心内容是接触模型,本文采用Hertz-Mindlin(no-slip)模型,该模型基于Mindlin研究,代表粒子之间的基本接触模型。在这个模型中,法向力和切向力都有阻尼分量,其中阻尼系数与恢复系数有关,切向摩擦力遵循库仑摩擦定律,滚动摩擦力以独立于接触的方向性恒定扭矩模型实现。
离散元法中,不同颗粒物理性能及接触参数是决定群体颗粒相互作用力的关键因素。本文所用钢球和矿物颗粒的物理属性及接触参数见表1
秘鲁拉斯邦巴斯选矿厂Φ12.2 m×6.7 m半自磨机容积为730 m3,转速9.04 r/min,磨机内部充填率(介质与矿物充填率的总和)25%(其中钢球充填率12%、矿物充填率13%),钢球直径127 mm,总负荷为420 t。对该半自磨机进行建模,建模时为避免随机生成的问题,矿物粒度按照实际粒级分布情况以最大粒度进行设定:粒径100 mm的矿物占32%;粒径25 mm的矿物占28%;粒径10mm的矿物占40%。
工业磨机筒体内壁附有衬板。衬板参数主要包括提升条高度、宽度和面角。半自磨机衬板结构及几何建模如图1所示。为探究磨矿过程中不同衬板参数对磨矿效果的影响,采用RSM软件中的Box-Behnken设计(BBD)进行实验设计。选择控制因素为提升条高度、宽度和面角,并分别设定3个不同水平值,详见表2
BBD能有效避免实验条件的极端组合,从而有效减少实验次数,并能保证实验结果的稳定性和可靠性。据此方法,共设计17组实验,每组实验对应不同的控制因素和水平的组合。
本文采用EDEM软件作为仿真平台,首先,将图1中的磨机模型导入仿真环境,在颗粒工厂中设置不同的实验条件,以模拟多样化的工况,包括调控矿物颗粒和介质颗粒的生成。在仿真初始阶段,将两类颗粒引入磨机中,确保其初始状态符合实验设计。接下来开始模拟磨机旋转,使其沿着设计好的转速旋转,最终处于稳定状态后结束仿真。
以7#衬板(提升条高度H=380 mm,宽度W=100 mm,面角A=30°)为例,建立磨矿过程中颗粒速度变化及位置分布如图2所示,其中不同颜色代表不同的颗粒速度。由图2可以看到,高速颗粒主要分布在提升和瀑落区域。在提升区域,颗粒被磨机筒体提升至一定高度,受到离心力和向心力的共同作用;在瀑落区域,颗粒从高处落下,受到重力加速度的作用,势能转变为动能。中低速颗粒主要分布在中间研磨区域,该区域内颗粒受到较小的离心力影响,主要依靠颗粒间的挤压和摩擦实现矿物的碎磨。
颗粒的抛出点和落回点是影响磨矿效率的关键因素。抛出点和落回点水平距离称为抛出范围,抛出点与落回点的高度差决定抛落高度。由图2可知,颗粒的抛出范围为7.76 m,抛落高度为7.36 m。
在磨矿过程中,颗粒接触包括3种形式:钢球-钢球、钢球-矿物和矿物-矿物。以7#衬板为例,磨矿过程中不同形式碰撞下的能量分布如图3所示。可以看出,钢球-钢球形式下的碰撞频率较低,但碰撞能量更大;其次是钢球-矿物和矿物-矿物。这是因为钢球的质量远大于矿物颗粒的质量,根据动能公式Ek=0.5mv2,质量较大的钢球在碰撞时产生的动能更大,而钢球数量相对较少,碰撞频率较低。相比之下,矿物颗粒数量较多,质量较小,碰撞频率较高但能量较低。其中,钢球-钢球碰撞的总能量为7 608 J,钢球-矿物碰撞的总能量为5 684 J,矿物-矿物碰撞的总能量为4 296 J。
采用能量离散程度来评估碰撞能量的分布状况,能量离散程度大,表示碰撞能量在磨矿过程中分布不均匀,能量离散程度小则表示碰撞能量分布较均匀。能量离散程度的计算公式为:
式中:D为能量离散程度;Ei为第i次的碰撞能量;为所有碰撞的平均能量;n为碰撞总次数。通过计算可得,钢球-钢球碰撞能量离散程度为1.61,钢球-矿物碰撞能量离散程度为0.34,矿物-矿物碰撞能量离散程度为0.03。
BBD实验方案及结果见表3
根据表3数据分析影响因子与响应变量之间的关系,对回归系数进行统计检验,二次回归模型ANOVA分析结果见表4
磨矿碰撞总能量E的回归方程为:
该二次回归模型在解释碰撞总能量上表现出显著性,模型的F值为34.73,表明整体模型非常有效,且提升条高度对碰撞总能量的P<0.000 1,表明其对碰撞总能量的影响尤为显著。修正的R2值为0.949 9,预测的R2值为0.964 7,两者相近,表明模型拟合优度较高。同时,模型的拟合不足不显著,说明其能够较好地适应实验数据并进行有效预测。
磨矿碰撞能量离散程度D的回归方程为:
该二次回归模型在预测能量离散程度上表现出极高的显著性,模型的F值为885.75,P<0.000 1,表明模型能够非常有效地解释能量离散程度的变化。具体来看,提升条高度、宽度和面角的主效应(一次项)以及它们的交互效应(AB、AC)和二次项(A2、B2、C2)均显著影响能量离散程度(P值均小于0.05)。模型的拟合不足不显著,意味着模型能够很好地拟合实验数据,并能够可靠地预测能量离散程度。
不同衬板参数下的磨矿运动行为预测值与实际值对比如图4所示。磨矿过程中介质的抛落高度和抛出范围实际值与预测值较为接近,表明该模型具有一定准确性,分析结果具有可信度,进一步说明该回归模型在不同衬板参数的协同作用下能有效描述磨矿过程中颗粒的运动规律。
不同衬板参数交互作用对抛落高度的影响如图5所示。可以发现,提升条高度、宽度和面角均对抛落高度具有显著影响。其中,提升条高度的正向影响很明显,随着高度增加,抛落高度呈现先增加后减小的趋势。表明在高度因子影响下,抛落高度并非呈线性变化,而是存在临界值,超过该值后抛落高度会降低。同时发现,因子间交互作用的影响相对较小,表现出高度与宽度、高度与面角的交互作用均对抛落高度有微弱的正向影响。
不同衬板参数交互作用对抛出范围的影响如图6所示。可以发现,提升条高度、宽度和面角分别对抛出范围产生不同影响。随着提升条高度增加,抛出范围呈现明显的扩展趋势,表明高度因子为正向系数;而宽度和面角均表现负向影响,随着因子数值增大,抛出范围逐渐较小。高度与面角的交互作用进一步抑制了抛出范围的扩展。
结合图5图6分析可知,提升条高度对颗粒运动起关键作用。随着提升条高度增加,颗粒运动能达到更高的抛落点,但这一趋势存在上限。随着颗粒水平抛出范围持续扩大,颗粒在水平面上的位移增加,导致在达到一定数值后,抛落高度反而有所下降。
基于衬板参数对颗粒运动行为分析,进一步对钢球-矿物碰撞能量分布展开研究。不同衬板参数下碰撞能量的最大值和最小值变化情况如图7所示。随着提升条高度增加,最大碰撞能量呈现上升趋势。这是因为增加提升条高度有利于增大颗粒抛落高度,进而提高颗粒势能,在抛落过程中,这部分势能转化为动能,从而提高了钢球对矿物颗粒的最大碰撞能量。随着提升条面角增加,最大碰撞能量呈现下降趋势。尽管面角增加对颗粒的抛落高度影响不大,但它会提高颗粒的脱离概率,同时降低颗粒的落点高度,导致动能减少,进而降低了最大碰撞能量。提升条宽度对最大碰撞能量的影响较小。随着提升条高度增加,最小碰撞能量呈现下降趋势。该能量主要发生在研磨区域,表明抛落高度位置上移和抛出范围增大,在一定程度上会分散研磨区域内钢球-矿物的碰撞强度,从而降低最小碰撞能量。随着提升条面角增加,最小碰撞能量呈现上升趋势,表明提升条面角增大,研磨区域得到增大,使得在该区域内钢球-矿物的碰撞更为集中,最小碰撞能量增大。提升条宽度对最小碰撞能量的影响同样不显著。
不同衬板参数交互作用对碰撞能量离散程度的影响如图8所示。可以发现:随着提升条高度增加,碰撞能量离散程度呈上升趋势;随着提升条面角和宽度增大,碰撞能量离散程度呈先下降后上升的趋势。一方面,随着提升条高度增加,颗粒从更高的位置抛出,增大了最大和最小碰撞能量之间的差距,从而加剧了能量分布的离散性;另一方面,随着提升条面角和宽度增大,颗粒的抛出运动逐渐减弱,导致其从抛落区域向研磨区域转移。当抛落运动减弱时,最大与最小碰撞能量之间的差距缩小,颗粒在研磨区域内的集中运动增加了其动能积累,最终导致能量离散程度再次增大。
基于钢球-矿物碰撞能量分布分析,进一步开展钢球-矿物碰撞总能量研究。不同衬板参数交互作用对碰撞总能量的影响如图9所示。可以看出,提升条高度因子增加时,碰撞总能量显著提高,提升条高度超过380 mm时,碰撞总能量增速开始放缓,最终趋于稳定。提升条宽度和面角对碰撞总能量影响相对较小,均呈现先增加后降低的趋势。宽度和面角交互作用分析结果表明,提升条宽度90~110 mm、面角25°~35°时,宽度和面角的组合有助于提升钢球-矿物碰撞总能量。
结合图8图9,综合考量碰撞能量分布和碰撞总能量,确定适宜的衬板提升条参数组合为:提升条高度380 mm、宽度100 mm、面角30°。该组合能够在保证碰撞总能量的同时,确保碰撞能量分布更集中。
1)提升条高度对颗粒的抛落高度和抛出范围起到关键作用,随着提升条高度增加,颗粒的抛落高度先增大后减小,抛出范围呈现扩大趋势;提升条宽度和面角对颗粒运动的影响较为次要。
2)颗粒运动变化对碰撞能量分布有直接影响。随着提升条高度增加,抛落高度位置上移和抛出范围增大会在一定程度上分散研磨区域内钢球-矿物的碰撞强度,从而降低最小碰撞能量;随着提升条面角和宽度增大,颗粒从抛落区域向研磨区域转移,造成钢球-矿物的碰撞能量分布呈现先减小后增大的趋势。
3)适宜的衬板提升条参数组合为:提升条高度380 mm、宽度100 mm、面角30°。
  • 国家重点研发计划(2022YFC2904602)
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2025年第45卷第2期
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doi: 10.3969/j.issn.0253-6099.2025.02.012
  • 接收时间:2024-10-19
  • 首发时间:2026-03-19
  • 出版时间:2025-04-01
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  • 收稿日期:2024-10-19
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国家重点研发计划(2022YFC2904602)
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    1.江西理工大学 资源与环境工程学院,江西 赣州 341000
    2.长沙矿冶研究院有限责任公司,湖南 长沙 410012
    3.湖南金磨科技有限责任公司,湖南 长沙 400012
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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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