Full Scale Explosive Tests in Woomera, Australia
大空间尺度上物种多样性的分布规律_胡军华
应用与环境生物学报 2007,13(5):731~735Chi n J App lEnvi ron B i o l =ISSN 1006 687X2007 10 25收稿日期:2006 07 17 接受日期:2006 09 21*广东省科学院人才基金(No .03 5)和广东省科学院台站基金(2004,2005) Supported by the Fund f or Tal en ts (N o .03 5)and t h e Fund for Fiel d S t ati on (2004,2005)fro m Guangdong Provi n ci alAcade my of S ci ences ,Ch i na**通讯作者 C orres ponding author (E m ai:l hu j h@gde.i gd .cn;ji angz g@i oz .ac .cn)大空间尺度上物种多样性的分布规律*胡军华1,2,3胡慧建1**蒋志刚1**(1中国科学院动物研究所动物生态与保护生物学重点实验室 北京 100080)(2华南濒危动物研究所 广州510260;3中国科学院研究生院 北京 100049)摘 要 物种多样性是生物多样性在物种水平上的表现形式.由于全球性保护行动的开展和多学科的相互渗透,把物种多样性研究推向大时空尺度方向发展,一些新的研究领域得到拓展.本文综述了物种多样性在大空间尺度上的经典研究(包括梯度变化格局、个体大小频次分布格局和物种-面积关系),同时着重探讨了经典研究的新认识及一些新领域内所揭示的新格局,主要有:生物类群间物种数的协同变化、物种和高级分类阶元的关系、局域物种多样性与区域物种多样性关系以及全球变化影响等等.参79关键词 物种多样性;大空间尺度;分布规律;分类单元CLC Q 14D istri bution Regul arities of Species D iversity at Large Spatial Scale*HU Junhua1,2,3, HU H uijian1**&JI A NG Zh i g ang1**(1K e y L abora t ory of Ani ma lE colo gy and Con serva tion,Institute o f Z oology,C hinese Acad e my o f S cie n ces ,Beiji ng 100080,Ch i n a)(2Sou t h Ch i na In stit u t e of E nd ang e re d A ni ma ls ,Guangzhou 510260,Ch i na)(3G raduate Un iversit y of Ch i nese A c ade my of Sciences ,B eiji ng 100049,C h i na)Abstract Spec i es divers it y i s the representa ti on o f biod i versity a t the level of spec i es .D ue to g l oba l conse rvation actions and m ulti disci p lines i nterpene trati on ,t he patterns o f spec i es d i versity have been deve l oped at l arge spa ti o te m pora l sca le .Th is paper rev i ews the classical patterns (i ncl uding the patterns of grad ient change ,frequency d i str i bution of body s i ze and spec ies ar ea curve),and discusses t he new arguments o f classical pa tterns and new ly developed patte rns i n so m e do m a i ns ,s uch as cova riation o f the nu mber of species a m ong tax ono m ic groups ,relations be t w een species and higher tax ono m ic taxa ,re lati ons bet ween l oca l and reg i onal spec i es d i versities and i m pacts of g loba l changes .R ef 79K eyword s species d i versity ;large spati a l sca l e ;distributi on regu l a rity ;taxon CLC Q 14物种多样性是生物多样性在物种水平上的表现形式[1].近年来,空间尺度对物种多样性分布的影响受到人们的重视.空间尺度大体可划分为个体空间、局域斑快、区域尺度、封闭系统和生物地理学尺度.其中,属于大空间尺度范畴的生物地理学尺度倍受关注[2].早在19世纪,人们就已发现物种多样性在大空间尺度上具有一定的规律性,随后对物种多样性的梯度变化格局、个体大小频次分布格局和物种-面积关系等展开了一系列的研究[3,4].近年来,随着对生物多样性全球性衰退以及全球变化认识的提高,人们越来越意识到人类活动对地球生命所造成的巨大破坏,但却还不了解这种破坏所造成的真正后果[5,6].因此,生物多样性在大空间尺度上的保护和研究已不再是单个地区或国家的事务,而是全球的共同责任和义务,多国间的和国际间的合作正在加强,这既有政府行为也有非政府组织的实践[7,8].也正是实践的需要,多学科(如生物地理学、古生物学、群落生态学等)在生物多样性的保护和研究中迅速渗透和结合,使得生物多样性在大时空尺度上的研究向更深更广的方向发展,生物多样性的全球格局研究成为关注的热点[9,10],宏生态学的产生则是其中典型的例子[11,12].如今,在对经典研究重新认识的基础上,物种多样性的大空间尺度格局研究主要是生物类群间物种数的协同变化、物种和高级分类阶元的关系、局域物种多样性与区域物种多样性关系以及全球变化影响等.这些为生物多样性的保护实践提供理论指导[11,13].1 经典研究及新认识1.1 梯度变化1.1.1 空间梯度格局 空间梯度变化是物种多样性大空间尺度格局的一个显著特征,许多综述性文献都有所涉及[1,4,9,13~15].经典研究中,纬度梯度格局最为典型[16],并存在于多种分类类群,如植物[17~19]、脊椎动物[20]、无脊椎动物[14]、海洋生物[21]和海洋生物化石[4].然而,关于纬度梯度格局的解释仍存在较大争议[4,22].这主要是由于不同的研究选择不同的空间尺度引起的[23],对一些在空间梯度格局中可能产生的变量的不同控制也是部分原因(例如,可利用面积或对物种地理分布的几何限制等)[22].其次是垂直梯度格局,包括海拔[24,25]和水深[26].再者是从海洋到内陆梯度格局[27].最后是经度梯度格局,但趋势不明显[28].1.1.2 影响因子与格局关系 许多研究认为物种多样性大空间尺度格局与环境因子密切相关,主要表现在3个方面:(1)在相关性分析中,物种丰富度往往与环境因子呈显著相关[25],有的甚至建立预测模型.张荣祖和林永烈(1985)和张荣祖(1999)在中国的研究发现,物种丰富度与年降水、年均温等因素显著相关[20,29];R etuerto(2004)通过梯度变化和地理分布分析估计植物对气候的适应性[30].有作者给出了能量与物种丰富度间的预测模型[31]和物种丰富度与营养级关系模型[26,32].(2)不同的物理因子与不同的类群之间相关性不同.张荣祖(1999)指出,不同动物类群多样性与年日照时间、降雨等有明显的相关性[29].(3)不同自然区域中各物理因子所起作用不同.在中国的青藏高原地区海拔是第一性的,在干旱和半干旱地区湿度是第一性的[20,29].除环境因子外,当地的历史和生境差异对空间格局也会产影响,如中国与美国维管束植物、被子植物丰富度间的差异[17~19,33~34],尼加拉瓜的鸟类格局[35].生境复杂多样的地方,物种丰富度高[36].1.1.3 机制 物种多样性大空间尺度格局的形成过程是由多因子决定的,是与生物进化历史相联系的复杂过程[9].其形成机制存在多种假说,蒋志刚(1997)列出了其中的8种,这些假说分别用了环境因子和生物因子进行解释,这么多假说的存在是由研究尺度或生物类群不同而造成的[1].有作者认为物种多样性大空间尺度格局一定有一个第一性的原因.一般认为,物理因子是第一性的,而生物间的相互关系是第二性的,能量可能是决定性因子[31,37].1.2 个体大小频次分布格局1.2.1 格局 H utch i nson&M acA rthur(1959)报道了美国密执安州和欧洲陆生兽类身体长度的频次分布图,发现体形中等的兽类物种数要明显多于体型较大或较小的兽类[38].以上格局被证实具有普遍性[39],所有生物物种的个体大小频次分布符合该格局[40].但是,个体大小频次分布被确认为右偏的log正态分布[3].Bro w n&N ico letto(1991)对比北美陆生兽类在大区域和小块生境中的体重频次分布,发现在小块生境中为均匀分布,而大尺度中具有右偏的l og正态分布[41].该结果表明,中等体型的物种占据小范围生境,而较大或较小体形的物种占据大范围生境.M arquet&Cofre(1999)对比了南、北美洲大陆兽类的体重频次分布,发现两大洲具有很大相似性.在南美洲兽类组成中,南、北美洲成分也都符合该规律[39].该结果表明体重频次分布受到起源和历史的影响.1.2.2 机制 Hu tch i nson&M ac A rt hur(1959)指出,该格局是由大量的 马赛克元素 (M o sa i c e le m en ts)组成,体型中等的物种所需元素要少于体形较大或较小的物种[38].由于l og正态分布是多个随机变量多重组合的结果,该解释不久被分形几何学说(F racta l geome try)所代替[42].以上解释忽略了体型较小物种的频次分布特征,所以人们尝试利用生理和生态异速生长来进行解释,涉及个体大小与多度、生长能量间的关系研究.B rown(1993)推导出最佳适宜体重模型,并根据现有生理实验结果,算出兽类最佳体重约为100g、鸟类约为30g,此结果得到实际观察的支持[43].在隔离条件下,一方面,兽类中体重大于100g的物种趋向小型化,而体重小于100g的物种趋向大型化[3];另一方面,兽类体重极大值和极小值分别与物种最大分布面积回归所得方程的交点在100g处[44].因此,上述结果较好地解释了个体大小频次分布格局的内在机制.1.3 物种-面积关系1.3.1 模型 物种-面积效应曲线是生物多样性研究中的经典模型,在生物多样性保护具有重要意义[45].特别是关于热带地区的物种-面积关系已被充分研究[46,47].物种-面积曲线存在4种不同的模式[4],人们通常采用P reston(1962)公式:S=CA z o r lg S=lg C+Z l g A(S为物种数,A为面积,C和Z 为参数)[48].Z值在同一区域的不同生物类群间或不同区域的同一生物类群中差异不明显,而在岛屿与大陆之间有明显差异(岛屿多为0.25~0.35,大陆为0.12~0.18)[4,49].物种数量与面积大小成指数关系源于关于物种丰度的假说或者是自相似性的概念.P l otk i n(2002)却发现这个规律在所有空间尺度上存在一致的离差,而且热带雨林在少于50 h m2的面积内没有自相似性[50].于是发展了一个广义的物种–面积关系模型,能够比任何其他途径都准确地从小尺度数据样本预测出大尺度物种多样性.1.3.2 生物学含义及机制 自P reston(1962)总结物种–面积关系后,许多研究人员尝试解释物种–面积方程及其参数的生物学含义[49].P reston(1962)认为,Z值在0.17~0.33之间是因为物种丰富度符合l og正态分布,加上非隔离区域在取样时有着较高的个体数/物种数比而使斜率低于岛屿值[48].H ansk i&G y llenberg(1997)利用异质种群(M etapopu l a ti on,又译为集合种群)理论提出岛屿-大陆模型和异质种群模型,发现岛屿-大陆模型的斜率要低于异质种群模型,而岛屿-大陆模型对应于岛屿格局而异质种群模型则对应于大陆格局[51].Sto rch(2003)认为物种-面积关系归因于样本效应,栖息地异质性、种群和集合种群过程引起的空间聚群.样本效应和栖息地异质性都不能单独解释观察到的物种-面积模型,两种模型所预测的物种丰富度都比实际高.适合的栖息地数量和样方地占有之间的关系对于2/3的物种来说都是无足轻重的.因此,物种-面积关系的斜率和形状受到栖息地异质性和空间聚集两方面的影响[52].2 新研究及格局2.1 生物类群间物种丰富度的协同变化由于物种多样性在大空间尺度上具有梯度变化格局,人们认为不同生物类群间物种丰富度在空间上存在正相关关系.该关系成为当前生物多样性4个重要研究领域之一[9].但是,相732 应用与环境生物学报 Chi n J App lEnvi ron B i o l 13卷关的研究结果却并不一致.有报道指出,不同生物类群间物种丰富度的相关关系很低而且没有预测价值[53~55];而其他报道称,不同生物类群间物种丰富度高度相关[9,29,56].G aston(2000a)认为,生物类群间物种丰富度的相关是由于受到相同决定性生态因子的影响[9].张荣祖(1999)发现受环境因子影响的相似类群之间物种丰富度具有强相关,两栖类和爬行类支持了该解释[29].中国不同地理尺度上和区域上鸟兽间物种数量具强相关支持G aston(2000a)的观点,并且利用物种-面积曲线可以推导出两类群间的相关模型[56].但是,协同变化的分析结果会受到分类类群、分类单元、数据质量、研究对象、调查时间和研究方法等多种因素影响[56].2.2 物种和高级分类阶元的关系物种和高级分类阶元的关系主要包括两个方面的内容:一是数量上的关系,即物种丰富度和属以上阶元的丰富度关系;二是频次分布关系,即属以上阶元所含物种数的频次分布. 物种和高级分类阶元在数量上具强相关关系,已在许多分类类群上被报道,如植物、兽类、鸟类、两栖类、鱼类等等[57].值得注意的是,这种关系具有普遍意义,无论是不同地理尺度和区域,还是不同类群间都存在[9].人们探讨利用高级分类阶元代替物种作为生物多样性的度量单位来进行热点地区的选择和评价,发现两者效果一致,但高级分类阶元的应用大大节约了时间和费用,因此具有应用价值[57,58].对物种和高级分类阶元的数量相关机理探讨较少,仅作为一种数量关系[59].根据蒋志刚和纪力强(1999)及Jiang&H u (2000a,b),属、科中物种数在鸟兽间具有强相关关系,这表明物种在科、属水平上的频次分布有一定规律性[59~62].因此,物种和高级分类阶元的数量相关应是规律性的.Bro w n(1995)在提出群落 组合规则 时指出物种与高级分类阶元的频次关系为1属1种出现的频次最多,然后是1属2种,再是1属3种,以此类推,并认为此格局是物种竞争的结果[3].然而,在实际研究中却很少有频次关系的相关报道.2.3 局域物种多样性与区域物种多样性间的关系以往,生物多样性方面研究多在小尺度进行,特别是群落生态学研究.这些研究占到生物多样性研究的75%以上[11].但是,越来越多的研究表明,生物多样性在不同空间尺度上有着不同的过程和组成方式[3,9,11].其中,区域的物种构成了局域地区的物种库,直接影响局域地区物种组成[9],并且局域与区域的关系讨论涉及到局域物种丰富度是否存在饱和问题.在局域与区域的物种多样性关系中,两种类型受到特别的重视:一是局域地区物种丰富度小于区域的,但与其成比例关系(类型 );一是局域地区物种多样性只在一定范围内随区域物种多样性增加而增加,到一定值后保持不变(类型 ).现有研究更多地发现类型 的存在.类型 的存在说明局域地区是没有饱和的,这与其他研究相矛盾[9].2.4 全球变化的影响全球变化(G l obal change)作为一个专用的科学名词和一门交叉学科,随着社会对地球环境问题的重视,日益被人们所认识[63].然而,近年来才把全球变化对物种多样性大空间格局影响作为全球变化研究中的重要科学问题之一[64,65].目前,大多数研究集中在CO2浓度增加对物种多样性的影响及生物入侵等问题上[66~72].S m ith(2000)发现,在北美洲西部沙漠地区CO2浓度增加是受全球变化驱使的,并对外来入侵植物有利的这种物种组成变化可能加速火灾发生周期,降低多样性和改变生态系统功能[68].R e ich(2001)则发现在CO2浓度升高和N2沉积的生态系统中,植物多样性和组成影响生物量的增加和碳的获得,物种组成贫乏的比物种组成丰富的增加得要少[69].Zava l eta(2003)模拟全球气候变化,指出C O2浓度的增加和N2的沉积能够减少植物多样性,而降雨量的增加则增加多样性,温度升高没有明显的作用[70].生物入侵被看成是全球变化的重要内容,正成为威胁各地物种多样性的重要因素之一,并即将上升为导致物种多样性丧失的第一位原因[67].生物入侵对物种多样性格局的影响具有两个长期的全球效应:第一,生物入侵将降低地域性动植物区系的独特性,并最终退化和失去服务功能;第二,生物入侵打破地理隔离,造成生物多样性的灾难性丧失[67].Jansson(2003)提出限制特有种的数量的全球模型是由1万~10万年时间内的气候变化引起的,这种关系是随着面积、纬度位置、前冰河作用的程度和海洋岛屿性的变化而变化的[71].Ju lliard(2004)探讨了全球变化中造成普通鸟类物种灭绝的重要因子[72].3 讨论大空间尺度上物种多样性研究受到关注,主要原因是: (1)当前生物学研究朝两个极端方向发展,即 微观更微,宏观更宏 .大空间尺度的研究代表了生物学在宏观上的发展趋势;(2)物种多样性和气候的全球变化正引起人们极大关注,而大空间尺度正迎合了人们了解全球变化的需求;(3)多学科,特别是各种宏观生物学(如宏生态学、宏进化、古生物学、群落生态学、生物地理学等等)在物种多样性研究上迅速渗透和结合,使得生物多样性的研究向大尺度方向发展.因此,物种多样性的大空间尺度研究是学科发展必然趋势.有关空间格局的研究,最主要的驱动力就是对地区乃至全球物种数量的预测及其产生的机制[58].作为一种发展趋势,物种多样性在大空间尺度上的研究已是一交叉性学科,而且还深深地影响了其他学科的发展.首先,不同的学科,如生态学、古生物学、进化生物学、生物地理学相交叉融合,大大促进了相关内容的研究及其机制的探讨.因此,多学科成果的跟踪和应用对大空间尺度上物种多样性分布规律的研究无疑是大有裨益的.p值得指出的是,物种多样性的丧失与其他全球性环境问题有密切关系,全球气候变化正对物种多样性产生深刻影响,而这一切都或多或少受人类活动的影响[73].在冻原或高山寒冷地带,气温的升高已证实能改变群落的物种组成[74,75];即便是哥斯达黎加的热带山区,过去二十几年的气温升高已造成二十多种蛙和蟾蜍等两栖动物的灭绝以及鸟类和爬行类物种的大量减少[76].物种多样性大空间尺度格局研究逐渐使人们意识到人类活动导致生境丧失和全球变化是对物种多样性的最大威胁.至20世纪80年代初,全球41%的热带雨林已经消失[77].F rankel等(1981)报道,大量的热带生物种类在生物学家还未来得及鉴定归类之间就会消失掉[78].据W ilson(1992)7335期胡军华等:大空间尺度上物种多样性的分布规律的估算,仅因热带雨林的破坏一年就造成了27000多种生物的灭绝[79].单纯保护某一个濒危物种的作用是十分有限的,所以应该在更大尺度上进行且是对生态系统的保护[1].R eferences1 蒋志刚,马克平,韩兴国.保护生物学.杭州:浙江科技出版社,19972 孙儒泳.动物生态学原理.北京:北京师范大学出版社,20013 B rown J H.M acroecol ogy.Ch i cago:Ch icago U n i vers it y Press,19954 Rosenw ei gM L.Speci es i n Space and T i 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Mathematical Modeling of the Hot Strip Rolling of Microalloyed Nb,Multiply-Alloyed Cr-Mo,and Plain C-Mn Steels FULVIO SICILIANO,Jr.and JOHN J.JONASIndustrial mill logs from seven different hot strip mills(HSMs)were analyzed in order to calculatethe mean flow stresses(MFSs)developed in each stand.The schedules were typical of the processingof microalloyed Nb,multiply-alloyed Cr-Mo,and plain C-Mn steels.The calculations,based on theSims analysis,take into account work roll flattening,redundant strain,and the forward slip ratio.Themeasured stresses are then compared to the predictions of a model based on an improved MisakaMFS equation,in which solute effects,strain accumulation,and the kinetics of static recrystallization(SRX)and metadynamic recrystallization(MDRX)are fully accounted for.Good agreement betweenthe measured and predicted MFSs is obtained over the whole range of rolling temperatures.Theevolution of grain size and the fractional softening are also predicted by the model during all stagesof strip rolling.Special attention was paid to the Nb steels,in which the occurrence of Nb(C,N)precipitation strongly influences the rolling behavior,preventing softening between passes.The presentstudy leads to the conclusion that Mn addition retards the strain-induced precipitation of Nb;bycontrast,Si addition has an accelerating effect.The critical strain for the onset of dynamic recrystalliza-tion(DRX)in Nb steels is derived,and it is shown that the critical strain/peak strain ratio decreaseswith increasing Nb content;furthermore,Mn and Si have marginal but opposite effects.It is demon-strated that DRX followed by MDRX occurs under most conditions of hot strip rolling;during theinitial passes,it is due to high strains,low strain rates,and high temperatures,and,in the final passes,it is a consequence of strain accumulation.I.INTRODUCTION been achieved.The goal of the present research was,there-fore,to characterize strip rolling in terms of softening mecha-T HE metallurgical features of plate rolling are now nism,strain accumulation,grain size,and precipitation.Also,largely understood.[1–10]The long interpass times allow com-the rolling behavior of microalloyed Nb,plain C-Mn,andsome Cr-Mo grades will be considered and compared. plete static recrystallization(SRX)to take place if the steelAnother important point that arose from this study is that is being rolled above the interpass recrystallization stopthe levels of Mn and Si present in the steel appear to influence temperature(T nr),i.e.,in the absence of carbonitride precipi-the precipitation behavior during strip rolling.The occur-tation.Plate rolling below T nr leads to austenite pancaking,rence of precipitation changes the rolling load and must, because strain-induced precipitation prevents any furthertherefore,be accurately predicted.SRX from occurring.By contrast,during the very shortHodgson[15]has carried out an excellent analysis of the interpass times involved in rod rolling,neither SRX nordifferent types of mathematical models and has supplied a precipitation can take place,[11–14]and,in contrast to platelist of the advantages associated with the application of a rolling,the strain accumulation that takes place leads toparticular model to a given practical situation.According dynamic recrystallization(DRX)followed by metadynamicto this author,the main advantages are(1)a reduction in recrystallization(MDRX).Thus,the metallurgical character-the number of mill trials,(2)an evaluation of hardware istics of plate rolling,on the one hand,and of rod rolling,modifications,(3)the prediction of variables that cannot on the other hand,are now fairly clear.be measured,(4)an estimation of the effect of interactions, From the point of view of interpass time,strip rolling(5)the potential for performance enhancement,and(6) falls between the two processes discussed previously.Duringinexpensive research costs.the initial passes,when the interpass times are still relativelyThe applicability of any model must be intensively tested long,the metallurgical behavior is similar to plate rolling.in advance,preferably with industrial data.That is the As the interpass intervals become shorter,the characteristicsapproach that was employed here.After an improved accu-approach those of rod rolling.Because the classification of racy in predicting the operational parameters has been dem-strip rolling as being like plate rolling,on the one hand,or onstrated,the model can then be applied to production. like rod rolling,on the other,depends on chemistry and The analysis of mean flow stress(MFS)behavior as a rolling schedule as well as pass number,a relatively simple function of inverse absolute temperature permits identifica-and generally accepted analysis of this process has not yet tion of the main microstructural changes taking place duringrolling.These include SRX,DRX followed by MDRX,strainaccumulation,and phase transformation.Figure1illustratesthese phenomena schematically in the form of an MFS vs FULVIO SICILIANO,Jr.,Research Associate,and JOHN J.JONAS,1/T curve for a hypothetical five-pass schedule.Beginning Professor,are with the Department of Metallurgical Engineering,McGillat the first pass(on the left-hand,or high-temperature side), University,Montreal,PQ,Canada H3A2B2.Manuscript submitted March22,1999.there is a low-slope region,within which SRX occurs.The(a )Fig.1—Schematic representation of the evolution of MFS as a function of the inverse absolute temperature.Each characteristic slope is associated with a distinct metallurgical phenomenon.high temperature permits full softening to take place during the interpass interval.After pass 2,the lower temperature does not permit full softening,leading to strain accumula-tion.This accumulation then leads to the onset of DRX (as long as there is no precipitation),which is followed by MDRX between passes 3and 4.The analysis of MFS curves as described previously was first proposed by Boratto et al.[1]for determination of the (b )three critical temperatures of steel rolling (Ar3,Ar1,and Tnr ).[2,3,4]This technique has also been used to deduce that DRX occurs in seamless tube rolling [16,17]as well as in hot strip mills (HSMs).[18,19]Sarmento and Evans [19]came to similar conclusions in their analysis of industrial data from two HSMs.The main types of controlled rolling considered here are listed in the following paragraphs.Recrystallization-Controlled Rolling .In the schedules considered subsequently,as long as strip rolling is carried out above T nr ,SRX is considered to take place.Conversely,below T nr ,there is strain accumulation.Conventional-Controlled Rolling .Here,finishing is employed to flatten or “pancake”the austenite grains at temperatures below T nr .In this case,the particle pinning (c )resulting from the precipitation of Nb(C,N)retards or even Fig.2—Temperature-time diagrams comparing three rolling approaches:prevents the occurrence of recrystallization.In the absence (a )recrystallization controlled rolling,(b )conventional controlled rolling,of precipitation,as long as rolling is carried out below T nr and (c )dynamic recrystallization controlled rolling.for static recrystallization,the strain accumulation that takes place can trigger DRX followed by MDRX,leading to rapid softening between passes.In terms of mathematical model-ing,if there is no precipitation and the accumulated strain exceeds the critical strain,DRX is initiated,often causing caused by DRX when high strain rates are employed and large strains are applied (this corresponds to single-peak full and fast softening.This is usually associated with unpre-dictable load drops in the final passes.[20]behavior in the stress-strain curve).Circumstantial evidence for the occurrence of DRX in seamless tube rolling [16,17]and Dynamic Recrystallization-Controlled Rolling .This type of process consists of inducing DRX in one or more passes HSMs [18,19,21,22]can be found in the literature.Figure 2illustrates schematically the three different rolling during the rolling schedule.This can be done either by applying large single strains to the material or via strain paradigms described previously for a hypothetical five-pass schedule.The conditions associated with each type of rolling accumulation.Both methods allow the total strain to exceed the critical strain for the initiation of DRX.Some of the are displayed in Table I.Knowledge of the rolling parameters and process limitations associated with each method makesbenefits of this approach involve the intense grain refinementTable I.Mechanistic Conditions Pertaining to the Three Controlled Rolling TechniquesRole of Relation betweenType of T Range with Strain-Induced Precipitation andProcess Respect to T nr Precipitation RecrystallizationRCR above absence required SRX before precipitationCCR below presence required precipitation before SRX or DRX DRCR below absence required no SRX;DRX before precipitation possible the design of rolling schedules to fit the needs and B.Analysis of Mill Log Dataconstraints of each case.Logged data were collected from the following fiveHSMs:Dofasco seven-stand HSM(Hamilton,Canada), II EXPERIMENTAL PROCEDURE Algoma six-stand–2.69-m-wide HSM(Sault Ste.Marie,Canada),Sumitomo seven-stand HSM(Kashima,Japan), The present work combines the use of models developedSumitomo seven-stand HSM(Wakayama,Japan),and BHP from hot torsion test data and from the analysis of industrialsix-stand HSM(Port Kembla,Australia).Data from two mill logs.other HSMs were taken from the literature.[19]One is fromthe Usiminas six-stand HSM in Brazil,and the other is an A.Materials unidentified seven-stand HSM referred to here as“Davy.”Some1300logs were made available for analysis,of Various materials were tested and were divided into threewhich about300were examined in detail.The data that groups:microalloyed Nb(group A),multiply alloyed Cr-were employed consisted of interstand distances,work roll Mo(group B),and plain C-Mn(group C)steels.Tables IIdiameters,and pyrometer locations.For each strip,the fol-and III list the grades studied here.In group A(Table II),lowing data were used:chemical composition,strip width, some steels have low Si contents,with the same base compo-strip thicknesses before and after all passes(H and h,respec-sition(e.g.,AD5and AD6and AD7and AD8).Other typestively),work roll rotational speeds,roll forces,and tempera-have different Mn contents,with the same base compositiontures(mean values)for each pass,according to a model or (e.g.,AD9and AD10and AD2,AD3,and AD4).Theseto entry and exit temperatures.grades are used to study the influences of Mn and Si on theThe previous parameters were then employed to calculate precipitation of Nb(C,N)and on the critical strain/peakthe true strains,strain rates,interpass times,and MFSs, strain ratio.Table III gives the chemical compositions ofaccording to the Sims formulation.[4,23]The corrections for some of the multiply alloyed Cr-Mo and plain C-Mn gradesroll flattening,[24,25]redundant strain,and forward slip studied here.The steels used for the torsion tests are markedwith“TT.”between roll and strip[25]were taken into account in theseTable II.Chemical Compositions of the Niobium Steels Investigated(Group A)Steel Plant C Mn Si Nb Ti N*Al P S AA1TT Algoma0.050.350.0100.035—0.0040.0430.0080.006 AA2Algoma0.050.700.1000.053—0.0050.0450.0070.004 AA3Algoma0.060.700.1100.058—0.0050.0450.0080.004 AS1TT Sumitomo0.07 1.120.0500.0230.0160.0000.0290.0190.002 AS2TT Sumitomo0.09 1.330.0600.0360.0160.0030.0190.0170.020 AB BHP0.11 1.050.0100.031—0.0030.0400.0120.012 AD1Dofasco0.060.650.2250.020—0.0040.0350.0080.005 AD2Dofasco0.140.650.2250.020—0.0040.0350.0080.005 AD3Dofasco0.120.850.2250.020—0.0040.0350.0080.005 AD4Dofasco0.12 1.000.2250.020—0.0040.0350.0080.005 AD5Dofasco0.060.650.1150.030—0.0040.0350.0080.005 AD6Dofasco0.060.650.0100.030—0.0040.0350.0080.005 AD7Dofasco0.060.650.1150.045—0.0040.0350.0080.005 AD8Dofasco0.060.650.0100.045—0.0040.0350.0080.005 AD9Dofasco0.060.450.0100.008—0.0040.0350.0080.005 AD10Dofasco0.060.650.0100.008—0.0040.0350.0080.005 AD11Dofasco0.06 1.250.3250.0750.0240.0040.0350.0080.005 AD12Dofasco0.06 1.250.3250.080—0.0040.0350.0080.005 AM1“Davy”0.060.700.0700.050—0.0040.0510.0180.013 AM2“Davy”0.050.450.0200.020—0.0050.0470.0140.008 AU Usiminas0.110.540.0020.018—0.0040.0570.0140.008 *For the Dofasco grades,a mean value of40ppm N is listed here.The actual values are taken into account in the spreadsheets.Table III.Chemical Compositions of the Multiply-Alloyed and Plain C-Mn SteelsGroup Steel Plant C Mn Si Nb Ti Cr Mo V Ni N Al P S B BCM Sumitomo 0.280.520.220——0.830.15——0.0050.0260.0160.004BCMV Sumitomo 0.410.630.280—0.015 1.380.600.270.020.0060.0460.0130.001BCMVN Sumitomo 0.470.660.1700.0160.0160.980.970.120.460.0040.0420.0160.004CCA TT Algoma 0.030.270.010——————0.0040.0420.0080.010CS1TT Sumitomo 0.10 1.080.060——————0.0030.0200.0170.003CS2Sumitomo 0.450.760.210——————0.0050.0040.0170.004CD Dofasco 0.060.270.000——————0.0040.0350.0070.005CM “Davy”0.030.240.020——————0.0040.0420.0090.006CUUsiminas0.050.240.002——————0.0040.0300.0160.010calculations and were organized using MICROSOFT [1];here,the MFS (M )is a function of the strain,strain rate,temperature,and carbon content in weight percent.EXCEL*spreadsheet software.Some typical spreadsheet*MICROSOFT and EXCEL are trademarks of the Microsoft Corpora-M ϭexp 0.126Ϫ1.75C ϩ0.594C 2[1]tion,Redmond,WA.inputs and outputs are shown in Table IV .The same spread-sheet was used for the microalloyed Nb,multiply alloyed ϩ2851ϩ2968C Ϫ1120C 2T0.21˙0.13Cr-Mo,and plain C-Mn grades;this is because it does not consider microstructure but only mechanical parameters.According to the present method,the Sims formulation is employed to calculate and plot the MFS vs 1000/T for several bars.Because strip rolling reductions are applied at III.THE SUBMODELS APPLIED TO HOTSTRIP ROLLING various strains and strain rates,all the derived MFSs are“normalized”to ϭ0.4and ˙ϭ5s Ϫ1.[27,28]An example of this approach for grade D5is illustrated A.The MFS Modelin Figure 3.It can be seen that Misaka’s equation overpre-dicts the MFSs obtained from the mill logs for this 0.03pct Improvement of the Misaka equationMisaka’s equation [26]has often been employed to specify Nb steel.On the other hand,it underpredicts the MFSs for some higher Nb grades.[28]The trend of the Misaka equation the MFS for C-Mn steels during hot strip rolling.It will be used here as the basis for a modified equation that takes fits the mill log values reasonably well in the region where the slope is quite shallow (i.e.,at low 1/T or high T values).into account the effects of different alloying elements,such as Mn,Nb,and Ti.The Misaka equation is displayed in Eq.This indicates that full SRX is occurring between the passesTable IV .Example of the Spreadsheet Calculations Carried Out Using the Mill DataInputs:Data from mill logsRoll Radius Roll Speed Width Gage TemperatureRoll Force Pass (mm)(rpm)(mm)(mm)(ЊC)(Tonne)————30.60——F139433.9126417.339872157F239154.5126410.799512223F338179.212647.429152116F4365119.01264 5.109071691F5363147.11264 3.908961357F6376167.21264 3.148841264F7378172.012642.618721627Outputs Hitchcock Forward Nominal Total Strain Rate Interpass 1000/T Sims MFS Pass R Ј(mm)Slip Factor Strain Strain*(s Ϫ1)Time (s)(K Ϫ1)(MPa)F1403 1.100.660.7512.9 3.480.79116F2412 1.090.550.6125.2 2.140.82151F3416 1.080.430.4841.3 1.480.84179F4402 1.080.430.4772.7 1.010.85151F5428 1.060.310.3494.20.790.86178F6472 1.050.250.271150.630.86185F75611.040.210.23131—0.87250*Includes the redundant strain.effects of the other elements are considered to be linear over their concentration intervals.**Comparison of Tables II and III indicates that the Eq.[2](group A)steels (Table II)have only half the average Si levels (about 0.11)compared to the Eq.[4](group B)steels of Table III (about 0.22pct Si).At the time this analysis was carried out,no account was taken of the Si levels on the MFS and,therefore,on the rolling load.In retrospect,however,this would have been desirable,as it appears from a study of the previous relations that the introduction of such a term may have permitted the use of a single set of coefficients.B.Modeling of Grain Size and Fractional SofteningDuring a particular pass of a rolling schedule,the sum ofFig.3—Comparison of Misaka’s equation and the present equation (MFS*)the retained and applied strains will determine which soften-based on chemical composition and fitted to the mill (Sims)data in the ing mechanism (SRX or DRX ϩMDRX)will operate.SRX region.Here,the mill data for grade AD5(0.03pct Nb)are corrected Depending on the type of softening,different equations are to a constant strain of 0.4and a constant strain rate of 5s Ϫ1.then employed to specify the grain size and fractional soften-ing.In this section,a method is described that can be used to follow the microstructural evolution during multipass roll-in this region.A solution-strengthening factor can,therefore,ing.For now,no attention is paid to the exact onset of DRX,be added that allows Misaka’s equation to fit all grades.For and the critical strain is simply taken as a fixed fraction of compositions AS1,AS2,and AB,for example,a correction the peak strain.The example given subsequently involves for solute strengthening due to the high Mn content (1.12,modeling microstructural evolution in a plain C-Mn grade,1.33,and 1.08,respectively),allows Misaka’s equation to and the critical strain is considered to be 0.8p .The onset fit the mill values.[28]Another correction is still required for of DRX in Nb steels is discussed in the next section,IIIC.the occurrence of strain accumulation and DRX,which leads During rolling,the temperature decreases continuously.to departures from Misaka-type behavior at high values of Thus,the temperature adopted for each interpass interval 1/T (i.e.,low T ).For this purpose,the model by Yada and is taken as the average of the prior and subsequent pass Senuma [29,30,31]was adapted and tested.[25,27,29]This pro-temperatures.This assumption is employed because the pres-duced the following final MFS equation:ent equations were derived for isothermal conditions and the interpass times are short enough to allow the use of a MFS ϩNbϭ(MFS Misaka (0.768ϩ0.51Nb ϩ0.137Mn [2]single temperature value.In the present work,the recrystallization and grain-size ϩ4.217Ti))ϫ(1ϪX dyn )ϩK ss X dynrelations described subsequently were incorporated into the Here,X dyn is the softening attributable to DRX,ss is theMICROSOFT EXCEL spreadsheet software,as shown in steady-state stress,and K ϭ1.14is a parameter that converts more detail in Section IV .The submodels involved here flow stress to MFS.were assembled by following a method developed for rod Equation [2]is valid over the following concentration rolling.[11]The recrystallization kinetics equations used here ranges:0.020to 0.080pct Nb,0.35to 1.33pct Mn,and 0are adaptations of the Avrami–Johnson–Mehl–Kolmogorov to 0.024pct Ti.This approach has been used successfully equation,with parameters that were selected to fit the mill to calculate the MFSs in plain C-Mn [25,27]as well as in Cr-data.Mo steels,[27,32]and the respective equations are displayed 1.Softening between passesin Eqs.[3]and [4],respectivelyA softening model uses parameters such as strain,strain MFS ϩC-Mn ϭ(MFS Misaka (0.768ϩ0.137Mn))[3]rate,initial grain size,and temperature to decide upon the mechanism and calculate the extent of softening.In an HSM,ϫ(1ϪX dyn )ϩK ss X dynthe softening between passes can be calculated with the aid of an MFS equation and temperature corrections.In the The Mn concentrations studied ranged from 0.27to 1.08present work,the microstructural evolution equations were pct.For the multiply alloyed steels,the following relation tested directly using the spreadsheet for the three groups of is applicable:[27,32]steels.The t 0.5equation selected for each group is shown in MFS ϩCr-Moϭ(MFS Misaka (0.835ϩ0.51Nb ϩ0.098Mn Table V .Note that Eq.[6]is the only one available for the DRX ϩ0.128Cr 0.8ϩ0.144Mo 0.3ϩ0.175V [4]kinetics of Nb steels.A similar expression is employed for ϩ0.01Ni))ϫ(1ϪX dyn )ϩK ss X dynthe multiply alloyed grades,as derived in a recent study.[32]For the C-Mn steels,several equations are available;how-Equation [4]is considered to apply to the following composi-ever,the one developed by Hodgson et al.[33,36]provided the tion ranges:0.52to 0.66pct Mn,0to 0.08pct Nb,0.83tobest fit to the mill logs.1.38pct Cr,0to 0.46pct Ni,0.15to 0.97pct Mo,and 0to 0.27pct V .Due to the high maximum concentrations of Cr2.Strain accumulation between passesPartial recrystallization between passes results in retained and Mo,the solution effects approached “saturation;”this is why exponents are employed in this expression.Thestrain,which must be added to the strain applied in theTable V .Equations Describing the Softening KineticsGroup Type EquationReferenceASRX t SRX 0.5ϭ(Ϫ5.24ϩ550[Nb])ϫ10Ϫ18(Ϫ4.0ϩ77[Nb])d 20exp (330,000/R T )[5]33DRXt MDRX 0.5ϭ4.42ϫ10Ϫ7˙(Ϫ0.59)exp (153,000/R T )[6]34,35B SRX32t 0.5ϭ1.57ϫ10Ϫ14иd 20иϪ2.9exp 271,000R T [7]DRX32t 0.5ϭ1.84ϫͫ˙иexp 330,000R TͬϪ0.86exp271,000R T[8]C SRX32,36t SRX0.5ϭ2.3ϫ10Ϫ15Ϫ2.5d 20exp230,000R T [9]DRX14t MDRX 0.5ϭ0.4˙иexp 300,000R TϪ0.8exp240,000R T[10]subsequent stand.The accumulated strain in pass i (i Ͼ1)is small,d 0i ϩ1will be close to the original grain size,d 0i ;in the latter case,the grains only change their shapes because then becomes [37]of the applied strain.[11]a i ϭi ϩK acc (1ϪX i Ϫ1)i Ϫ1[11]b.Grain growth after recrystallizationwhere X is the fractional softening and K acc is a constant.After complete recrystallization,the microstructure is sub-The value of K acc was reported in the literature as falling jected to grain growth;this is driven by the decrease in free between 0.5and 1.[11,37]The parameter K acc can be related energy associated with the grain boundaries.For the group to the rate of recovery.High rates of recovery result in less A and B steels,one single equation (Eq.[19])was employed accumulated strain.This is clear from the work of Gibbs et to describe grain growth:al.,[37]where longer interpass times led to K acc ϭ0.5and shorter interpass times (less recovery)to K acc ϭ1.In the present hot strip model,the K acc constant is assumed to be d 4.5ϭd 4.50ϩ4.1ϫ1023ϫt ip[19]1and the accumulated strain is used in all the calculations.The latter is considered to represent the average strain pres-ϫexp (Ϫ435,000/R T )ent within the material.3.Grain-size evolutionAlthough the previous equation was derived for Nb steels,a.Recrystallized grain sizeit is used here to describe grain growth in the multiply This calculation simply takes into account the initial grain alloyed steels as well.This is due to the lack of an equation size,strain,and/or strain rate.The grain size after SRX is for the multiply alloyed grades,and because the alloying well known to be strongly dependent on the prior strain and elements present in the group B grades make it more rea-only depends on the strain rate to a minor extent.On the other sonable to adopt an equation derived for Nb steels than hand,the grain sizes after MDRX are strongly dependent on one derived for C-Mn grades.The grain-growth kinetics the strain rate.[14,15,34–36,38–41]The equations used here are in Nb and multiply alloyed steels are,of course,expected listed in Table VI.to be slower than in plain C-Mn compositions due to solute The grain size pertaining to the entrance of a given pass drag.For the group C (C-Mn)steels,however,a group of is considered to be the “initial”grain size (d 0).Note that equations is available to describe grain growth.The the equations used to model the recrystallized grain sizes method used here was proposed by Hodgson et al.[11,36,44]for the steels pertaining to groups A and B are the same;and is a “pragmatic”one,based on both laboratory [44]and this is due to the lack of appropriate equations for the multi-industrial [11]observations.ply alloyed steels.It should be noted that there is a large difference between In the case of incomplete recrystallization,the initial grain the rate of growth during the first second of the interpass size for the following pass (d 0i ϩ1)can be calculated using interval and the remaining time.This difference may arise the following relation,[11,33,43]which specifies a kind of because of the large driving force for grain growth present “average”derived from the freshly formed and original in the initially fine-grained structure.Another possible effect grain sizes:concerns the presence of “deformation”vacancies immedi-ately after rolling,which could accelerate growth.[45]This d 0i ϩ1ϭd rex i ϫX 4/3i ϩd 0i (1ϪX i )2[18]transition was handled by adopting different grain-growth exponents for each stage [11]and by using the following With this formulation,when X i is close to 1,the initial grainsize for the following pass is d rex i .On the other hand,if X iequations.Table VI.Equations Describing the Recrystallized Grain SizeGroup Type Equation Ref.A SRX d SRXϭ1.1иd0.670иϪ0.67[12]42DRX34d MDRXϭ1370ϫϪ0.13expϪ45,000R T[13]B SRX d SRXϭ1.1иd0.670иϪ0.67[14]41DRX35d MDRXϭ1370ϫϪ0.13expϪ45,000R T[15]C SRX33,36d SRXϭ343иd0.40иϪ0.5expϪ45,000R T[16]DRX33,36d MDRXϭ2.6ϫ104и˙иexp300,000R TϪ0.23[17]SRX,t ipϽ1s[20]Eq.[3],based on the Misaka equation.The observed andpredicted MFSs are compared in Table VIII,where the differ-ences between the three sets of MFSs are also shown(in d2ϭd2SRXϩ4.0ϫ107(t ipϪ4.32t0.5)expϪ113,000R Tpercentage).The“basic”version of the prediction spreadsheet MDRX,t ipϽ1s[21]described previously,allowing for strain accumulation andDRXϩMDRX,is considered to be fully applicable to the d2ϭd2MDRXϩ1.2ϫ107(t ipϪ2.65t0.5)expϪ113,000R Tgroup C(C-Mn)grades.However,for Nb steels,the criticalstrain for the initiation of DRX must be accurately known,and agreement regarding this quantity is lacking in the litera-SRX,t ipϾ1s[22]ture.The actual precipitation start time during hot strip roll-ing is also an unknown quantity.In the next two sections d7ϭd7SRXϩ1.5ϫ1027(t ipϪ4.32t0.5)expϪ400,000R T(C and D),some improved methods for the estimation ofthese two parameters will,therefore,be proposed anddescribed for the Nb grades.MDRX,t ipϾ1s[23]d7ϭd7MDRXϩ8.2ϫ1025(t ipϪ2.65t0.5)expϪ400,000R T C.Critical Strain for the Initiation of DRX4.Design of the microstructural-predictionThe critical strain for the onset of DRX is an important spreadsheet parameter employed in the mathematical modeling of micro-The previous equations describing the microstructuralstructural evolution and of rolling load.Knowledge of the events can now be organized into a spreadsheet.Basically,critical strain for the initiation of DRX is a requirement for the spreadsheet parameters displayed in Table VII are usedprediction of the operating softening mechanisms in hot as input data to simulate the microstructural changes taking working processes.place during hot rolling,in a pass-by-pass analysis.TheFor the present purpose,it is useful to express the critical starting grain size(after roughing and before strip rolling)strain for the initiation of DRX(c)as a function of the is adopted as100m for the C-Mn grades and as80mpeak strain(p),as determined from a stress-strain curve. for the others.The subsequent grain sizes are calculated This is because several equations are available to specify after recrystallization and grain growth,and the results con-the peak strain as a function of initial grain size,temperature, stitute the input data for the next pass.Both the accumulated and strain rate for Nb steels.Thec/p ratio often lies strain as well as the redundant strain are employed through-between0.67and0.86[46]and is generally considered to be out the calculations.Some typical inputs and outputs of the0.8for plain C-Mn steels.Previous workers have reportedvalues for Nb steels as low as0.65.[34]The effects of Nb, microstructural-evolution spreadsheet are given in Table VII.The following example uses data from the Dofasco HSM,Mn,and Si were taken into account in a recent investiga-grade CD.tion,[47]and a fit was found for thec/p ratio.The method In C-Mn steels,mechanisms such as carbonitride precipi-used was to test several possible values ofc/p and then tation followed by strain accumulation do not take place,soto select the ratio that provides the best fit to the Sims MFS only SRX as well as DRXϩMDRX effects are considered curve.This procedure,thus,specifies the conditions underwhich DRX will occur.Over100mill logs were tested in here.The observed MFS is calculated using the Sims formu-lation(from the mill data).Then,predictions are made using this way using the grades listed in Table I.The resulting。
安捷伦进样针选型指南说明书
Syringe NeedlesThere are so many different needle OD’s (outside diameters), which one do I need?Needle selection is based on application andpersonal choice. When selecting needle diameter,always choose the widest possible to reduce the prob-ability of bending. Autosampler syringes with0.63mm OD needles should be selected for all appli-cations except on-column injection. Care must be taken when selecting an appropriate needle ID for medium to high viscosity samples.I’ve always used a bevel tip needle for mymanual GC injections. Now I have an autosampler and all the needles seem to have cone tips, why?The cone shaped needle tip has been special-ly developed to improve septum lifetimewhen used with an autosampler. Because anautosampler allows the needle to "hit" the septum in exactly the same position each time, the cone design effectively "parts" the septum during piercing, not cuts it, as would a bevel needle. A bevel tip needle isstilled the preferred option for manual injectionwhere "hitting" the septum in exactly the same place is difficult.Needle OptionsWhat’s best, fixed or removable needles?Fixed needle syringes are always the pre-ferred option for experienced operators or for appli-cations requiring trace sample levels. A fixed needle syringe is also recommended for autosampler usewhere the probability of needle bending is minimal.Fixed needles are the most economical syringe option. A fixed needle syringe will also guarantee minimum sample carry-over because the gap between needle and barrel is totally filled with For the novice or inexperienced user a removableneedle syringe is recommended. The removable nee-dle syringe will reduce cost over time because only the needle will need to be replaced if bent.Removable needle syringes can also be heated to 120ºC.To maximize syringe accuracy and repro-ducibility, it is recommended that the minimum vol-ume injected from a syringe is 20% of full scale.This will ensure that variations caused by scale read-ing, needle volume and mechanical handling of the syringe do not become significant errors in dis-pensed syringe volume. Therefore the smallest rec-syringe How do I chooseThe Best Syringe?The most common questions about Syringe SelectionA syringe should be flushed with approximately 5-10 times its totalcapacity to eliminate carryoverbetween samples.TipS Y R I N G EQ AQ AQ AWhy do I need to buy a specific design syringe for my autosampler?SGE autosampler syringes have been designed to meet allfit and function criteria of a specific autosampler model. As mini-mum requirements, they will meet dimensional specifications,accuracy of better than ±1%, plunger and barrel designed for worry free overnight sampling and extended life. A gas tight (Teflon®tipped) syringe should be selected when analyzing dirty samples.A gas tight syringe stops particulate matter from getting between the plunger and barrel by effectively wiping the barrel ID during the plunger stroke. SGE has autosampler syringes for:•GC autosamplers: Hewlett Packard, Perkin Elmer, Shimadzu,Thermoquest/CE, Unicam, Dynatech and Varian instruments.•HPLC autosamplers: ThermoSpectra, Hitachi, Waters, CTC/Fisons, Kontron, Hewlett Packard and Spark Holland instru-ments.How is it possible to measure less that 1mL accurately,what about the needle volume?To accurately dispense 1µL or less, a sample-in-needlesyringe is recommended. These syringes have the ability to inject down to 0.1µL because the entire sample is contained within the needle. Designed with submicron tolerances, these syringes are rugged, robust and reliable with virtually zero dead volume. Liquid and gas tight to 650 atm, they provide maximum precision, accura-cy at ±2%. Sample-in-needle syringes should always be used in conjunction with the SGE FocusLiner™.Syringe PlungerHelp! I always seem to be bending the plunger in my syringe, how can I reduce the risk?Firstly, make sure your syringe technique is correct (contact you local SGE office if you require help with this) and the sample does not contain particulates. If there is a tendency for the plunger to continue to bend, there are a number of alternatives in syringe designs which can help reduce the possibility of bending.For manual syringe operation, Guided Plungers are the most robust barrel and plunger option available. The extended barrel takes the roughest handling without damage, making these syringes ideal for rugged low volume applications or student users. Other alternatives include the Plunger Protection and SuperfleX™syringes. Always use a gas tight (Teflon®tipped) syringe when analyzing dirty sam-ples.Can I replace a bent plunger in my syringe?Metal plungers are individually fitted (to submicron toler-ances) and leak tested to ensure a perfect fit in an individual syringe barrel. This means that the plunger and barrel become a matched pair and cannot be interchanged. Plungers in a gas tight syringes CAN be replaced as they have a multi point sealing,Teflon®tip. Plungers on gas tight syringes are suitable for both gas and liquid samples and are a good alternative if plunger bending is a constant problem in your lab.Tip 2Always keep the box your syringe arrives in. It is the best way to protect the syringe when it’s not in use and also provides a quick reference for part number and description when its time to reorder. It also contains the batch and date codes for ease of traceability.Q AQ AQ ASGE GUIDED PLUNGER SYRINGESSYRINGESTip 3S Y R I N G EWhen injecting volumes <1µL always use an SGE FocusLiner™ for brilliantreproducibility.Modern chromatography instrumentation can detect a femtogram (10-15)?Low detection limits, precision, accuracy and repro-ducibility are only as good as the sample introduction method.Are you using the best syringe for your analytical requirements?Selected syringes are available in packs of six, ten and twenty-five. Packed in a convenient storage box, you can now have dedi-cated syringes and will always have a "spare".S AV E …Q A。
Perceived Stress Scale
Perceived Stress Scale1. Background and referencesThe Perceived Stress Scale is a 10-item self report questionnaire that measures persons’ evaluation of the stressfulness of the situations in the past month of their lives. The citation for the 10-item scale is Cohen, S., & Williamson, G. (1988). Perceived stress in a probability sample of the United States. In S. Spacapan & S. Oskamp (Eds.), The social psychology of health: Claremont Symposium on applied social psychology. Newbury Park, CA: Sage. The PSS was designed for use with community samples with at least a junior high school education. The items are easy to understand and the response alternatives are simple to grasp. Moreover, the questions are quite general in nature and hence relatively free of content specific to any sub-population group. There are also 14- and 4-item versions of the scale, which were not used in the COHRA study.There are many different aspects of stress, including (a) actual environmental experiences, (b) subjective evaluations of the stressfulness of a situation, and (c) the affective, behavioral, or biological responses to environmental experiences or their subjective evaluations. The Perceived Stress Scale measures subjective evaluations of the stressfulness of a situation. These are referred to as appraisals or perceptions of stress. “[This] psychological perspective on stress places emphasis on the organism’s perception and evaluation of the potential harm posed by stimuli (stressors or events). The perception of threat arises when the demands imposed upon an individual are perceived to exceed his or her felt ability to cope with those demands. This imbalance gives rise to labeling oneself as being stressed and to a concomitant negative emotional response. It is important to emphasize that psychological stress is defined not solelyin terms of the stimulus condition or the response variables, but rather in terms of the transaction between the person and the environment. Psychological stress involves interpretation of the meaning of an event and the interpretation of the adequacy of coping resources. In short, the psychological pers pective on stress assumes that stress arises totally out of persons’ perceptions (whether accurate or inaccurate) of their relationship to their environment” (Cohen, Kessler, and Gordon, 1997).The Perceived Stress Scale is the only empirically established index of general stress appraisal. “The PSS measures the degree to which situations in one’s life are appraised as stressful” (Co hen, et al., 1983; p. 385). The original 14-item scale was designed “to tap the degree to which respondents found their lives unpredictable, uncontrollable, and overloading” (p. 387).2. Summary statisticPSS-10 scores are obtained by reversing the scores on the four positive items, e.g., 0=4, 1=3, 2=2, etc. and then summing across all 10 items. Items 4,5, 7, and 8 are the positively stated items. Scores can range from 0 to 40, with higher scores indicating greater stress.The PSS is not a diagnostic instrument, so there are no cut-offs. There are only comparisons between people in a given sample. There are some normative data on the PSS based on a 1983 Harris Poll of a representative U.S. sample. These data may be helpful in providing comparisons, but they are over 20 years old. See: Cohen, S., & Williamson, G. (1988). Perceived stress in aprobability sample of the United States. In S. Spacapan & S. Oskamp (Eds.), The social psychology of health: Claremont Symposium on applied social psychology. Newbury Park, CA: Sage.For more information about PSS scoring (cut-offs and diagnoses), refer to the article:Cohen, S. (1986). Contrasting the hassle scale and the perceived stress scale. American Psychologist, 41, 716-719 (comment).3. Reliability and validityInternal reliability. From Cohen and Williamson, 1988, p. 55, Coefficient alpha of .78.Test-retest reliability. I didn’t find anything. The items on the scale are anchored to appraisalsin the past month, so one would not necessarily expect high test-retest reliability for measurements that did not overlap in time.Construct validity: From Cohen and Williamson, 1988, p. 55: “… PSS scores were moderately related to responses on other measures of appraised stress, as well as to measures of potential sources of stress as assessed by event frequency.”Predictive validity. Go to/research/psychosocial/notebook/pssref.html to see a list of studies that examine the relationship between the Perceived Stress Scale (PSS) and biological or verified disease outcomes.Discriminant validity. In a study examining the relationship of the common cold to negative life events, negative affect, and perceived stress, having more negative life events was associated with more severe clinical illness (i.e., more severe symptoms) whereas greater negative affect and perceived stress were associated with a higher probability of becoming infected (Cohen, et al., 1993). This demonstrates that perceived stress is not the same as negative life events themselves, even though it may have been the negative life events that contributed to the perceived stress.4. Selected abstractsCohen, Sheldon. Perceived stress in a probability sample of the United States. In Spacapan, Shirlynn (Ed); Oskamp, Stuart (Ed). (1988). The social psychology of health. (pp. 31-67). 251 pp. Thousand Oaks, CA, US: Sage Publications, Inc.Abstract(from the chapter) the purpose of this chapter is to present psychometric and descriptive data on a scale designed to measure stress perceptions, and to establish that such a scale can predict the range of health-related outcomes presumed to be associated with appraised stress /// we discuss the advantages of a scale measuring generalized perceptions of stress, describe the Perceived Stress Scale (PSS), and address the controversy surrounding the use of a scale assessing stress perceptions /// we report new and exciting PSS data from a large (2,387 respondents) probability sample of the United States collected by Louis Harris and Associates,Inc. in 1983 /// data are presented on the psychometric qualities of the scale, and on the relation of the PSS to other stress, health, and satisfaction measures.Cohen, Sheldon; Kamarck, Tom; Mermelstein, Robin. A global measure of perceived stress. Journal of Health and Social Behavior. Vol 24(4) Dec 1983, 385-396.Presents data on the Perceived Stress Scale (PSS), a 14-item measure of the degree to which situations in one's life are appraised as stressful. Concurrent and predictive validities and internal and test-retest reliabilities of the new scale were determined using scores from 446 undergraduates and from 64 Ss (mean age 38.4 yrs) participating in a smoking-cessation program offered by the university. Results show that the PSS had adequate reliability and was a better predictor of the outcome in question (depressive and physical symptomatology, utilization of health services, social anxiety, and smoking-reduction maintenance) than were life-event scores. When compared to a depressive symptomatology scale, the PSS was found to measure a different and independent predictive construct. Additional data indicated adequate reliability and validity of a 4-item version of the PSS for telephone interviews. It is suggested that the PSS, which is appended, be used to examine the role of nonspecific appraised stress in the etiology of disease and behavioral disorders and as an outcome measure of experienced levels of stress. Cohen, Sheldon. Contrasting the Hassles Scale and the Perceived Stress Scale: Who's really measuring appraised stress? American Psychologist. Vol 41(6) Jun 1986, 716-718.Responds to the criticism of the perceived stress scale (PSS) developed by the present author and colleagues (see record 1984-24885-001) by R. S. Lazarus et al (see record 1986-10765-001) in their defense of the hassles scale they developed. It is contended that the PSS predicts psychologic and physical symptoms and health behaviors after controlling for any redundancy with psychological symptom measures.Cohen, Sheldon; Tyrrell, David A; Smith, Andrew P. Psychological stress and susceptibility to the common cold. New England Journal of Medicine. Vol 325(9) Aug 1991, 606-612. Examined the association between psychological stress and susceptibility to the common cold. 394 healthy Ss (aged 18-54 yrs) were assessed for degree of stress and then experimentally exposed to 1 of 5 cold viruses, while 26 control Ss were exposed to a placebo. Psychological stress was associated with increased risk of acute infectious respiratory illness in a dose-response manner; this risk was attributable to increased rates of infection. The stress index was associated with host resistance and not with differential exposure to virus. The relation between stress and colds was independent of a variety of health practices, but there was a limited association between stress and clinical illness.Cohen, Sheldon; Tyrrell, David A; Smith, Andrew P. Negative life events, perceived stress, negative affect, and susceptibility to the common cold. Journal of Personality and Social Psychology. Vol 64(1) Jan 1993, 131-140.After completing questionnaires assessing stressful life events, perceived stress, and negative affect, 394 healthy Ss were intentionally exposed to a common cold virus, quarantined, and monitored for the development of biologically verified clinical illness. Consistent with the hypothesis that psychological stress increases susceptibility to infectious agents, higher scores on each of the 3 stress scales were associated with greater risk of developing a cold. However, the relation between stressful life events and illness was mediated by a different biologic processthan were relations between perceived stress and illness and negative affect and illness. That these scales have independent relations with illness and that these relations are mediated by different processes challenges the assumption that perceptions of stress and negative affect are necessary for stressful life events to influence disease risk.。
TheNewcastle-OttawaScale（NOS）forAssessingthe…
Development: Identifying Items
• Identify ‘high’ quality choices with a ‘star’
• A maximum of one ‘star’ for each item within the ‘Selection’ and ‘Exposure/Outcome’ categories; maximum of two ‘stars’ for ‘Comparability’
2. Representativeness of the cases a) consecutive or obviously representative series of cases ♦ b) potential for selection biases or not stated
3. Selection of Controls a) community controls ♦ b) hospital controls c) no description
Selection
1. Is the case definition adequate? a) yes, with independent validation ♦ b) yes, eg record linkage or based on self reports c) no description
Bias and Confounding
电子称用户说明书
• Never load the scale with more than 2.2 lbs. (1 Kg) or permanent damage may occur!• Operate only at normal room temperatures and avoid exposure to extreme heat or cold.• If scale has been stored in a hot or cold location, allow it to acclimate to normal room temperature for at least one hour before use.• Keep scale in a clean environment away from dust, dirt, moisture, vibration, air currents and close proximity to other electronic equipment.• Use only on flat, stable surfaces. Gently place all items to be weighed on tray top only. Avoid shaking, dropping or otherwise shocking the scale.• When powering up, wait 30-60 seconds before weighing to allow internal components to stabilize.• Do not submerse the scale in water or place in dishwasher. Clean with a soft, dry cloth only.• Keep scale out of the reach of children or pets.• Measures accuracy to 0.1g.TARE Press to deduct weight of an item or container placed on the scale (before items to beweighed are added to the container).PCS Activates the “Counting Feature.” This is very useful if, for example, you are bagging multiple items of a uniform weight in bag quantities of 25, 50, 60, 75 or 100.*MODE Press to cycle through units of measure. Measures weight in oz (ounces),g (grams), ozt (troy ounce), dwt (pennyweight), gn (grain) and ct (carat total weight).ON/OFF Switches power on and off. When first turned on, the unit self-tests and displays “HELLo” for a few seconds and then reset to zero.*TO USE THE COUNTING FEATURE: All items must be of uniform weight for the counting feature to work accurately. Press and hold the “PCS” key until you see the number “25” in the numerical display and “PCS” in the upper left corner. Press the “MODE” key repeatedly to cycle through the quantity count you want (25, 50, 60, 75 or 100). Then, place the samequantity of items on the scale that you selected for the quantity count and press “PCS” to set. Remove all items and scale should revert to “0.” Now, without having to count by hand, you simply place as many items on the scale as it takes to display your preset quantity count.AUTO-OFF To conserve battery power, the unit will automatically turn off after 2 minutes ofinactivity. To extend battery life further, you can turn off the scale before 2 minutes have elapsed by pressing “ON/OFF”.OVERLOAD INDICATOR When “EEEE” is displayed it indicates an overload. Remove excessiveload immediately. Remember, you can permanently damage the scale and void your warranty by overloading it!INSTABILITY INDICATOR When “Unst” is displayed it indicates scale is in an unstable position.Make sure scale is on a flat, stable surface.LOW BATTERIES Almost all scale function problems are cause by low batteries. They must be replaced for the scale to function properly.NEGATIVE VALUE Any tared value will be displayed as a negative number once all weight isremoved, press “TARE” or cycle the power to re-zero the scale.1000P R E C I S I O N D I G I T A L S C A L EWhat is “Tare Weight?”“TARE WEIGHT” is the weight of the container used to hold the items you want to ually, you’ll want to weigh a container’s contents only without counting the weight of the container itself. Place your empty container on the scale and press “TARE.” Note the display readjusts to “0.00”.You can now accurately weigh items minus container weight.FUNCTIONS & OPERATIONWARNING!Thank you for purchasing the Measure Master 1000 Digital Scale. This scale is a precision instrument and with normal care and proper treatment it will provide years of reliable service. Measure Master scales can be used for a variety of purposes, including the precise measuring of fertilizers and dry nutrients.Measure Master 1000 Control Panel and LCD DisplayProduct #740633Sunlight 。
Full scale
AbstractAnalysis of full-scale measurements obtained from the instrumented Smedvig West Epsilon jack-up platform operating in the STATOIL Sleipner Vest "eld in the North Sea is described. This jack-up platform has a skirted spud-can foundation. The following topics are discussed in the paper:i Comparison between measured and calculated natural frequencies and modes of the plat- form based on modal analysis.i Comparison of measured foundation sti!ness with the design sti!ness.i Comparison between measured and simulated platform response by application of a nonlin- ear time domain analysis. Implications with respect to procedures and assumptions em-ployed for design of the platform are addressed.The comparison between measured and simulated response is performed for a moderate sea state with a signi"cant wave height of 9.3 m. 1999 Elsevier Science Ltd. All rights reserved.描述了从在北海的STATOIL Sleipner Vest字段中操作的仪表化的Smedvig西Epsilon自升式平台获得的全尺寸测量的分析，该自升式平台具有裙状定位桩基座。
The WSRT wide-field HI survey II. Local Group features
1. Introduction
The high velocity cloud (HVC) phenomenon has been under study for some 40 years, since the first detections of λ21 cm emission from atomic hydrogen at velocities far removed from those allowed by rotation in the Galaxy disk (Muller, Oort & Raimond 1963). Several explanations have been put forth for their interpretation, including a galactic fountain, infall of circum-galactic gas, tidal debris from mergers and subgalactic-mass companions. The suggestion has been made that
Received mmddyy / Accepted mmddyy
Abstract. We have used the Westerbork array to carry out an unbiased wide-field survey of H emission features, achieving an
at least one component of the Galactic HVCs, the so-called CHVCs (Braun & Burton 1999, Blitz et al. 1999) might be the gaseous counterpart of low-mass dark-matter satellites. A critical prediction of this scenario (De Heij et al. 2002) is that a large population of faint CHVCs should be detected in the vicinity of M31 (at declination +40◦ ) if enough sensitivity were available. While existing observational data were consistent with this scenario, they were severely limited by the modest point source sensitivity available at northern declinations (within the Leiden/Dwingeloo Survey, Hartmann & Burton 1997) which is almost an order of magnitude poorer than that of HIPASS (Barnes et al. 2001) in the south. We have undertaken a moderately sensitive large-area H survey both to test for the predicted population of faint
Introduction of personality tests
Examples of personality tests∙The first modern personality test was the Woodworth Personal data sheet, which was first used in 1919. It was designed to help the United States Army screen out recruits who might be susceptible to shell shock.∙The Rorschach inkblot test was introduced in 1921 as a way to determine personality by the interpretation of abstract inkblots.∙The Thematic Apperception Test was commissioned by the Office of Strategic Services (O.S.S.) in the 1930s to identify personalities that might be susceptible to being turned by enemy intelligence.∙The Minnesota Multiphasic Personality Inventory was published in 1942 as a way to aid in assessing psychopathology in a clinicalsetting.∙Myers-Briggs Type Indicator is a 16-type indicator based on Carl Jung's Psychological Types, developed during World War II by Isabel Myers and Katherine Briggs.∙Keirsey Temperament Sorter developed by David Keirsey is influenced by Isabel Myers sixteen types and Ernst Kretschmer's four types.∙The 16PF Questionnaire(16PF) was developed by Raymond Cattell and his colleagues in the 1940s and 1950s in a search to try to discover the basic traits of human personality using scientific methodology.The test was first published in 1949, and is now in its 5th edition, published in 1994. It is used in a wide variety of settings forindividual and marital counseling, career counseling and employee development, in educational settings, and for basic research.∙The Five Factor Personality Inventory - Children (FFPI-C) was developed to measure personality traits in children based upon the Five Factor Model (Big Five personality traits).[3]∙The EQSQ Test developed by Professor Simon Baron-Cohen, Sally Wheelwright, and their team at the University of Cambridge, England, centers on the Empathizing-Systemizing theory of the male versus the female brain types. [1]∙The Personal Style Indicator (PSI) classifies four aspects of innate behavior by testing a person's preferences in wordassociations.∙The Strength Deployment Inventory, developed by Elias Porter, Ph.D.in 1971 and is based on his theory of Relationship Awareness. Porter was the first known psychometrician to use colors (Red, Green and Blue) as shortcuts to communicate the results of a personality test.[4]∙The ProScan Survey is an instrument designed by Professional DynaMetric Programs, Inc. (PDP) to measure the major aspects of self-perception, including an individual’s basic behavior,reaction to environment, and predictable behavior. It wasoriginally developed beginning in 1976 by Dr. Samuel R. Houston, Dr. Dudley Solomon, and Bruce M. Hubby.[5]∙The Newcastle Personality Assessor (NPA), created by Daniel Nettle, is a short questionnaire designed to quantify personality on five dimensions: Extraversion, Neuroticism, Conscientious,Agreeableness, and Openness.[6]∙The DISC assessment is based on the research of William Moulton Marston and later work by John Grier, and identifies fourpersonality types: Dominance; Influence; Steadiness andConscientiousness. It is used widely in Fortune 500 companies, for-profit and non-profit organizations.∙Other personality tests include the NEO PI-R, Forté Profile, Millon Clinical Multiaxial Inventory, Eysenck Personality Questionnaire, Swedish Universities Scales of Personality, and Enneagram of Personality.。
The full detector simulation for the Atlas experiment status and outlook
The full detector simulation for the ATLAS experiment:status and outlookA. RimoldiUniversity of Pavia & INFN, ItalyA.Dell’AcquaCERN, Geneva, CHThe simulation of the ATLAS detector is a major challenge, given the complexity of the detector and the demanding environment of the LHC. The apparatus, one of the biggest and most complex ever designed, requires a detailed, flexible and, if possible, fast simulation which is needed already today to deal with questions related to design optimization, to issues raised by staging scenarios, and of course to enable detailed physics studies to lay the basis for the first physics discoveries. Scalability and robustness stand out as the most critical issues that are to be faced in the implementation of such a simulation. In this paper we present the status of the present simulation and the adopted solutions in terms of speed optimization, centralization of services, framework facilities and persistency solutions. Emphasis is put on the global performance when the different detector components are collected together in a full and detailed simulation. The reference tool adopted is Geant4.1. INTRODUCTIONThe simulation of the Atlas experiment is an ambitious task since it requires a careful and detailed design for providing optimal functionalities in the different domains characterizing it.Its global design is indeed very complex since the detector to be simulated is out of scale respect to any previous ever built: the local environment is demanding because the biggest collaboration of physicists ever gathered is faced to the most complete and challenging physics scenario of the LHC. The simulation domain in Atlas wraps as its own components:• the fast simulation project• the digitization for the implementation of the different detector responses• the MonteCarlo generators• the simulation in GEANT3, operatonal since ten year and still used for Data Challenges purposes • the new simulation in GEANT4, under imple- mentation and test and ready to be used as Atlasbaseline starting from mid 2003.In particular the new simulation in GEANT4 has been developed and tested for physics validation studies to verify the physics content in GEANT4, it was then carefully compared with the current simulation performed in GEANT3 and with real data from testbeam experimental setups, where modules from the subdetectors productions are tested on beam lines.The new simulation should also account for staged scenarios and to beam or machine constraints at the LHC startup.Due to the huge amount of details characterizing it and to the need of improving performances, the simulation itself should also house a fast-simulation for parts of the detector or should gain from the implementation and use of parameterization techniques for optimization issues, without loosing the benefits of a detailed geometry description.In this paper is presented an overview of the simulation project in Atlas with emphasis to the most recent applications in the GEANT4 geometry description of the whole detector and the testbeam setup implementations, while physics validation issues are presented in a different CHEP03 paper (Ref.1).2. A ROAD TO THE ATLAS SIMULATIONData Challenges (DC) are the software milestones for the experiment and simulation is playing the main role for generating the requested event samples. Since the end of 2001 many tests on event productions were performed with the standard GEANT3 simulation. This phase, called DC0, was meant for resuming all the functionalities in place at the Physics Technical Design Report (TDR) time (1999) and to start the procedure for further DCs in the same environment with improved functionalities or using new tools.During DC0 the GEANT4 Atlas community performed a dedicated production of single particle and Higgs events (~10**6) for a selected geometry configuration as early test for application robustness and distributed site production (CERN and Japan).The apparatus geometry described in this application contained a detailed description of the muon system and the tile calorimeter, while rough description of other parts of the Atlas detector were fit together.The following phase (DC1), done in the GEANT3 environment, was characterized, at the beginning, by event generation of small event samples (single particle, B scans and Higgs), then it continued through high statistics single particle, minimum-bias events, QCD-jets and physics events productions.These samples were requested by the different Atlas physics communities for testing purposes in view of the preparation of the subdetectors Technical Design Reports. During this phase, lasting 2002 and continuing in 2003, checks of robustness for large production samples were performed.TUMT001For DC2, expected at startup in late fall 2003, a heavy plan of event productions will undergo both in GEANT3 and in GEANT4 frameworks with goal to refine the present procedures and to add functionalities, being the basis for the Computing TDR (2004).Since May 2000 an extensive programme of physics validations in GEANT4 was launched in order to authenticate the physics content of GEANT4.The purpose was twofold: for the GEANT4 physics benchmarking and the GEANT4 physics validation itself. The aim was to compare features of interaction models with similar features in the Geant3.21 baseline and try to understand differences in applied models, e.g.: effect of cuts on simulation parameters (range cut vs. energy threshold, for example).For the physics validation itself, the purpose was related to the use of available experimental references from testbeam for various sub-detectors and particle types to determine prediction power of models, to estimate the Geant4 performance using different sensitivities of sub-detectors (energy loss, track multiplicities, shower shapes…), to tune Geant4 models (“physics lists”) and parameters (“range cuts”) for optimal representation of the experimental detector signal.The GEANT4 simulation and its validation using testbeam results is the only reality check until there is real data to compare with.3. SIMULATION DATA FLOWIn the ATLAS experiment the simulation data flow is designed in order to optimize the link between the different components as shown in Fig.1.In the simulation there are a number of steps that need to be undertaken. The passage of particles through the detectors is recorded as a number of positions throughout the detectors themselves.The hits information is combined with estimates of internal noise and subjected to a parameterization of the known response of the detectors to produce simulated digital output (digits). The digits can be fed to the pattern recognition and track reconstruction algorithms as if they were real data.The diagram presents the simulation data flow, including Generator and HepMC, pile-up and digitization when the hits generation is performed by the simulation itself and merged hits, after pile-up or from the Level1 digitization, are passed to the ROD emulation algorithm for further processing.Fig.1 The Atlas Simulation data flow TUMT001SSI2002, SLAC, August 5-16, 2002 3 4. THE GEANT3 SIMULATIONThe GEANT3 simulation is the baseline for Atlas since more than ten years; the package was frozen since 1995 and it now is representing the current simulation for the experiment.The program parameters characterizing it are an operative expression of the expected complexity for this experiment: • 27 Millions of distinct volumes copies• 23 thousand of different volume objectsThe processing time per job is about 24 hours while the typical output file for a production of a sample of ~170-320 events (comprehensive of hits and digits) is ~200-300 MB.The detector components are simulated in an evolving representation, while they have been in a stable configuration during all DC1 productions.Pile up was used in the latest production, but full pile-up with cavern background should be added.The simulation program using GEANT3 is still in evolution. In its latest version new implementations were made in the pixel detector and in the forward moderator. Inactive material description and forward shielding are simulated and the correspondent material is taken into account for background evaluation.5. THE GEANT4 SIMULATIONSince years a big effort was devoted to the developing of the simulation program in the new OO environment. In all the Atlas subdetectors a wide program of implementation of a correct, complete and detailed simulation was launched and most applications are already implemented in the common framework of Atlas, among them the complete geometry description of the whole apparatus.The new Geant4 based simulation is meant for dealing with the new physics environment, with extensive tests on apparatus prototypes against real data from testbeam before and during the massive productions of the whole detector components for the real experiment.Currently most applications are using the GEANT4 version 4.1.1 and the upgrade to the new version (5.1R2) was successfully made for the geometry part in all the detector components in the standard framework.5.1.FrameworkThe simulation makes use of the standard Atlas framework (Athena-Gaudi) for all the domain’s components and also profits from standalone applications for development purposes. For the GEANT4 based simulation most applications are developed in a the specific framework, FADS/Goofy (Framework for Atlas Detector Simulation in a Geant4 OO FollY).The framework, born three years ago under redhat6.2 and gcc compiler version 2.95, is successfully running since more than one year in Redhat 7.2, gcc 2.96; the migration to Redhat 7.3.1 gcc 3.2 was successfully completed in 2003.The FADS/Goofy framework was widely used for subdetector applications in the development phase or for testbeam developments implying physics validation studies. This framework is very light, portable and fast. The dynamic loading facility is extensively used as well as the lazy instantiation technique, that allows performing actions on demand through uploading or downloading of specific libraries.In that way the possibility of collecting detector elements at run time, without a predefined detector structure is easily possible.After the development in the simulation framework, the subdetector applications were implemented in the standard Atlas framework (Athena-Gaudi) without any modification. 5.2. Detector geometry in GEANT4The four main subdetectors composing Atlas are implemented in the new simulation with a high level of details.Figures 2 to 6 show three-dimensional views of some geometry implementation of the Atlas subdetectors: the SCT component of the Inner Detector is shown in Fig.2, the LAr calorimeter module in Fig.3, while the complete Tile calorimeter in Fig.4.The muon system is shown in Fig.5: a cut view shows the four different components characterizing it: the precision chamber system in the barrel and forward region (MDT and CSC chamber system) and the trigger system (RPC and TGC system); the complete geometry for the barrel and endcap toroids in shown in Fig.6.Fig. 2 The SCT detector of AtlasTUMT001UC San Diego,CHEP03 , 23-27 March 2003 4Fig.3 LAr electromagnetic calorimeter testbeam moduleThe level of details reached by the new simulation in the geometry description is at least of the same order of magnitude with respect to the one achieved in the previous simulation in Geant3, while the implementation details differ in some cases from the previous simulation due to new functionalities in GEANT4.In the muon system, for example, special solid hexagonal shapes have been implemented in order to describe the CSCFig.4 The tile calorimeter three dimensional view.Fig.5 Open view of the muon system with all the precision system and the trigger system (barrel and endcap regions)Fig.6 The Atlas toroid system with feet, rails and service chimneys.system in the forward region, for the toroids implementation wide use of boolean solids was adopted and for the description of the LAr calorimeter new solid shapes describing the ‘accordion’ geometry were built.5.3.Testbeam geometry in GEANT4In the past years an extensive test of modules in each subsystem was performed in dedicated setups on beam lines and a parallel and wide effort in the simulation followed, in order to verify the physics content of GEANT4.Comparisons with the previous simulation in GEANT3 were performed, for tuning the new simulation and understanding the possible differences when tuning was ineffective.For each subdetector setup a detailed simulation in GEANT4 was put in place. Emphasis was put in the geometry description and in the implementation of the beam line characteristics (beam momentum tuning, beam spread, vertex displacement from the nominal position).Fig. 7 shows the geometry of the tile testbeam modules as simulated after the 1996 data taking period (upper part of Fig. 7) and in a later setup (2001) (lower part of Fig.7).Fig.8 presents a three dimensional view of the complex setup for the forward calorimeter along the beam line: cryostat containing the calorimeter modules and all the components on the setup are described in the simulation.In Fig.9 the setup for the combined geometry of pixel detector, tile and muon system sector is shown.TUMT001SSI2002, SLAC, August 5-16, 2002 5Fig.7 three dimensional view of the tile testbeam modules as in the 1996(up) and 2001(down) setups.Fig.8 The forward LAr calorimeter (FCAL) testbeamsetupFig.9 Testbeam setup for the combined configuration as in CERN H8 testbeam area (summer 2002) with Pixel detector elements, tile calorimeter and barrel sector of the muon system with some extra material in front of the muon setup (Al or Fe blocks).Using these geometries we approached the physics validaton studies in the different Atlas subdetectors: we compared features of interaction models with similar features in Geant 3.21baseline. For the validation we used all available experimental references from testbeam and different sensitivities of subdetectors to estimate the Geant4 performance and we tuned physics lists and parameters (range cut) for optimal representation of the experimental detector signal.AcknowledgmentsThe authors wish to thank all the contributors, developers and users: they made possible the realization of the Atlas simulation since the early times of the Atlas life.Their comments were essential for refinements to the final design and for developing new features that made possible the realization of this work. The following list of references documents the huge amount of work behind this short presentation (Ref. 2 to 8) performed in the last years from a community involving more than 20 people.TUMT001UC San Diego,CHEP03 , 23-27 March 2003 6 References[1] Dell’Acqua,A. (on behalf of the Atlas Geant4Validation team).Status of the physics validationstudies using Geant4 in Atlas (MOMT003)[2] Dell’Acqua,A. et al.The Atlas Muon SpectrometerSimulation using Geant4 ATL-MUON-2000-020[3] Rebuzzi,D. et al. Study of the A/H -> mumu channel in the Muon Spectrometer with GEANT4 and comparison with ATLFAST ATL-MUON-2002-004[4] Rimoldi,A. et al. Geometrical Acceptance for theTrigger Chamber System and study of the reaction H-> ZZ* -> four muons from the acceptance point ofview ATL-DAQ-1998-019 [5] Policicchio,A. et al. Simulation and Reconstructionof Muon Events at the H8 Testbeam (ATL-COM-MUON-2003-014)[6] Kortner,O. et al. Shower production by highly energeticmuons ATL-COM-PHYS-2002-046[7]http://www.mppmu.mpg.de/~kiryunin/g4_note/[8] A.A.Solodkov, V.Tsulaia. TileCal Beam Test SimulationApplication in the FADS/Goofy Framework (GEANT4) ATL-TILECAL-2003-002TUMT001。