FLUENT经典算例合集7个
案例分析的电子书《数值计算与工程仿真》专刊一 FLUENT HELP算例精选中文版(→)目录前言..2目录FLUENT经典算例翻译之一算例1介绍如何使用 Fluent算例4非定常可压缩流动模型.52算例5辐射与自然对流模拟·:······99FLUENT经典算例翻译之二算例13使用非预混燃烧模型151算例15蒸发性液体喷雾建模.∴214算例18使用混合物多相模型和欧拉多相模型..∴252算例21使用欧拉多相粒子传热模型垂··D垂垂垂。看垂垂垂看D看垂·D4。垂278ww.myCFDcn《数值计算与工程仿真》专刊一 FLUENT HELP算例精选中文版(→)算例1介绍如何使用 Fluent引言此向导通过图例说明了一个发生在混合弯管处的两维湍流流动和传热问题的求解方法和过程。这种混合弯管的结构常见于发电厂和化工厂的管道系统中。正确计算出弯管内流体交汇处附近的流场和温度场分布,对于设计合适的入口管道位置具有重要意义通过此向导,用户可学会以下内容●在 Fluent中输入网格文件使用混合单位制去定义儿何体和流体的属性设置强制对流的湍流流动的流体物性和边界条件迭代计算并使用残差监视器监测计算过程及其收敛性●使用隔离求解器进行求解使用等势图检察流场和温度场●运用二阶离散化方法重新计算以获得更佳的温度分布对网格进行温度梯度自适应,进一步求解更佳的温度场分布前提条件在学习此向导之前,假设用户还没有使用 Fluent的给验,不过,已经学习过用户指南第一章中的简单算例,并且熟悉 Fluent的界面及其指南中的规约可题描述问题如图1-1所小。一股温度为26℃的冷流体流入大管道,在弯管处与另股温度为40℃热流体混合。管道的长度单位为英寸,而流体的属性和边界条件则使用国际单位。入口管道的雷诺数为2.03×105,因此,选择湍流流动模型。4ww.myCFDcn《数值计算与工程仿真》专刊一 FLUENT HELP算例精选中文版(→)P =100 kg/viscosity8x14FConductivity: k=0.537 Y4 miK2SpC Ic Heat 9=4216 Jkg-k6酽.2mT1121m图图1-1问题说明准备工作1.从 Fluent的文件光盘中拷贝文件 elbow/ elbow, msh到电脑的 Fluent作日录中对于Unⅸx系统,当把文件光盘放入电脑光驱后,可以在以下目录找到这个文件:/ edrom/uent61/help/ tuttles述 cdrom为电脑的光驱目录对于 windows系统,当把文件光盘放入电脑光驱后,可以在以下冂录找到个文件cdrom: fluent 6.1 help tutfiles上述 cdrom为电脑的光驱目录2.启动 Fluent,选择2D求解器。ww.myCFDcn《数值计算与工程仿真》专刊一 FLUENT HELP算例精选中文版(→)第1步:与网格相关的操作读取网格文件 elbow, mshFilc→Read+}CascSelect fileFiterh,于d,SH,GRdirectoriesFileshome user tutorial/elbow. msh/home userautorialaCase Filehome /user/tutorialoKFiterCancela)在 Files项中点击选中 elbow. msh,然后点击OK完成操作。注意当 Fluent读取网格文件的同时,信息会不断显示在反馈窗口内,报告网格转化的过程。当读取网格文件完毕, Fluent的反馈窗凵会显示共读取了918个三角形的流体单元,以及许多带着不同分区标识符的边界面。2.网格检查。Grid→} Check6ww.myCFDcn《数值计算与工程仿真》专刊一 FLUENT HELP算例精选中文版(→)F1uent的信息反馈窗口会显示如下信息:Grid checkDomain extentscoordinate:min(m)=0.0000009+00,max(m)=6.400001e+01y- coordinate:min(m)=-4.538534e+00,max(m)=6.400000e+01Volume slatisticsminimum volume (m3): 2.782193c-01maximum volume (m3):3.926232e+00total volume (m3):1.682930e+03Face area statisticsminimum face area (m2):8.015718e-01maximum face area(m2):4. 118252e+00Checking number of nodes per cellChecking number of faces per cellChecking thread pointers.Checking number of cells per faceChecking face cellsChecking bridge facesChecking right-handed cellsChecking face handednessChecking element type consistencyChecking boundary typesChecking face pairs.Checking periodic boundaries.Checking node countChecking nosolve cell countChecking nosolve face countChecking face childrenChecking cell childrenChecking storageww.myCFDcn《数值计算与工程仿真》专刊一 FLUENT HELP算例精选中文版(→)Done注意网格检查结東后,信息反馈窗∏会以默认的SI单位制给出网格在ⅹ轴和Y轴上的最大和最小值,并将报告出网格的賦它特性。网格检查还会报告出有关网格的任何错误。需要特别注意的是,确保最小体积不能是负值,否则 Fluent无法进行计算。在SI单位制中,默认单位是m,若想改变单位制,使用 in ches:可以打开 Scale grid对话框。3.平滑(或者交换)网格Grid→} Smooth/swap…Smooth/Swap GridsmoothSwap InfoMethodNumber SwappedskewnessMinimum skewnesscumber visitedNumher of lerationsSmoothCloseFluent读取网格文件后,平滑三角形或四边形网格是一个良好的习惯,那样能确保使用质量铰好的网格进行计算。a)点击按钮 Smooth,再点击按钮Swap,重复上述操作,直到 Fluent报告没有需要交换的面为止。若 Fluent再无法通过交换改善网格质量,则没有平面可被交换了。b)点击 Close关闭对话框。ww.myCFDcn《数值计算与工程仿真》专刊一 FLUENT HELP算例精选中文版(→)4.更改网格的长度单位Grid→ scalea)在 Units conversion(单位转换)项的 Grid was created ln(网格长度单位)的右侧下拉列表中选择In(代表选择了英寸b)点击 Scale按钮,更改长度单位。在 Domain extents栏中采用了默认的SI单位制,长度单位为mc)点击按钮 Change length Units,设定 inches(英寸)为此次计算采用的长度单位确保Xmax(in)和Ymax(in)中数值为64英尺。(如图1.1)Scale gridScale factorsUnit a conversion00254rid Was Created In inY0+0254Change Length UnitsDomain extentsXmax [in]E4400001Ymin (in534Ymax(in) 64scaleUnscaleCloseHeld)计算采川的长度单位已被吏改为 inches(英寸),此时便能正确反映网格的几何尺寸注意此算例的求解过程中,除了长度外,其它单位均采用SI制。一般来说,没有必要对其它单位进行改动。按照上述的操作,长度单位已被确定为 inches若用户想采用别的单位制作为长度单位,如mm,可以在 Define的下拉菜单中打开 Set units对话框,进行更改。ww.myCFDcn《数值计算与工程仿真》专刊一 FLUENT HELP算例精选中文版(→)5.显示网格。(图1.2)Display→Grid,,Grid DisplOptionsEdge TypeSurfaces三彐p Mores今Atermal-3pressure-outlet-7H Edgesv feature velocity-inlet-5p facesy outlineuelocily-inlet-rall-4Partitionswall-iiShrink factor到终安Surface Types且彐Surface eame patternclip-surfHatchfanOutline InteriorDIsplayColorsCloseHelpa)确保在 surfaces项屮的所有表面都被选屮,然后点击 Display。ww.myCFDcn
- 2020-11-30下载
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Finite-Dimensional Vector Spaces - P. Halmos (Springer, 1987)
在学习代数学之余，值得一看的代数学书籍。里面介绍了更为丰富的代数学概念和结论。PREFACEMy purpose in this book is to treat linear transformations on finite-dimensional vector spaces by the methods of more general theories. Theidea is to emphasize the simple geometric notions common to many partsof mathematics and its applications, and to do so in a language that givesaway the trade secrets and tells the student what is in the back of the mindsof people proving theorems about integral equations and Hilbert spaces.The reader does not, however, have to share my prejudiced motivationExcept for an occasional reference to undergraduate mathematics the bookis self-contained and may be read by anyone who is trying to get a feelingfor the linear problems usually discussed in courses on matrix theory orhigher"algebra. The algebraic, coordinate-free methods do not lose powerand elegance by specialization to a finite number of dimensions, and theyare, in my belief, as elementary as the classical coordinatized treatmentI originally intended this book to contain a theorem if and only if aninfinite-dimensional generalization of it already exists, The temptingeasiness of some essentially finite-dimensional notions and results washowever, irresistible, and in the final result my initial intentions are justbarely visible. They are most clearly seen in the emphasis, throughout, ongeneralizable methods instead of sharpest possible results. The reader maysometimes see some obvious way of shortening the proofs i give In suchcases the chances are that the infinite-dimensional analogue of the shorterproof is either much longer or else non-existent.A preliminary edition of the book (Annals of Mathematics Studies,Number 7, first published by the Princeton University Press in 1942)hasbeen circulating for several years. In addition to some minor changes instyle and in order, the difference between the preceding version and thisone is that the latter contains the following new material:(1) a brief dis-cussion of fields, and, in the treatment of vector spaces with inner productsspecial attention to the real case.(2)a definition of determinants ininvariant terms, via the theory of multilinear forms. 3 ExercisesThe exercises(well over three hundred of them) constitute the mostsignificant addition; I hope that they will be found useful by both studentPREFACEand teacher. There are two things about them the reader should knowFirst, if an exercise is neither imperative "prove that.., )nor interrogtive("is it true that...?" )but merely declarative, then it is intendedas a challenge. For such exercises the reader is asked to discover if theassertion is true or false, prove it if true and construct a counterexample iffalse, and, most important of all, discuss such alterations of hypothesis andconclusion as will make the true ones false and the false ones true. Secondthe exercises, whatever their grammatical form, are not always placed 8oas to make their very position a hint to their solution. Frequently exer-cises are stated as soon as the statement makes sense, quite a bit beforemachinery for a quick solution has been developed. A reader who tries(even unsuccessfully) to solve such a"misplaced"exercise is likely to ap-preciate and to understand the subsequent developments much better forhis attempt. Having in mind possible future editions of the book, I askthe reader to let me know about errors in the exercises, and to suggest im-provements and additions. (Needless to say, the same goes for the text.)None of the theorems and only very few of the exercises are my discovery;most of them are known to most working mathematicians, and have beenknown for a long time. Although i do not give a detailed list of my sources,I am nevertheless deeply aware of my indebtedness to the books and papersfrom which I learned and to the friends and strangers who, before andafter the publication of the first version, gave me much valuable encourage-ment and criticism. Iam particularly grateful to three men: J. L. Dooband arlen Brown, who read the entire manuscript of the first and thesecond version, respectively, and made many useful suggestions, andJohn von Neumann, who was one of the originators of the modern spiritand methods that I have tried to present and whose teaching was theinspiration for this bookP、R.HCONTENTS的 FAPTERPAGRI SPACESI. Fields, 1; 2. Vector spaces, 3; 3. Examples, 4;4. Comments, 55. Linear dependence, 7; 6. Linear combinations. 9: 7. Bases, 108. Dimension, 13; 9. Isomorphism, 14; 10. Subspaces, 16; 11. Calculus of subspaces, 17; 12. Dimension of a subspace, 18; 13. Dualspaces, 20; 14. Brackets, 21; 15. Dual bases, 23; 16. Reflexivity, 24;17. Annihilators, 26; 18. Direct sums, 28: 19. Dimension of a directsum, 30; 20. Dual of a direct sum, 31; 21. Qguotient spaces, 33;22. Dimension of a quotient space, 34; 23. Bilinear forms, 3524. Tensor products, 38; 25. Product bases, 40 26. Permutations41; 27. Cycles,44; 28. Parity, 46; 29. Multilinear forms, 4830. Alternating formB, 50; 31. Alternating forms of maximal degree,52II. TRANSFORMATIONS32. Linear transformations, 55; 33. Transformations as vectors, 5634. Products, 58; 35. Polynomials, 59 36. Inverses, 61; 37. Mat-rices, 64; 38. Matrices of transformations, 67; 39. Invariance,7l;40. Reducibility, 72 41. Projections, 73 42. Combinations of pro-jections, 74; 43. Projections and invariance, 76; 44. Adjoints, 78;45. Adjoints of projections, 80; 46. Change of basis, 82 47. Similarity, 84; 48. Quotient transformations, 87; 49. Range and null-space, 88; 50. Rank and nullity, 90; 51. Transformations of rankone, 92 52. Tensor products of transformations, 95; 53. Determinants, 98 54. Proper values, 102; 55. Multiplicity, 104; 56. Triangular form, 106; 57. Nilpotence, 109; 58. Jordan form. 112III ORTHOGONALITY11859. Inner products, 118; 60. Complex inner products, 120; 61. Innerproduct spaces, 121; 62 Orthogonality, 122; 63. Completeness, 124;64. Schwarz e inequality, 125; 65. Complete orthonormal sets, 127;CONTENTS66. Projection theorem, 129; 67. Linear functionals, 130; 68. P aren, gBCHAPTERtheses versus brackets, 13169. Natural isomorphisms, 138;70. Self-adjoint transformations, 135: 71. Polarization, 13872. Positive transformations, 139; 73. Isometries, 142; 74. Changeof orthonormal basis, 144; 75. Perpendicular projections, 14676. Combinations of perpendicular projections, 148; 77. Com-plexification, 150; 78. Characterization of spectra, 158; 79. Spec-ptral theorem, 155; 80. normal transformations, 159; 81. Orthogonaltransformations, 162; 82. Functions of transformations, 16583. Polar decomposition, 169; 84. Commutativity, 171; 85. Self-adjoint transformations of rank one, 172IV. ANALYSIS....17586. Convergence of vectors, 175; 87. Norm, 176; 88. Expressions forthe norm, 178; 89. bounds of a self-adjoint transformation, 17990. Minimax principle, 181; 91. Convergence of linear transformations, 182 92. Ergodic theorem, 184 98. Power series, 186APPENDIX. HILBERT SPACERECOMMENDED READING, 195INDEX OF TERMS, 197INDEX OF SYMBOLS, 200CHAPTER ISPACES§L. FieldsIn what follows we shall have occasion to use various classes of numbers(such as the class of all real numbers or the class of all complex numbers)Because we should not at this early stage commit ourselves to any specificclass, we shall adopt the dodge of referring to numbers as scalars. Thereader will not lose anything essential if he consistently interprets scalarsas real numbers or as complex numbers in the examples that we shallstudy both classes will occur. To be specific(and also in order to operateat the proper level of generality) we proceed to list all the general factsabout scalars that we shall need to assume(A)To every pair, a and B, of scalars there corresponds a scalar a+called the sum of a and B, in such a way that(1) addition is commutative,a+β=β+a,(2)addition is associative, a+(8+y)=(a+B)+y(3 there exists a unique scalar o(called zero)such that a+0= a forevery scalar a, and(4)to every scalar a there corresponds a unique scalar -a such that十(0(B)To every pair, a and B, of scalars there corresponds a scalar aBcalled the product of a and B, in such a way that(1)multiplication is commutative, aB pa(2)multiplication is associative, a(Br)=(aB)Y,( )there exists a unique non-zero scalar 1 (called one)such that al afor every scalar a, and(4)to every non-zero scalar a there corresponds a unique scalar a-1or-such that aaSPACES(C)Multiplication is distributive with respect to addition, a(a+n)If addition and multiplication are defined within some set of objectsscalars) so that the conditions(A),B), and (c)are satisfied, then thatset(together with the given operations) is called a field. Thus, for examplethe set Q of all rational numbers(with the ordinary definitions of sumand product)is a field, and the same is true of the set of all real numberaand the set e of all complex numbersHHXERCISIS1. Almost all the laws of elementary arithmetic are consequences of the axiomsdefining a field. Prove, in particular, that if 5 is field and if a, and y belongto 5. then the following relations hold80+a=ab )Ifa+B=a+r, then p=yca+(B-a)=B (Here B-a=B+(a)(d)a0=0 c=0.(For clarity or emphasis we sometimes use the dot to indi-cate multiplication.()(-a)(-p)(g).If aB=0, then either a=0 or B=0(or both).2.(a)Is the set of all positive integers a field? (In familiar systems, such as theintegers, we shall almost always use the ordinary operations of addition and multi-lication. On the rare occasions when we depart from this convention, we shallgive ample warningAs for "positive, "by that word we mean, here and elsewherein this book, "greater than or equal to zero If 0 is to be excluded, we shall say"strictly positive(b)What about the set of all integers?(c) Can the answers to these questiong be changed by re-defining addition ormultiplication (or both)?3. Let m be an integer, m2 2, and let Zm be the set of all positive integers lessthan m, zm=10, 1, .. m-1). If a and B are in Zmy let a +p be the leastpositive remainder obtained by dividing the(ordinary) sum of a and B by m, andproduct of a and B by m.(Example: if m= 12, then 3+11=2 and 3. 11=9)a) Prove that i is a field if and only if m is a prime.(b What is -1 in Z5?(c) What is囊izr?4. The example of Z, (where p is a prime)shows that not quite all the laws ofelementary arithmetic hold in fields; in Z2, for instance, 1 +1 =0. Prove thatif is a field, then either the result of repeatedly adding 1 to itself is always dif-ferent from 0, or else the first time that it is equal to0 occurs when the numberof summands is a prime. (The characteristic of the field s is defined to be 0 in thefirst case and the crucial prime in the second)SEC. 2VECTOR SPACES35. Let Q(v2)be the set of all real numbers of the form a+Bv2, wherea and B are rational.(a)Ie(√2) a field?(b )What if a and B are required to be integer?6.(a)Does the set of all polynomials with integer coefficients form a feld?(b)What if the coeficients are allowed to be real numbers?7: Let g be the set of all(ordered) pairs(a, b)of real numbers(a) If addition and multiplication are defined by(a月)+(,6)=(a+y,B+6)and(a,B)(Y,8)=(ary,B6),does s become a field?(b )If addition and multiplication are defined by(α,月)+⑦,b)=(a+%,B+6)daB)(,b)=(ay-6a6+的y),is g a field then?(c)What happens (in both the preceding cases)if we consider ordered pairs ofcomplex numbers instead?§2. Vector spaceWe come now to the basic concept of this book. For the definitionthat follows we assume that we are given a particular field s; the scalarsto be used are to be elements of gDEFINITION. A vector space is a set o of elements called vectors satisfyingthe following axiomsQ (A)To every pair, a and g, of vectors in u there corresponds vectora t y, called the aum of a and y, in such a way that(1)& ddition is commutative,x十y=y十a(2)addition is associative, t+(y+2)=(+y)+a(3)there exists in V a unique vector 0(called the origin) such thata t0=s for every vector and(4)to every vector r in U there corresponds a unique vector -rthat c+(-x)=o(B)To every pair, a and E, where a is a scalar and a is a vector in u,there corresponds a vector at in 0, called the product of a and a, in sucha way that(1)multiplication by scalars is associative, a(Bx)=aB)=, and(2 lz a s for every vector xSPACESSFC B(C)(1)Multiplication by scalars is distributive with respect to vectorddition, a(+y=a+ ag, and2)multiplication by vectors is distributive with respect to scalar ad-dition, (a B )r s ac+ Bc.These axioms are not claimed to be logically independent; they aremerely a convenient characterization of the objects we wish to study. Therelation between a vector space V and the underlying field s is usuallydescribed by saying that v is a vector space over 5. If S is the field Rof real number, u is called a real vector space; similarly if s is Q or if gise, we speak of rational vector spaces or complex vector space§3. ExamplesBefore discussing the implications of the axioms, we give some examplesWe shall refer to these examples over and over again, and we shall use thenotation established here throughout the rest of our work.(1) Let e(= e)be the set of all complex numbers; if we interpretr+y and az as ordinary complex numerical addition and multiplicatione becomes a complex vector space2)Let o be the set of all polynomials, with complex coeficients, in avariable t. To make into a complex vector space, we interpret vectoraddition and scalar multiplication as the ordinary addition of two poly-nomials and the multiplication of a polynomial by a complex numberthe origin in o is the polynomial identically zeroExample(1)is too simple and example (2)is too complicated to betypical of the main contents of this book. We give now another exampleof complex vector spaces which(as we shall see later)is general enough forall our purposes.3)Let en,n= 1, 2,. be the set of all n-tuples of complex numbers.Ix=(1,…,轨)andy=(m1,…,n) are elements of e, we write,,bdefinitionz+y=〔1+叽,…十物m)0=(0,…,0),-inIt is easy to verify that all parts of our axioms(a),(B), and (C),52, aresatisfied, so that en is a complex vector space; it will be called n-dimenaionalcomplex coordinate space
- 2020-12-05下载
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