內容簡介
This edition contains four new sections on the following topics: the BDDC domain decomposition preconditioner (Section 7.8), a convergent adaptive algorithm (Section 9.5), interior penalty methods (Section 10.5) and Poincare-Friedrichs inequalities for piecewise Wp1 functions (Section 10.6).We have made improvements throughout the text, many of which were suggested by colleagues, to whom we are grateful. New exercises have been added and the list of references has also been expanded and updated.
內頁插圖
目錄
series preface
preface to the third edition
preface to the second edition
preface to the first edition
0 basic concepts
0.1 weak formulation of boundary value problems
0.2 ritz-galerkin approximation
0.3 error estimates
0.4 piecewise polynomial spaces - the finite element method
0.5 relationship to difference methods
0.6 computer implementation of finite element methods
0.7 local estimates
0.8 adaptive approximation
0.9 weighted norm estimates
0.x exercises
1 sobolev spaces
1.1 review of lebesgue integration theory
1.2 generalized (weak) derivatives
1.3 sobolev norms and associated spaces
1.4 inclusion relations and sobolev's inequality
1.5 review of chapter 0
1.6 trace theorems
1.7 negative norms and duality
1.x exercises
2 variational formulation of elliptic boundary value problems
2.1 inner-product spaces
2.2 hilbert spaces
2.3 projections onto subspaces
2.4 riesz representation theorem
2.5 formulation of symmetric variational problems
2.6 formulation of nonsymmetric variational problems
2.7 the lax-milgram theorem
2.8 estimates for general finite element approximation
2.9 higher-dimensional examples
2.x exercises
3 the construction of a finite element space
3.1 the finite element
3.2 triangular finite elements
the lagrange element
the hermite element
the argyris element
3.3 the interpolant
3.4 equivalence of elements
3.5 rectangular elements
tensor product elements
the serendipity element
3.6 higher-dimensional elements
3.7 exotic elements
3.x exercises
4 polynomial approximation theory in sobolev spaces
4.1 averaged taylor polynomials
4.2 error representation
4.3 bounds for riesz potentials
4.4 bounds for the interpolation error
4.5 inverse estimates
4.6 tensor. product polynomial approximation
4.7 isoparametric polynomial approximation
4.8 interpolation of non-smooth functions
4.9 a discrete sobolev inequality
4.x exercises
5 n-dimensional variational problems
5.1 variational formulation of poisson's equation
5.2 variational formulation of the pure neumann problem
5.3 coercivity of the variational problem
5.4 variational approximation of poisson's equation
5.5 elliptic regularity estimates
5.6 general second-order elliptic operators
5.7 variational approximation of general elliptic problems
5.8 negative-norm estimates
5.9 the plate-bending biharmonic problem
5.x exercises
6 finite element multigrid methods
6.1 a model problem
6.2 mesh-dependent norms
6.3 the multigrid algorithm
6.4 approximation property
6.5 w-cycle convergence for the kth level iteration
6.6 ]/-cycle convergence for the kth level iteration
6.7 full multigrid convergence analysis and work estimates
6.x exercises
7 additive schwarz preconditioners
7.1 abstract additive schwarz framework
7.2 the hierarchical basis preconditioner
7.3 the bpx preconditioner
7.4 the two-level additive schwarz preconditioner
7.5 nonoverlapping domain decomposition methods
7.6 the bps preconditioner
7.7 the neumann-neumann preconditioner
7.8 the bddc preconditioner
7.x exercises
8 max-norm estimates
8.1 main theorem
8.2 reduction to weighted estimates
8.3 proof of lemma 8.2.6
8.4 proofs of lemmas 8.3.7 and 8.3.11
8.5 lp estimates (regular coefficients)
8.6 lp estimates (irregular coefficients)
8.7 a nonlinear example
8.x exercises
9 adaptive meshes
9.1 a priori estimates
9.2 error estimators
9.3 local error estimates
9.4 estimators for linear forms and other norms
9.5 a convergent adaptive algorithm
9.6 conditioning of finite element equations
9.7 bounds on the condition number
9.8 applications to the conjugate-gradient method
9.x exercises
10 variational crimes
10.1 departure from the framework
10.2 finite elements with interpolated boundary conditions
10.3 nonconforming finite elements
10.4 isoparametric finite elements
10.5 discontinuous finite elements
10.6 poincare-friedrichs inequalitites for piecewise w1p functions
10.x exercises
11 applications to planar elasticity
11.1 the boundary value problems
11.2 weak formulation and korn's inequality
11.3 finite element approximation and locking
11.4 a robust method for the pure displacement problem
11.x exercises
12 mixed methods
12.1 examples of mixed variational formulations
12.2 abstract mixed formulation
12.3 discrete mixed formulation
12.4 convergence results for velocity approximation
12.5 the discrete inf-sup condition
12.6 verification of the inf-sup condition
12.x exercises
13 iterative techniques for mixed methods
13.1 iterated penalty method
13.2 stopping criteria
13.3 augmented lagrangian method
13.4 application to the navier-stokes equations
13.5 computational examples
13.x exercises
14 applications of operator-interpolation theory
14.1 the real method of interpolation
14.2 real interpolation of sobolev spaces
14.3 finite element convergence estimates
14.4 the simultaneous approximation theorem
14.5 precise characterizations of regularity
14.x exercises
references
index
精彩書摘
We will take this opportunity to philosophize about some power-ful characteristics of the finite element formalism for generating discreteschemes for approximating the solutions to differential equations. Being based on the variational formulation of boundary value problems, it is quite systematic, handling different boundary conditions with ease; one simply re-places infinite dimensional spaces with finite dimensional subspaces. What results, as in (0.5.3), is the same as a finite difference equation, in keeping with the dictum that different numerical methods are usually more similarthan they are distinct. However, we were able to derive very quickly the convergence properties of the finite element method. Finally, the notation for the discrete scheme is quite compact in the finite element for mulation.This could be utilized to make coding the algorithm much more efficient if only the appropriate computer language and compiler were available. Thislatter characteristic of the finite element method is one that has not yet been exploited extensively, but an initial attempt has been made in the sys-tem fec (Bagheri, Scott & Zhang 1992). (One could also argue that finiteele ment practitioners have already taken advantage of this by developingtheir own "languages" through extensive software libraries of their own, but this applies equally well to the finite-difference practitioners.)
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前言/序言
Mathematics is playing an ever more important role in the physical and biological sciences, provoking a blurring of boundaries between scientific disciplines and a resurgence of interest in the modern as well as the clas-sical techniques of applied mathematics. This renewal of interest, both inresearch and teaching, has led to the establishment of the series Texts in Applied Mathematics (TAM).
The development of new courses is a natural consequence of a high level of excitement on the research frontier as newer techniques, such asnumerical and symbolic computer systems, dynamical systems, and chaos,mix with and reinforce the traditional methods of applied mathematics.Thus, the purpose of this textbook series is to meet the current and future needs of these advances and to encourage the teaching of new courses.
TAM will publish textbooks suitable for use in advanced undergraduateand beginning graduate courses, and will complement the Applied Mathe-matical Sciences (AMS) series, which will focus on advanced textbooks andresearch-level monographs.
《現代數值計算方法與算法》 內容簡介 本書係統地探討瞭現代數值計算領域的核心理論、關鍵算法及其在工程與科學計算中的應用。全書結構嚴謹,內容涵蓋瞭從基礎的綫性代數運算到復雜偏微分方程數值解法的全貌,力求在理論深度與實際應用之間取得最佳平衡。 本書的目標讀者是高年級本科生、研究生以及從事數值模擬、數據分析和計算科學的專業研究人員。它不僅提供瞭紮實的理論基礎,更側重於算法的內在機製、穩定性和收斂性分析,以及如何在實際計算環境中高效地實現這些算法。 第一部分:數值分析基礎與誤差理論 本部分奠定整個數值計算的理論基石。首先,對實數運算、浮點數錶示、機器精度和截斷誤差、捨入誤差進行瞭詳盡的闡述。重點討論瞭誤差的傳播和纍積效應,特彆是如何通過閤理的算法設計來控製誤差的增長。隨後,深入分析瞭函數逼近的數學工具,包括多項式插值(如牛頓插值、拉格朗日插值),並詳細討論瞭插值餘項的性質,引導讀者理解“完美”插值在實際中的局限性。 第二部分:綫性方程組的數值求解 綫性係統 $Ax=b$ 的求解是計算科學的基石。本章首先迴顧瞭矩陣代數的基礎知識,隨後聚焦於兩大類求解方法:直接法和迭代法。 在直接法部分,詳細分析瞭高斯消元法及其對計算復雜度的影響。重點討論瞭矩陣的分解技術,特彆是LU分解、Cholesky分解(針對對稱正定矩陣)和QR分解。每種分解方法都配有詳細的算法步驟、誤差分析和對特定矩陣結構的適用性討論。 迭代法部分,本書著重探討瞭求解大型稀疏綫性係統的有效策略。講解瞭雅可比迭代和高斯-賽德爾迭代的收斂性條件(如對角占優矩陣),並深入剖析瞭更高級的迭代方法,如共軛梯度法(CG)、最小殘量法(MINRES)和雙共軛梯度法(BiCGStab)。針對非對稱係統,對預處理技術(如代數多重網格預處理、代數重構預處理)的重要性進行瞭詳盡的論述,強調預處理器對加速收斂速度的關鍵作用。 第三部分:非綫性方程與優化問題 本部分轉嚮非綫性的世界。對於單變量非綫性方程 $f(x)=0$,本書詳細比較瞭割綫法、牛頓法、信賴域法等方法的優缺點,特彆是牛頓法在局部二次收斂性上的優勢和計算成本。 在多變量非綫性方程組 $mathbf{F}(mathbf{x})=mathbf{0}$ 的求解中,重點介紹瞭牛頓法及其準牛頓方法的變體,如BFGS和DFP算法,這些算法通過近似計算Hessian矩陣,顯著降低瞭計算復雜度。 優化理論部分是本章的另一核心。從無約束優化開始,詳細分析瞭最速下降法、牛頓法、準牛頓法,並引入瞭擬牛頓法的收斂性理論。對於約束優化問題,本書深入講解瞭拉格朗日乘子法、KKT條件,並詳細闡述瞭序列二次規劃(SQP)方法,這是求解大規模非綫性約束問題的有效手段。 第四部分:常微分方程(ODE)的數值積分 常微分方程在建模物理、化學和生物係統時無處不在。本章專注於建立和分析ODE的數值解法。 首先,介紹瞭前嚮和後嚮歐拉法,並討論瞭它們的穩定域。隨後,係統地講解瞭龍格-庫塔(Runge-Kutta, RK)方法族,特彆是經典的四階RK法(RK4)。在穩定性和精度方麵,本書對絕對穩定性和A-穩定性進行瞭詳細的數學推導和幾何解釋,這是選擇隱式方法(如後嚮歐拉法)的關鍵依據。對於剛性方程組(Stiff Equations),本書專門闢齣章節,講解瞭隱式歐拉法和BDF(後嚮微分公式)方法的構建和應用,強調瞭如何處理大時間步長下的計算穩定性。 第五部分:偏微分方程(PDE)的數值方法概論 本部分是全書的高級主題之一,為後續更專業的數值方法學習打下基礎。本書側重於介紹求解擴散方程(熱傳導方程)和波動方程(波動方程)的通用框架,避免陷入某一特定離散化技術的細節。 對有限差分法(FDM)進行瞭詳盡的討論,包括如何利用泰勒展開構建高階差分近似,並分析瞭Von Neumann穩定性分析方法,用於判斷時間步長和空間步長的耦閤關係。 此外,本書還引入瞭譜方法的基本思想,展示瞭傅裏葉級數展開在周期性問題求解中的高效性,並簡要對比瞭譜方法與局部離散化方法的特點。 本書特色與優勢 1. 理論與實踐並重: 每種核心算法後都附有詳細的穩定性、收斂性分析和計算復雜度的評估。 2. 清晰的算法結構: 所有關鍵算法均以僞代碼形式清晰呈現,便於讀者直接轉化為計算機程序實現。 3. 深入的矩陣代數背景: 對矩陣性質、特徵值和奇異值分解在數值穩定性中的作用進行瞭強化講解。 4. 現代計算視角: 關注瞭大規模計算中的稀疏性處理和預處理技術,這些是現代高性能計算環境中的必備知識。 本書內容全麵、論述嚴謹,是深入理解現代計算科學和進行復雜工程仿真不可或缺的參考教材。