大規模流場科學計算可視化

《大規模流場科學計算可視化》是2013年8月國防工業出版社出版圖書，作者是李思昆。

書籍信息

書名大規模流場科學計算可視化

書號978-7-118-09028-4

作者李思昆等

出版時間2013年8月

譯者

版次1版1次

開本16

裝幀精裝

出版基金國防科技圖書出版基金

頁數356

字數418

中圖分類35

叢書名

定價78.00

圖書目錄

第1章概論1

1.1科學計算可視化的形成與發展1

1.1.1科學計算可視化的形成1

1.1.2科學計算可視化的概念內涵3

1.1.3科學計算可視化的技術發展4

1.2流場數值模擬與流場可視化8

1.2.1流場數值模擬基本原理8

1.2.2流場可視化的流程10

1.2.3流場可視化的特點12

1.2.4數值風洞的流場可視化13

1.2.5虛擬風洞的流場可視化16

1.3流場可視化技術發展與挑戰19

1.3.1流場可視化技術分類19

1.3.2流場可視化面臨的挑戰25

參考文獻27

第2章流場數據對象28

2.1引言28

2.2數據模型28

2.3數據類型30

2.3.1標量數據31

2.3.2矢量數據31

2.3.3張量數據32

2.3.4數據屬性32

2.4數據格式34

2.4.1Tecplot格式34

2.4.2PLOT3D格式37

2.4.3CGNS格式38

2.4.4HDF格式39

2.4.5VTK格式41

2.4.6NetCDF格式43

2.5小結43

參考文獻44

第3章幾何形狀可視化45

3.1引言45

3.2標量場數據可視化45

3.2.1等值線45

3.2.2等值面47

3.2.3大規模數據等值面提取的加速技術50

3.3矢量場數據可視化54

3.3.1幾何圖示55

3.3.2時間序列點56

3.3.3矢量線57

3.3.4矢量線種子點放置方法59

3.3.5大規模數據矢量線生成方法67

3.3.6動態圖元69

3.3.7矢量面72

3.3.8矢量體75

3.4小結76

參考文獻76

第4章紋理可視化78

4.1引言78

4.2經典紋理可視化方法79

4.2.1粒子跟蹤基礎79

4.2.2線積分卷積方法82

4.2.3紋理平流方法88

4.3冷暖光照稀疏紋理繪製92

4.3.1LIC紋理的GPU生成及邊緣檢測93

4.3.2稀疏紋理自適應處理95

4.3.3紋理冷暖光照繪製100

4.4小結106

參考文獻106

第5章體可視化108

5.1引言108

5.2體可視化技術基礎109

5.2.1體可視化基本原理109

5.2.2基於可見性排序的體可視化方法111

5.2.3基於光線投射的體可視化方法115

5.3傳輸函式設計方法118

5.3.1基於數據的傳輸函式設計119

5.3.2基於圖像的傳輸函式設計121

5.4格心格線數據直接體繪製方法123

5.4.1格心格線直接數據重構方法124

5.4.2基於雙控制體的間斷態重構方法127

5.4.3間接繪製方法與直接繪製方法比較128

5.4.4實驗結果130

5.5非結構格線數據體光照方法134

5.5.1光照模型135

5.5.2採樣點梯度計算方法136

5.5.3算法設計與實現139

5.5.4實驗結果140

5.6時變流場體繪製方法142

5.6.1基於時空一致性的時變體繪製算法142

5.6.2時間一致性分析與時間表建立144

5.6.3基於GPU的算法實現145

5.6.4實驗結果147

5.7大規模數據並行體繪製方法149

5.7.1數據劃分149

5.7.2圖像合成150

5.8小結151

參考文獻152

第6章特徵可視化154

6.1引言154

6.2典型特徵提取、跟蹤及事件檢測技術155

6.2.1特徵提取中的基本物理量155

6.2.2渦特徵提取的典型方法156

6.2.3二維/三維流場特徵智慧型特徵提取157

6.2.4基於旋轉熵的渦特徵提取166

6.2.5其他典型特徵提取方法169

6.2.6特徵跟蹤與時間檢測技術170

6.3模糊特徵提取框架172

6.3.1模糊聚類理論基礎173

6.3.2流場特徵模糊描述與自動提取177

6.4流場拓撲分析184

6.4.1拓撲結構分析184

6.4.2拓撲Voronoi圖方法189

6.5拉格朗日擬序結構提取技術202

6.5.1拉格朗日擬序結構的定義203

6.5.2拉格朗日擬序結構提取及可視化算法206

6.5.3拉格朗日擬序結構可視化套用211

6.6小結215

參考文獻215

第7章互動式可視化218

7.1引言218

7.2人機互動基礎218

7.2.1相關互動硬體219

7.2.2WIMP220

7.2.3互動科學221

7.2.4互動的使用222

7.3互動式可視化技術分類223

7.3.1修改類互動223

7.3.2基於選擇的互動224

7.3.3互動式可視分析225

7.3.4其他227

7.4CFD三維流場數據典型特徵互動分析建模與實現230

7.4.1互動式特徵提取和XML230

7.4.2FFDL231

7.4.3互動式模糊特徵提取算法235

7.4.4實驗結果與分析237

7.5基於草圖的互動式可視化240

7.5.1流水線242

7.5.2解釋243

7.5.3接口設計247

7.5.4套用250

7.5.5挑戰與問題251

7.6GPU加速的互動式體繪製方法252

7.6.1ICVE253

7.6.2實驗結果與分析256

7.7小結257

參考文獻257

第8章並行可視化259

8.1引言259

8.2數據組織與劃分260

8.2.1經典標量場數據劃分261

8.2.2經典矢量場數據劃分263

8.2.3柵格劃分的二叉樹區間結點構造算法264

8.3並行繪製與圖像合成271

8.3.1經典並行繪製體系結構與圖像合成271

8.3.2GPGPU加速CPU端無冗餘圖像合成方法276

8.3.3P2P直接通信的GPU端圖像合成及最佳化方法283

8.3.4胖繪製結點間層次式Sortlast並行繪製框架290

8.4線上實時可視化298

8.4.1原位可視化與移位可視化概述299

8.4.2原位特徵提取及跟蹤302

8.4.3原位可視化繪製305

8.4.4原位可視化框架307

8.5小結與展望310

參考文獻311

第9章流場可視化系統314

9.1引言314

9.2典型系統介紹314

9.2.1Tecplot314

9.2.2EnSight317

9.2.3AVS319

9.3天河CFD並行可視化系統320

9.3.1大規模流場可視化套用需求320

9.3.2系統簡介322

9.3.3硬體環境323

9.3.4軟體結構325

9.3.5系統功能329

9.4小結331

參考文獻332

Contents

Chapter 1Introduction1

1.1Brief History of Science Visualization1

1.1.1Birth of Science Visualization1

1.1.2Concept and Meaning3

1.1.3Technique Evolution of Science Visualization4

1.2Fluid Simulation and Visualization8

1.2.1Principle of Fluid Simulation8

1.2.2Procedure of Flow Visualization10

1.2.3Features of Flow Visualization12

1.2.4Visualization in Numeric Wind Tunnel13

1.2.5Visualization in Virtual Wind Tunnel16

1.3Challenges and Opportunities of Flow Visualization19

1.3.1Catalogue and Classification of Flow Visualization19

1.3.2Challenges of Flow Visualization25

References27

Chapter 2Flow Field Data28

2.1Introduction28

2.2Data Model28

2.3Data Type30

2.3.1Scalar Data31

2.3.2Vector Data31

2.3.3Tensor Data32

2.3.4Data Attributions32

2.4Data Format34

2.4.1Tecplot Format34

2.4.2PLOT3D Format37

2.4.3CGNSFormat38

2.4.4HDFFormat39

2.4.5VTKFormat41

2.4.6NetCDFFormat43

2.5Conclusions43

References44

Chapter 3Geometric Visualization45

ⅩⅦ3.1Introduction45

3.2Scalar Data Visualization45

3.2.1Isoline45

3.2.2Isosurface47

3.2.3Isosurface Extraction from Large Scale Datasets50

3.3Vector Data Visualization54

3.3.1Hedgehogs55

3.3.2Time Animation56

3.3.3Intergration Based Line57

3.3.4Seed Placement for Intergration Based Line59

3.3.5Intergration Based Line Generation from Large Scale

Datasets67

3.3.6Dynamic Glyph69

3.3.7Intergration Based Surface72

3.3.8Flow Volume75

3.4Conclusions76

References76

Chapter4TextureBased Visualization78

4.1Introduction78

4.2Classical TextureBased Visualization Methods79

4.2.1Fundamental of Particle Tracing79

4.2.2Line Integral Convolution Method82

4.2.3Texture Advection Method88

4.3CoolWarm IlluminationBased Sparse Texture Rendering92

4.3.1GPU Rendering of LIC Texture and Edge Detection93

4.3.2Adaptive Process of Sparse Texture95

4.3.3CoolWarm IlluminationBased Texture Rendering100

4.4Conclusions106

References106

Chapter 5Volume Visualization108

5.1Introduction108

5.2Basics of Volume Visualization109

5.2.1Foundamental of Volume Visualization109

5.2.2Visibility Sorting Based Volume Visualization111

5.2.3RayCasting Based Volume Visualization115

5.3Transfer Functions118

5.3.1DataDriven Transfer Functions119

5.3.2ImageDriven Transfer Functions121

5.4Direct Volume Visualization for CellCentered Data123

ⅩⅧ5.4.1Direct Reconstruction of CellCentered Data124

5.4.2Discontinuity Reconstruction Based on Double

Control Volumes127

5.4.3Direct Volume Visualization vs Undirect Volume

Visualization128

5.4.4Results130

5.5Volume Illumination for Unstructured Grids134

5.5.1Illumination Model135

5.5.2Gradient Computation for Sample Points136

5.5.3Algorithm139

5.5.4Results140

5.6Volume Visualization for TimeVaring Flow Field142

5.6.1TimeVaring Volume Visualization Based on SpatioTemporal

Coherence142

5.6.2Temporal Coherence Analysis and Temporal Table

Construction144

5.6.3GPUbased Algorithm145

5.6.4Results147

5.7Parallel Volume Visualization for Large Scale Datasets149

5.7.1Data Partition149

5.7.2Image Composition150

5.8Conclusions151

References152

Chapter 6FeatureBased Visualization154

6.1Introduction154

6.2Typical Feature Extraction, Tracing and Event Detection Methods155

6.2.1Basic Physical Quantity in Feature Extraction155

6.2.2Typical Methods for Vortex Feature Extraction 156

6.2.3Intelligent Feature Extraction of 2D/3D Flow Field157

6.2.4Vartex Feature Extraction Based on Rotate Entropy166

6.2.5Other Extraction Methods for Typical Features169

6.2.6Feature Tracing and Event Detection170

6.3Fuzzy Feature Extraction Framework172

ⅩⅨ6.3.1Fundamental of Fuzzy Clustering Theory173

6.3.2Fuzzy Description and Automatic Extraction of Flow

Features177

6.4Topology Analysis of Flow Field184

6.4.1Topology Analysis184

6.4.2Topology Voronoi Graph Method189

6.5Lagrangian Coherent Structure Extraction Techniques202

6.5.1Definition of Lagrangian Coherent Structure203

6.5.2Lagrangian Coherent Structure Extraction and Visualization

Algorithms206

6.5.3Applications of Lagrangian Coherent Structure Visualization211

6.6Conclusions215

References215

Chapter 7Interactive Visualization218

7.1Introduction218

7.2HumanComputer Interaction Foundation218

7.2.1Related Interaction Hardwares219

7.2.2WIMP220

7.2.3Interaction Science221

7.2.4Usage of Interaction222

7.3Categary of Interactive Visualization Methods223

7.3.1ModificationBased Interaction223

7.3.2SelectionBased Interaction224

7.3.3Interactive Visual Analysis225

7.3.4Others227

7.4Interactive Modeling and Implementation of Typical CFD Features230

7.4.1Interactive Feature Extraction and XML230

7.4.2FFDL231

7.4.3Interactive Fuzzy Feature Extraction Algorithm235

7.4.4Results and Analysis237

7.5SketchBased Visualization240

7.5.1Pipeline242

7.5.2Explanation243

7.5.3Interface Design247

7.5.4Applications250

7.5.5Challenges and Problems251

7.6GPUAccelerated Interactive Volume Rendering Method252

7.6.1ICVE253

7.6.2Results and Analysis256

7.7Conclusions257

References257

Chapter 8Parallel Visualization259

ⅩⅩ8.1Introduction259

8.2Data Partition and Distribution260

8.2.1Classical Partition Methods for Scalar Datasets261

8.2.2Classical Partition Methods for Vector Datasets263

8.2.3Lattice Partition Method for Binary Interval Tree Nodes264

8.3Parallel Rendering and Image Compositing271

8.3.1Classical Parallel Rendering Architecture271

8.3.2GPGPUAccelerated CPU Image Composition without

Inactive Pixels276

8.3.3Parallel Image Composition Based on GPU P2P

Communication283

8.3.4Hierarchical Sortlast Parallel Rendering in Fat

Rendering Node290

8.4Realtime Online Visualization298

8.4.1Insitu and Intransit Visualization299

8.4.2Insitu Feature Extraction and Tracking302

8.4.3Insitu Parallel Rendering305

8.4.4Insitu Parallel Frame307

8.5Conclusions and Future Works310

References311

Chapter 9Flow Visualization Systems314

ⅩⅪ9.1Introduction314

9.2Typical Visualization Systems314

9.2.1Tecplot314

9.2.2EnSight317

9.2.3AVS319

9.3TIANHE CFD Parallel Visualization System320

9.3.1Requirements of LargeScale Flow Visualization320

9.3.2System Introduction322

9.3.3Hardware Environment323

9.3.4Software Architecture325

9.3.5System Functions329

9.4Conclusions331

References332