Preface	5
	Contents	7
	Part I Methods	9
	Calculation of Chemical Equilibria in Multi-Phase: Multicomponent Systems	10
	1 Introduction	10
	2 Problem Formulation	12
	2.1 Non-Ideal Gibbs Function	12
	2.2 Stoichiometric Constraints	13
	2.3 The Optimization Problem	15
	3 Methodology for the Calculation of Chemical Equilibria	16
	3.1 Reformulation of the Minimization Problem	17
	3.2 Discretization of the H-Problem	18
	3.3 Corrector Step	19
	4 Automated Detection of Miscibility Gaps	20
	5 Results	23
	5.1 Gibbs Free Energy Minimization Using BePhaSys	23
	5.2 Calculation of Two-Dimensional Phase Diagrams: Interpolation and Parallelization	23
	Appendix: The Gibbs Free Energy Function	29
	References	30
	LC-GAP: Localized Coulomb Descriptors for the Gaussian Approximation Potential	32
	1 Introduction	32
	2 Potential Energy Prediction Through Machine Learning	33
	2.1 The GAP Framework and Gaussian Process Regression	34
	2.2 Localized Coulomb Matrix Descriptors	35
	3 Results	37
	3.1 Comparison of Descriptor Functions on QM7	39
	3.2 Larger Datasets and Prediction of Multiple Properties	41
	3.3 Distribution of Individual Atomic Contributions	44
	4 Conclusions and Future Work	47
	References	48
	River Bed Morphodynamics: Metamodeling, Reliability Analysis, and Visualization in a Virtual Environment	50
	1 Introduction	50
	2 RBF Metamodel	53
	3 Quantile Estimation	55
	3.1 Sensitivity-Based Approach	55
	3.1.1 First-Order Approximation	55
	3.1.2 Second-Order Approximation	55
	3.2 Monte Carlo	56
	3.3 Weighted Monte Carlo	57
	3.4 Quasi-Monte Carlo (QMC)	57
	3.5 Quasi-Random Splines (QRS)	58
	4 Numerical Tests	59
	5 Visualization in Virtual Environment	62
	6 Conclusion	65
	References	65
	Cooling Circuit Simulation I: Modeling	67
	1 Introduction	67
	2 Network	68
	3 Water Pipes	69
	3.1 Continuum Mechanics	69
	3.2 Simplifying Assumptions	70
	3.3 Discretization and Regularization	72
	4 Further Devices	75
	4.1 Resistors and Valves	75
	4.2 Pumps	77
	4.3 Heat Exchangers	79
	5 Element Control	82
	6 Conclusion	84
	References	85
	Part II Products	86
	Algebraic Multigrid: From Academia to Industry	87
	1 Introduction	87
	2 From Geometric to Algebraic Multigrid	89
	3 The Early Phase of Algebraic Multigrid (1982–1987)	91
	3.1 The First Documented AMG Application	92
	3.2 The Basics of `Classical' AMG	93
	4 The Renaissance of AMG (1995–2000)	95
	4.1 Resumption of Major Research on AMG	95
	4.2 Towards Industry	96
	4.2.1 Computational Fluid Dynamics	97
	4.2.2 Streamline Approach in Oil Reservoir Simulation	99
	5 The Main AMG Development Phase (2000–Today)	101
	5.1 The General Trend	101
	5.2 Bridging the Gap	102
	5.3 SAMG for Coupled PDE Systems	105
	5.3.1 Unknown-Based Approach	105
	5.3.2 Point-Based Approach	106
	5.3.3 Status of the Solver Framework SAMG	106
	6 Industry-Driven Applications	107
	6.1 Semiconductor Applications	107
	6.2 Multi-Ion Transport and Reaction	110
	6.3 Oil Reservoir Simulation	111
	6.3.1 The Reservoir Simulation Models	113
	6.3.2 Fully Implicit Methods	114
	7 Summary, Conclusions and Lessons Learned	119
	References	121
	Parallel Algebraic Multigrid	124
	1 Introduction	124
	2 Challenges Imposed by Parallel Computer Architectures	126
	2.1 Single Core Performance: CPU Clock Speed and Memory Frequency	126
	2.2 Multi-Core CPUs and Shared Memory Parallelism	127
	2.2.1 Multi-Core and Memory Access	128
	2.2.2 Intrinsically Serial Components	129
	2.2.3 Race Conditions	129
	2.2.4 Multiple Sockets	130
	2.3 Distributed Memory Parallelism	130
	3 How SAMG Counters the HPC Challenges	131
	3.1 Tuning and Parallelization of Smoothing	132
	3.2 Ruge-Stüben Coarsening	134
	3.3 Coarse Grid Solution	135
	4 SCAI's Parallel SAMG Solver Library	136
	References	137
	MpCCI: Neutral Interfaces for Multiphysics Simulations	138
	1 Introduction	138
	2 MpCCI CouplingEnvironment	139
	2.1 Aero-Elasticity and Fluid-Structure-Interaction	141
	2.1.1 Wing and Spoiler Design	141
	2.1.2 Hydraulic Pump Layout	142
	2.2 Thermal and Vibration Loads in Turbomachinery	143
	2.2.1 Thermal Loads on Ceramic Impeller	143
	2.2.2 Life-Time Estimation of Turbine Blades	144
	2.3 Vehicle Dynamics and Nonlinear Component Behavior	144
	2.3.1 Driving Over Obstacles	144
	2.3.2 Wading Simulation for Off-Road Vehicles	144
	2.4 Automotive Thermal Management	146
	2.4.1 Automotive Thermal Management for Full Vehicles	146
	2.4.2 Automotive Thermal Management for Vehicle Manifolds	146
	2.5 Component Design in Electrical Engineering	147
	2.5.1 Cooling of a 3-Phase Transformer	147
	2.5.2 Electric Arc in Switching Devices	147
	3 MpCCI FSIMapper	148
	4 MpCCI Mapper Solution for Integrated Simulation Workflows	149
	4.1 Passive Safety	150
	4.2 Forming Tools and Material Properties	151
	4.2.1 Lightweight Stamping Tools: Use Forming Loads in Structural Optimization	151
	4.2.2 Validation of Material Model Parameters: Compare Forming Results and Experimental Data	151
	4.3 Composite Structures and Plastic Components	152
	4.3.1 CFRP Workflows: From Draping via Mulling and Curing to Structural Analysis	152
	4.3.2 Structural Integrity of Blow Moulded Plastic Components	153
	5 Conclusion	153
	References	153
	Cooling Circuit Simulation II: A Numerical Example	155
	1 Introduction	155
	2 Application	156
	2.1 Cooling System	156
	2.2 Circuit Basics and Example	156
	3 Concept and Software	163
	3.1 Framework and Components	163
	3.2 Semi-Automatic Model Creation with Schemparser	165
	3.3 Device Modeling and Sensor Mapping	166
	3.4 Collection of Measurement Data with PowerDAM	167
	3.5 Nonlinear Problem Setup and Solution with MYNTS	168
	4 Numerical Tests	170
	4.1 Simplified Heat Exchanger	170
	4.2 Logarithmic Mean Temperature Difference	177
	5 Conclusion	179
	References	181
	The LAMA Approach for Writing Portable Applications on Heterogenous Architectures	183
	1 Introduction	183
	2 LAMA	184
	2.1 Heterogeneous Memory	186
	2.2 Heterogeneous Kernel	188
	2.3 Task Parallelism	188
	2.4 Distributed Memory Support	190
	2.5 Matrices and Vectors	191
	2.6 Solver Framework	191
	2.7 Extensibility and Maintainability	193
	3 Performance Comparison	194
	4 Summary	197
	Appendix	198
	Test Environment	198
	Test Matrices	199
	References	200
	ModelCompare	201
	1 Introduction	201
	2 Development History	202
	3 Capabilities	202
	3.1 Detection of Geometry Changes	203
	3.2 Detection of MultiParts	204
	3.3 Spotwelds and Rigid Body Elements	205
	3.4 Detection of Material-ID and Thickness Changes	206
	4 Outlook	207
	References	207
	Rapid Enriched Simulation Application Development with PUMA	208
	1 Introduction	208
	2 Partition of Unity Methods	209
	3 PUMA Framework Design	210
	4 Application Examples	212
	5 Concluding Remarks	225
	References	226
	Part III Applications and Show Cases	228
	Applying CFD for the Design of an Air-Liquid Interface In-Vitro Testing Method for Inhalable Compounds	229
	1 Introduction	229
	2 In-Vitro Air-Liquid Interface	230
	3 Simulating the Aerosol Conduction System	231
	4 Simulating the Liquid Supply System	237
	4.1 Clogging in Liquid Channels	239
	5 Simulating an Aerosol Sampling Box	240
	6 Conclusions	243
	References	243
	A Mapping Procedure for the Computation of Flow-Induced Vibrations in Turbomachinery	244
	1 Introduction	244
	2 Nonlinear Harmonic Method	245
	3 Mapping of Pressure Excitations	246
	3.1 Periodic Models and Nodal Diameters	248
	3.2 Deriving Excitation and Responding Shape	251
	3.3 Summary	252
	4 Application Example	252
	4.1 Harmonic CFD Simulation	254
	4.2 Mapping	254
	4.3 Harmonic Structural Analysis	257
	5 Conclusion	259
	References	261
	Molecular Dynamics Simulation of Membrane Free Energy Profiles Using Accurate Force Field for Ionic Liquids	263
	1 Introduction	263
	2 Computational Methods	264
	2.1 Simulation Details	264
	2.1.1 Technical Details	264
	2.1.2 Force Field Development for [C2MIM][EtSO4]	265
	2.2 Umbrella Sampling	267
	3 Results and Discussion	269
	3.1 Force Field Development for [C2MIM][EtSO4]	269
	3.1.1 Density	269
	3.1.2 Self-Diffusion Coefficients	270
	3.1.3 Heat of Vaporization	270
	3.1.4 Shear Viscosity	271
	3.2 Free Energy Profiles	271
	4 Outlook and Conclusion	274
	4.1 Outlook: Towards Fully Automated Force Field Development	274
	4.1.1 Case Study: Automated Parameterization of Ethylene Oxide	277
	4.2 Conclusion	279
	References	279
	The cloud4health Project: Secondary Use of Clinical Data with Secure Cloud-Based Text Mining Services	283
	1 Introduction	283
	2 Developing a Secure Cloud-Solution for Medicine	285
	2.1 Existing Cloud Solutions for Medicine	285
	2.2 Requirements for Cloud Infrastructures Arising from Patient Data Processing	287
	2.3 Security Mechanisms	288
	2.4 Secure Cloud Infrastructure	290
	2.4.1 Secure Clinical Gateway to the Cloud	291
	2.4.2 Data Processing Flow	292
	2.4.3 End-to-End Encryption	293
	2.4.4 Multi-Tenancy and No Data Persistence	295
	3 Clinical Text Mining Solutions	297
	3.1 Short Literature Overview	297
	3.2 General Architecture of the Text Mining Services	299
	3.3 Overview Use Cases	301
	3.3.1 General Use Case Process Model	302
	3.4 Mining Endoprosthetic Surgery Reports	303
	3.5 Mining Pathology Reports	306
	4 Discussion	309
	References	311
	Dimensionality Reduction for the Analysis of Time Series Data from Wind Turbines	314
	1 Introduction	314
	2 Time Series Characteristics in Wind Energy	316
	2.1 Numerical Simulations of Wind Turbines	316
	2.2 Condition Monitoring of Wind Turbines	318
	3 Exploration of Time Series Data from Numerical Simulations	319
	3.1 Virtual Sensor Data from Wind Turbine Simulations	319
	3.2 Nonlinear Dimensionality Reduction for Time Series Analysis	321
	3.3 Diffusion Maps	322
	3.4 Numerical Results	323
	4 Anomaly Detection Based on Linear Dimensionality Reduction for Condition Monitoring Sensor Data from Wind Turbines	326
	4.1 Sensor Data from Rotor Blades	326
	4.1.1 Pre-processing	327
	4.2 Anomaly Detection in Sensor Data	329
	4.2.1 Model of Undamaged State	329
	4.2.2 Deviation from the Undamaged State	330
	4.3 Methodology for Damage Detection	331
	4.4 Numerical Results	332
	5 Conclusions	335
	References	335
	Energy-Efficiency and Performance Comparison of Aerosol Optical Depth Retrieval on Distributed Embedded SoC Architectures	337
	1 Introduction	337
	2 Method	338
	3 Implementation	340
	4 Embedded Low-Energy System	342
	5 Benchmarks	344
	5.1 Benchmark Environment	345
	5.2 Performance Benchmarks	345
	5.3 Energy Benchmarks	347
	6 Discussion	353
	7 Outlook	353
	References	354
	Part IV A Short History	355
	The Fraunhofer Institute for Algorithms and ScientificComputing SCAI	356
	1 Foundation of the GMD, the First Decade (1968–1977)	358
	2 Numerical Simulation, Multigrid and Parallel Computing (1978–1991)	359
	3 SCAI: Algorithms and Scientific Computing (1992–2001)	362
	4 SCAI as a Fraunhofer Institute, the First Years (2001–2009)	366
	5 New Fields of Research and New Business Areas (2010–2016)	368
	References	369