Damage Prognosis : For Aerospace, Civil and Mechanical Systems

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Damage Prognosis : For Aerospace, Civil and Mechanical Systems

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  • 製本 Hardcover:ハードカバー版/ページ数 449 p.
  • 言語 ENG
  • 商品コード 9780470869079
  • DDC分類 624.171

Full Description


Damage prognosis is a natural extension of damage detection and structural health monitoring and is forming a growing part of many businesses. This comprehensive volume presents a series of fundamental topics that define the new area of damage prognosis. Bringing together essential information in each of the basic technologies necessary to perform damage prognosis, it also reflects the highly interdisciplinary nature of the industry through the extensive referencing of each of the component disciplines. Taken from lectures given at the Pan American Advanced Studies Institute in Damage Prognosis sponsored by the US National Science Foundation in cooperation with Los Alamos National Laboratories, this book will be essential reading for anyone looking to get to grips with the fundamentals of damage prognosis. Presents the 'ground rules' for Damage Prognosis. Deals with interdisciplinary topics: rotating machines, aerospace structures, automotive components and civil structures. Covers essential technical material: equations, graphs and plots, tables and photographs. Offers additional material from the associated workshop on an active web site.

Table of Contents

List of Contributors                               xi
Preface xviii
1 An Introduction to Damage Prognosis 1 (12)
C.R. Farrar, N.A.J. Lieven and M.T. Bement
1.1 Introduction 1 (3)
1.2 The Damage-Prognosis Solution Process 4 (4)
1.3 Motivation for Damage-Prognosis 8 (3)
Solutions
1.4 Disciplines Needed to Address Damage 11 (1)
Prognosis
1.5 Summary 11 (1)
References 12 (1)
Part I Damage Models 13 (118)
2 An Overview of Modeling Damage Evolution 15 (46)
in Materials
T.O. Williams and I.J. Beyerlein
2.1 Introduction 15 (2)
2.2 Overview of General Modeling Issues 17 (6)
2.3 Characterization of Material 23 (3)
Behavior: Damage Initiation and
Evolution
2.4 Material Modeling: General 26 (3)
Considerations and Preliminary Concepts
2.5 Classical Damage-Modeling Approaches 29 (6)
2.6 Phenomenological Constitutive 35 (2)
Modeling
2.7 Micromechanical Modeling of 37 (18)
Materials
2.8 Summary 55 (1)
References 56 (5)
3 In Situ Observation of Damage Evolution 61 (14)
and Fracture Toughness Measurement by SEM
J.E.P. Ipi  and A.A. Yawny
3.1 Overview of Fracture Mechanics 61 (3)
Related to Damage Prognosis
3.2 In Situ Observation of Damage 64 (9)
Evolution and Fracture Toughness
Measurement
3.3 Concluding remarks 73 (1)
Acknowledgements 73 (1)
References 73 (2)
4 Predictive Modeling of Crack Propagation 75 (16)
Using the Boundary Element Method
P. Sollero
4.1 Introduction 75 (2)
4.2 Damage and Fracture Mechanics 77 (4)
Theories
4.3 Boundary Element Fracture Mechanics 81 (3)
4.4 Predictive Modeling of Crack 84 (2)
Propagation
4.5 Numerical Results 86 (2)
4.6 Conclusions 88 (1)
Acknowledgments 89 (1)
References 89 (2)
5 On Friction Induced Nonideal Vibrations: 91 (20)
A Source of Fatigue
J.M. Balthazar and B.R. Pontes
5.1 Preliminary Remarks 91 (6)
5.2 Nonlinear Dynamics of Ideal and 97 (6)
Nonideal Stick-Slip Vibrations
5.3 Switching Control for Ideal and 103 (4)
Nonideal Stick-Slip Vibrations
5.4 Some Concluding Remarks 107 (1)
Acknowledgments 108 (1)
References 108 (3)
6 Incorporating and Updating of Damping in 111 (22)
Finite Element Modeling
J.A. Pereira and R.M. Doi
6.1 Introduction 111 (1)
6.2 Theoretical Fundamentals 112 (6)
6.3 Application 118 (10)
6.4 Conclusion 128 (1)
References 128 (3)
Part II Monitoring Algorithms 131 (174)
7 Model-Based Inverse Problems in 133 (44)
Structural Dynamics
V. Steffen Jr and D.A. Rade
7.1 Introduction 133 (1)
7.2 Theory of Discrete Vibrating Systems 134 (5)
7.3 Response Sensitivity 139 (3)
7.4 Finite-Element Model Updating 142 (7)
7.5 Review of Classical Optimization 149 (2)
Techniques
7.6 Heuristic Optimization Methods 151 (4)
7.7 Multicriteria Optimization 155 (1)
7.8 General Optimization Scheme for 156 (1)
Inverse Problems in Engineering
7.9 Applications 157 (16)
Acknowledgments 173 (1)
References 173 (4)
8 Structural Health Monitoring Algorithms 177 (24)
for Smart Structures
V. Lopes Jr and S. da Silva
8.1 Initial Considerations about SHM 177 (2)
8.2 Optimal Placement of Sensors and 179 (7)
Actuators for Smart Structures
8.3 Proposed Methodology 186 (2)
8.4 Artificial Neural Network as a SHM 188 (6)
Algorithm
8.5 Genetic Algorithms as a SHM 194 (3)
Algorithm
8.6 Conclusion 197 (1)
References 198 (3)
9 Uncertainty Quantification and the 201 (20)
Verification and Validation of
Computational Models
F.M. Hemez
9.1 Introduction 201 (1)
9.2 Verification Activities 202 (5)
9.3 Validation Activities 207 (5)
9.4 Uncertainty Quantification 212 (2)
9.5 Assessment of Prediction Accuracy 214 (3)
9.6 Conclusion 217 (1)
References 218 (3)
10 Reliability Methods 221 (14)
A. Robertson and F.M. Hemez
10.1 Introduction 221 (1)
10.2 Reliability Assessment 222 (5)
10.3 Approximation of the Probability 227 (4)
of Failure
10.4 Decision Making 231 (2)
10.5 Summary 233 (1)
References 234 (1)
11 Lamb-Wave Based Structural Health 235 (24)
Monitoring
A. Raghavan and C.E.S. Cesnik
11.1 Introduction 235 (2)
11.2 Fundamentals of Elastic Wave 237 (14)
Propagation
11.3 Application of Lamb-Wave 251 (5)
Formulation to SHM
11.4 Epilogue 256 (1)
References 257 (2)
12 Structural Energy Flow Techniques 259 (16)
J.R. de F. Arruda
12.1 Introduction 259 (1)
12.2 Power and Intensity Concepts 260 (3)
12.3 Experimental Power Flow Techniques 263 (4)
12.4 Spatial Filtering for Fault 267 (1)
Detection
12.5 Acoustical Measurements as a Tool 268 (1)
for Fault Detection
12.6 Detecting Nonlinearity with 269 (1)
Special Excitation Signals
12.7 Frequency Limits of Numerical 270 (2)
Modeling Techniques - The Midfrequency
Problem
References 272 (3)
13 Impedance-Based Structural Health 275 (18)
Monitoring
G. Park and D.J. Inman
13.1 Introduction 275 (1)
13.2 Electro-Mechanical Principle 276 (1)
13.3 Parameters of the Technique 277 (3)
13.4 Comparisons with Other Damage 280 (2)
Identification Approaches
13.5 Proof-of-Concept Applications 282 (1)
13.6 Health Assessment of Pipeline 282 (5)
Structures
13.7 Analysis of a Quarter Scale Bridge 287 (3)
Section
13.8 Summary 290 (1)
References 291 (2)
14 Statistical Pattern Recognition Paradigm 293 (12)
Applied to Defect Detection in Composite
Plates
H. Sohn
14.1 Introduction 293 (1)
14.2 Statistical Pattern Recognition 294 (7)
Paradigm
14.3 Experimental Results 301 (1)
14.4 Summary and Discussion 302 (1)
Acknowledgments 302 (1)
References 302 (3)
Part III Hardware 305 (58)
15 Sensing and Data Acquisition Issues for 307 (16)
Damage Prognosis
C.R. Farrar, P.J. Cornwell, N.F. Hunter
and N.A.J. Lieven
15.1 Introduction 307 (1)
15.2 Sensing and Data Acquisition 308 (2)
Strategies for Damage Prognosis
15.3 Instrumentation: Conceptual 310 (10)
Challenges
15.4 Summary: Sensing and Data 320 (1)
Acquisition
References 321 (2)
16 Design of Active Structural Health 323 (20)
Monitoring Systems for Aircraft and
Spacecraft Structures
F.-K. Chang, J.-B. Ihn and E. Blaise
16.1 Introduction 323 (2)
16.2 Active Sensor Network for 325 (6)
Structural-Health Monitoring Systems
16.3 Diagnostic Software 331 (5)
16.4 Validation of the Active SHM System 336 (3)
16.5 Conclusions 339 (1)
Acknowledgments 340 (1)
References 340 (3)
17 Optical-Based Sensing 343 (20)
M.D. Todd
17.1 Overview and Scope of Chapter 343 (1)
17.2 Basic Optics Concepts 343 (3)
17.3 Primary Fiber Optic Sensing 346 (13)
Approaches for Structural Measurements
17.4 Summary 359 (1)
Acknowledgements 360 (1)
References 360 (3)
Part IV Applications 363 (72)
18 Prognosis Applications and Examples 365 (20)
D.E. Adams
18.1 Introduction 365 (2)
18.2 Applications 367 (15)
18.3 Conclusions 382 (1)
Acknowledgments 382 (1)
References 383 (2)
19 Prognosis of Rotating Machinery Components 385 (36)
M.J. Roemer, G.J. Kacpryznski, R.F.
Orsagh and B.R. Marshall
19.1 Introduction 385 (1)
19.2 Bearing Prognosis Framework 386 (6)
19.3 Model-Based Analysis for Prognosis 392 (9)
19.4 Bearing Prognosis Discussion 401 (1)
19.5 Gear Prognosis Framework 402 (11)
19.6 Bearing and Gear Prognosis Module 413 (1)
Discussion
19.7 Utilization of Prognosis 414 (5)
Information in Navy ICAS System
References 419 (2)
20 Application of Simplified Statistical 421 (14)
Models in Hydro Generating Unit Health
Monitoring
G.C. Brito Jr
20.1 Introduction 421 (2)
20.2 Influences of the Environment and 423 (5)
Operating Conditions in the Behavior of
the Generating Units
20.3 Statistical Models for Structural 428 (4)
Health Monitoring
20.4 Concluding Remarks 432 (1)
20.5 Terminology 432 (1)
References 433 (2)
Index 435