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Advanced Intelligent Design of Structures: Fatigue and Reliability in Engineering Applications

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19 diapositives · 364 Views · Aug 22, 2014

This paper presents a comprehensive approach to the design of structures focusing on fatigue and reliability. Employing the Advanced Intelligent Design of Structures (A.I.D.S.) methodology, it addresses complex loadings through deterministic and probabilistic frameworks. It includes the development of the ZAK framework, which utilizes a quasi-local approach for multi-scale analysis, with an emphasis on identifying microscopic mechanisms and optimizing fatigue design rules. The study highlights the integration of Monte Carlo methods and numerical simulations, offering practical insights for engineering applications in mechanical structures.

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Transcription de la présentation
  1. 26/11/2003 Habib Karaouni 1Joseph Zarka 2 Intelligent Optimal Design in Fatigue and Reliability 1) CADLM 2) LMS at Ecole Polytechique

  2. CADLM Airways Motivations Errors Numerical simulations Geometry Mechanical Prop. Loadings Fatigue Failure? ? Initial State Complex Loadings

  3. Objectives Complex Loadings Deterministic 1 ZAK-Det Equivalence rule Quasi-Local Approach  A.I.D.S. (J. Zarka) ZAK Advanced Intelligent Design of Structures 3  2 ZAK-Fi ZAK-Alea With random conditions Reliability Monte Carlo

  4. Plan • A.I.D.S. Approach • Equivalence Rule II.1. Radial loadings II.2. Non-Radial loadings II.3. Identification of the microscopical mechanisms • ZAK Approach III.1. Principles III.2. Use of the A.I.D.S. Approach III.3. Generation of the Fatigue Design Rules • Perspectives Contents

  5. I. A.I.D.S. Approach Advanced Intelligent Design of Structures Principles of Automating Learning Learning Base RULES + Reliabily LB DB Test Base TB Production Base PD New cases

  6. I. A.I.D.S. Approach Advanced Intelligent Design of Structures Primitive Description Example Conclusion

  7. I. A.I.D.S. Approach Advanced Intelligent Design of Structures With actual whole knowledge Simplified analytical models Simplified analysis Complex beautiful theories A.I.D.S. Knowledge Primitive Description Intelligent Description Rules Cj = gj(Di) Optimization Experiences and Numerical simulations

  8. II. Equivalence rule relative to fatigue damage Hypothesis 1- Two independant scales : a- Macroscopic Elastic-shakedown at the scale of the structure b- Microscopic Plastic-shakedown on some microscopic mechanisms Yield Stress  Endurance Limit Damage = pc ouWD Crack Initiation  Critical Damage 2- Global simplified Analysis  ZAC (Zarka/Casier)

  9. Loading 1 Loading 2  WD1; WD2; or WD1 = WD2  II. Equivalence rule relative to fatigue damage II.1. Radial Loadings Fluctuation max Cf = (max + min)/2 F = (max - min)/2 min « Measure » of the loading LOCALCumulated plastic strain pc LOCALDissipated Energy WD

  10. II. Equivalence rule relative to fatigue damage II.1. Radial Loadings Particular Loadings  a = F m = Cf N

  11. II. Equivalence rule relative to fatigue damage II.2. Non Radial Loadings Same Equivalence Rule  Radial Cyclic Loading in the direction  Loading Plastic Strain

  12. II. Equivalence rule relative to fatigue damage II.3. Identification of the microscopical mechanisms 1 F. block - 1D 1 F. block - 2D 2 Friction block - 2D

  13. 5) Region/material III. ZAK : Quasi-Local framework III.1. Principle : Multi-scale Analysis 3) 2D Détail 1) Elastic Analysis 2) 3D Sub-Structure A.I.D.S. 4) Window + Radial Cyclic Loading

  14. Classes Conclusions III. ZAK : Quasi-Local framework III.2. Use of the A.I.D.S. Approach • Synthesis of the loadings  Equivalence Rule • Synthesis of the material (cyclic and Fatigue) • Synthesis of the geometries  Analysis within the 2D region I1, J2 ,||grad J2|| , DVK, Ns-n , pc Material Descriptors Stress Field/Fatigue Descriptors - 13 Material desc. - 72 Stress Field desc. - 9 Fatigue desc. - 4 size of region - 2 kind of analysis - 36 details - 12 regions per detail Given Analysis Given size region

  15. MAXt MOYt MINt Layer 5 M Mmax Layer 4 Layer 3 Mmin Layer 2 Layer 1 III. ZAK : Quasi-Local framework III.2. Use of the A.I.D.S. Approach M I1, J2 ,||grad J2|| , DVK, Ns-n , pc  Average of M within  (Mmoy) Maximum of M within  (Mmax) Minimum of M within  (Mmin)  Region  (MlayN) = SN / S0

  16. III. ZAK : Quasi-Local framework III.3. Generation of the Fatigue Design Rules Failure or No Failure If Failure => Number of cycles Software : SEA and NeuroShell Best results : Elastic analysis + region size = .8 mm

  17. IV. Conclusions & Perspectives Experimental Validation of the E.R. Increase the Data Base • more materials • more details and kind of loadings  INDUSTRIAL QUALIFICATION OF THE FRAMEWORK Integration of the ZAK framework in FatPro

  18. Loadings • Cyclics • Variable Amplitudes • Random • Multiaxial FatPro Finite Element Analysis • NISA • CADSAP/ALGOR • ABAQUS • CASTEM Fatigue failure models and criteria • Stress Life • Strain Life • Dang Van • Papadopoulos • ZAK Life • Decreasing of Errors linked to the mesh • Equivalent Rule Demo

  19. Thank You!