UID:
almahu_9949640557802882
Umfang:
1 online resource (481 pages)
Ausgabe:
First edition.
ISBN:
0-443-15426-0
Serie:
Woodhead Publishing Series in Composites Science and Engineering Series
Anmerkung:
Front Cover -- Machine Learning Aided Analysis, Design, and Additive Manufacturing of Functionally Graded Porous Composite Structures -- Copyright Page -- Contents -- List of contributors -- I. Introduction -- 1 An introduction to functionally graded porous materials and composite structures -- 1.1 Porous materials -- 1.2 Functionally graded porous materials -- 1.2.1 Functionally graded porosity -- 1.2.2 Fabrication -- 1.3 Functionally graded porous composite structures -- 1.3.1 Structural forms -- 1.3.2 Mechanical analysis -- 1.4 Chapters in this book -- 1.5 Conclusions -- Acknowledgments -- References -- II. Structural performance evaluation -- 2 Free and forced vibrations of functionally graded porous straight and curved beams -- Nomenclature -- 2.1 Introduction -- 2.2 Materials and methods -- 2.2.1 Model description -- 2.2.2 Energy formulations of functionally graded porous curved beam -- 2.2.3 Model discretization and solution procedure -- 2.3 Result and discussion -- 2.3.1 Convergence study -- 2.3.2 Validation -- 2.3.3 Parameter studies -- 2.4 Conclusion -- Acknowledgments -- References -- 3 Free and forced vibrations of functionally graded porous quadrilateral plates with complex curved edges -- Nomenclature -- 3.1 Introduction -- 3.2 Theory analysis -- 3.2.1 Establishment of the model -- 3.2.2 Constitutive relation and energy equation -- 3.2.3 Spectral Chebyshev method -- 3.2.4 Solving procedure -- 3.3 Results and discussion -- 3.3.1 Free vibration of FGP plates -- 3.3.1.1 Convergence and verification -- 3.3.1.2 Parametric investigation -- 3.3.2 Transient response of FGP plates -- 3.3.2.1 Verification examples -- 3.3.2.2 Parametric investigation -- 3.3.3 Steady-state response of FGP plates -- 3.3.3.1 Verification examples -- 3.3.3.2 Parametric analysis for steady-state response -- 3.4 Conclusion -- Acknowledgments -- References.
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4 Free and forced vibrations of functionally graded porous circular cylindrical shells -- 4.1 Introduction -- 4.2 Linear free vibration -- 4.2.1 Governing equations -- 4.2.2 Solution procedure -- 4.2.3 Results and discussion -- 4.3 Linear forced vibration -- 4.3.1 Governing equations -- 4.3.2 Solution procedure -- 4.3.3 Results and discussion -- 4.4 Nonlinear free vibration -- 4.4.1 Governing equations -- 4.4.2 Solution procedure -- 4.4.3 Results and discussion -- 4.5 Nonlinear forced vibration -- 4.5.1 Governing equations and solution -- 4.5.2 Results and discussion -- 4.6 Conclusion -- Acknowledgments -- References -- 5 Free and forced vibrations of functionally graded porous shallow shells on elastic foundation -- Nomenclature -- 5.1 Introduction -- 5.2 Theoretical formulations -- 5.2.1 Functionally graded porous material properties -- 5.2.2 Description of the shallow shells -- 5.2.3 Energy functional of the functionally graded porous shallow shells -- 5.2.4 Spectral Chebyshev method -- 5.2.5 Solving procedure -- 5.3 Analysis and discussion -- 5.3.1 Convergence studies -- 5.3.2 Validity of the present method -- 5.3.3 Free vibration analysis -- 5.3.4 Forced vibration analysis -- 5.3.4.1 Steady-state response -- 5.3.4.2 Transient-state response -- 5.4 Conclusion -- Acknowledgments -- References -- 6 Improving buckling and vibration response of porous beams using higher order distribution of porosity -- 6.1 Introduction -- 6.2 Porous materials with graded porosities -- 6.3 Governing equations -- 6.3.1 Displacement field -- 6.3.2 Strain-displacement relations -- 6.3.3 Constitutive equations -- 6.3.4 Hamilton principle -- 6.4 Solution methodology -- 6.4.1 Galerkin technique -- 6.4.2 Harmonic balance method -- 6.5 Numerical results and discussions -- 6.5.1 Comparative studies -- 6.5.2 Parametric studies -- 6.6 Conclusions -- Acknowledgments -- Appendix.
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References -- 7 Probabilistic stability analysis of functionally graded graphene reinforced porous beams -- 7.1 Introduction -- 7.2 Material properties of functionally graded graphene reinforced porous beams -- 7.3 Theoretical formulations -- 7.4 Solution methodology and equations -- 7.4.1 Discrete singular convolution algorithm -- 7.4.2 Stability analysis by using discrete singular convolution method -- 7.5 Surrogate model-based stochastic framework -- 7.5.1 Chebyshev metamodel -- 7.6 Results and discussion -- 7.6.1 Validation of deterministic buckling analysis -- 7.6.2 Validation and accuracy of the probabilistic buckling analysis -- 7.6.3 The influence of different porosity types -- 7.6.4 The influence of different graphene platelets distribution pattern -- 7.6.5 The influence of different boundary conditions -- 7.7 Conclusion -- Acknowledgments -- References -- 8 An improved approach for thick functionally graded beams under bending vibratory analysis -- 8.1 Introduction -- 8.2 Theoretical formulation -- 8.2.1 Model definition -- 8.2.2 Displacement and strain fields -- 8.2.3 Calculation of energies -- 8.2.4 Governing equation -- 8.2.5 Analytical solution for a simple supported functionally graded beam (S-S FG beam) -- 8.3 Numerical results and discussion -- 8.3.1 Static analysis -- 8.3.2 Vibration analysis -- Conclusions -- Appendix A -- References -- III. Machine learning aided analysis -- 9 Accelerated design and characterization of nonuniformed cellular architected materials with tunable mechanical properties -- 9.1 Introduction -- 9.2 Materials and methods -- 9.2.1 Basic geometry of material units -- 9.2.2 Numerical simulations -- 9.2.3 Neural network parameters and architecture of machine learning framework -- 9.3 Analysis and prediction results -- 9.3.1 Response classification of 3×3 units.
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9.3.2 Response classification of representative 4×4 units -- 9.3.3 Machine learningmodel validation and response prediction -- 9.4 Conclusion -- Acknowledgments -- References -- 10 Artificial intelligence (AI) enhanced finite element multiscale modeling and structural uncertainty analysis of a functi... -- 10.1 Introduction -- 10.2 AI-enhanced finite element multiscale modeling -- 10.2.1 Representative volume elements for finite element homogenization -- 10.2.2 Database construction -- 10.2.3 Convolutional neural networks -- 10.2.4 Results from convolutional neural network -- 10.3 Structural uncertainty analysis -- 10.3.1 Material uncertainty -- 10.3.2 Bending analysis of FG porous beam -- 10.3.3 Validation and discussion on FG porous beam -- 10.4 Conclusions -- Acknowledgments -- References -- 11 Machine learning-aided stochastic static analysis of functionally graded porous plates -- 11.1 Introduction -- 11.2 Functionally graded porous plates -- 11.3 Theoretical formulation -- 11.3.1 First-order shear deformation theory of plate -- 11.4 Machine learning-aided stochastic static analysis -- 11.4.1 The Karhunen-Loève expansion -- 11.4.2 Machine learning-aided stochastic static analysis of functionally graded porous plate -- 11.4.3 Artificial neural networks -- 11.4.4 The extended support vector regression -- 11.5 Investigation of results -- 11.5.1 Convergence and validation -- 11.5.2 Functionally graded porous cylinder plate example -- 11.5.3 Functionally graded porous spanner plate example -- 11.6 Conclusion -- 11.6.1 Summary and conclusions -- Acknowledgments -- References -- 12 Machine learning aided stochastic free vibration analysis of functionally graded porous plates -- 12.1 Introduction -- 12.2 Material models of the functionally graded porous plates -- 12.3 Stochastic free vibration analysis.
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12.3.1 Free vibration analysis of functionally graded porous plate -- 12.3.2 Stochastic free vibration analysis of functionally graded porous plate -- 12.4 Machine learning aided stochastic free vibration analysis -- 12.4.1 Preliminary -- 12.4.2 Gaussian process regression -- 12.4.3 The extended support vector regression -- 12.4.4 Optimizing hyperparameters -- 12.5 Investigation of results -- 12.5.1 Convergence and validation -- 12.5.2 Functionally graded porous plate example -- 12.5.3 Functionally graded porous drone base example -- 12.6 Conclusion -- Acknowledgments -- References -- IV. Additive manufacturing -- 13 Performance evaluations of functionally graded porous structures -- 13.1 Introduction -- 13.2 Design of functionally graded porous structures -- 13.2.1 Topology design of triply periodic minimal surface -- 13.2.2 From triply periodic minimal surface to lattice structures -- 13.2.3 Triply periodic minimal surface lattice with functionally graded relative density -- 13.3 Manufacturing techniques -- 13.3.1 3D printing of composite materials -- 13.3.2 Additive manufacturing of concrete -- 13.4 Results and discussion -- 13.4.1 Mechanical properties of triply periodic minimal surface composite-based structures -- 13.4.2 Mechanical performance of porous cement and concrete-based structures -- 13.5 Potential applications -- 13.6 Conclusions -- Acknowledgments -- References -- 14 Design and fabrication of additively manufactured functionally graded porous structures -- 14.1 Introduction -- 14.2 Additive manufacturing techniques -- 14.2.1 Powder bed fusion -- 14.2.2 Material extrusion -- 14.2.3 Vat photopolymerization -- 14.3 Additively manufactured cellular solids -- 14.3.1 Open-cell foams -- 14.3.2 Closed-cell foams -- 14.3.3 Honeycomb architectures -- 14.3.4 Lattice architectures -- 14.3.5 Graded cellular solids -- 14.4 Perspective and outlook.
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14.5 Conclusions.
Weitere Ausg.:
Print version: Yang, Jie Machine Learning Aided Analysis, Design, and Additive Manufacturing of Functionally Graded Porous Composite Structures San Diego : Elsevier Science & Technology,c2023 ISBN 9780443154256
Sprache:
Englisch