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Journal Articles
Journal:
Applied Mechanics Reviews
Article Type: Research-Article
Appl. Mech. Rev. May 2024, 76(3): 031001.
Paper No: AMR-22-1071
Published Online: August 2, 2023
Journal Articles
Journal:
Applied Mechanics Reviews
Article Type: Review Articles
Appl. Mech. Rev. May 2024, 76(3): 030801.
Paper No: AMR-22-1066
Published Online: August 2, 2023
Image
in Thermo-Hydro-Chemo-Mechanical (THCM) Continuum Modeling of Subsurface Rocks: A Focus on Thermodynamics-Based Constitutive Models
> Applied Mechanics Reviews
Published Online: August 2, 2023
Fig. 1 A coupled thermo-hydro-chemo-mechanical multiphysics process where each physics affects the other More about this image found in A coupled thermo-hydro-chemo-mechanical multiphysics process where each phy...
Image
in Thermo-Hydro-Chemo-Mechanical (THCM) Continuum Modeling of Subsurface Rocks: A Focus on Thermodynamics-Based Constitutive Models
> Applied Mechanics Reviews
Published Online: August 2, 2023
Fig. 2 A conceptual schematic showing the ( a ) principle of constitutive modeling where thermodynamical consistency can ensure accurate prediction of material behavior and ( b ) an example where the difference between observed and calculated thermodynamic variables (e.g., stress–strain) is minimi... More about this image found in A conceptual schematic showing the ( a ) principle of constitutive modeling...
Image
in Thermo-Hydro-Chemo-Mechanical (THCM) Continuum Modeling of Subsurface Rocks: A Focus on Thermodynamics-Based Constitutive Models
> Applied Mechanics Reviews
Published Online: August 2, 2023
Fig. 3 Schematic explaining the mixture theory of biphasic elements ( s = solid , f = fluid ) in the reference (undeformed) configuration based on a material body of volume B containing a material point P (adapted from Ref. [ 17 ]) More about this image found in Schematic explaining the mixture theory of biphasic elements ( s = s...
Image
in Thermo-Hydro-Chemo-Mechanical (THCM) Continuum Modeling of Subsurface Rocks: A Focus on Thermodynamics-Based Constitutive Models
> Applied Mechanics Reviews
Published Online: August 2, 2023
Fig. 4 The characteristic length of the REV is different at micro- and macroscales [ 195 ] (reproduced with permission) More about this image found in The characteristic length of the REV is different at micro- and macroscales...
Image
in Thermo-Hydro-Chemo-Mechanical (THCM) Continuum Modeling of Subsurface Rocks: A Focus on Thermodynamics-Based Constitutive Models
> Applied Mechanics Reviews
Published Online: August 2, 2023
Fig. 5 A schematic description of various multiphysics dissipative processes in the context of underground hydrogen storage [ 223 ] (reproduced with permission) More about this image found in A schematic description of various multiphysics dissipative processes in th...
Image
Published Online: August 2, 2023
Fig. 1 Representative examples of field observations and experiments involving biological fish. Instantaneous structure of fish schools measured using ( a ) ocean acoustic waveguide remote sensing and ( b ) high-resolution sonar imaging. ( c ) Video tracking of fish groupings in a water tunnel at ... More about this image found in Representative examples of field observations and experiments involving bio...
Image
Published Online: August 2, 2023
Fig. 2 Representative examples of experiments with mechanical fish abstractions. ( a ) A pair of passively flapping filaments arranged in two different spacings in a soap-film tunnel. ( b ) A couple of actively pitching hydrofoils in a water tunnel [ 97 ]. ( c ) Two heaving hydrofoils traveling in... More about this image found in Representative examples of experiments with mechanical fish abstractions. (...
Image
Published Online: August 2, 2023
Fig. 3 Representative examples of reduced-order models. Schools of finite-length vortex dipoles interacting ( a ) freely and ( b ) subject to behavioral rules. ( c ) A pair of zero-thickness heaving plates. ( d ) A lattice of flapping hydrofoils. Subfigures ( a )–( d ) are adapted with permission ... More about this image found in Representative examples of reduced-order models. Schools of finite-length v...
Image
Published Online: August 2, 2023
Fig. 4 Representative examples of high-fidelity CFD simulations. ( a ) Multiple undulating plates driven by their heaving and pitching heads. ( b ) A hydrofoil undergoing prescribed heaving in a periodic domain. ( c ) A generic fish-like swimmer traveling in isolation and in a group. Collective sw... More about this image found in Representative examples of high-fidelity CFD simulations. ( a ) Multiple un...
Image
Published Online: August 2, 2023
Fig. 5 Schematics outlining common formations considered in collective swimming studies. ( a ) and ( b ) depict rectangular and diamond configurations, and their respective derivatives. More about this image found in Schematics outlining common formations considered in collective swimming st...
Journal Articles
Journal:
Applied Mechanics Reviews
Article Type: Research-Article
Appl. Mech. Rev. November 2023, 75(6): 061001.
Paper No: AMR-23-1014
Published Online: July 28, 2023
Image
in Recent Advances and Applications of Machine Learning in Experimental Solid Mechanics: A Review
> Applied Mechanics Reviews
Published Online: July 28, 2023
Fig. 1 Schematics of three ML approaches based on available physics and data: (I) PINNs; (II) physics-based data-driven; and (III) purely data-driven (Reproduced with permission from Ref. [ 62 ]. Copyright 2021 by Hanxun Jin). Figure idea from Karniadakis et al. [ 61 ]. More about this image found in Schematics of three ML approaches based on available physics and data: (I) ...
Image
in Recent Advances and Applications of Machine Learning in Experimental Solid Mechanics: A Review
> Applied Mechanics Reviews
Published Online: July 28, 2023
Fig. 2 Applications of ML in characterizing fracture cohesive properties. ( a ) ML solutions can predict accurate fracture toughness comparable to simulations when an analytical solution is not available due to sample complexity: (i) ML framework for engineering problems; (ii) NNs-based prediction... More about this image found in Applications of ML in characterizing fracture cohesive properties. ( a ) ML...
Image
in Recent Advances and Applications of Machine Learning in Experimental Solid Mechanics: A Review
> Applied Mechanics Reviews
Published Online: July 28, 2023
Fig. 3 Applications of ML in crack/flaw detection. ( a ) PINNs can identify internal voids/inclusions for linear and nonlinear solids: (i) general setup for geometric and material property identification; (ii) architectures of PINNs for continuum solid mechanics. (iii) inference of deformation pat... More about this image found in Applications of ML in crack/flaw detection. ( a ) PINNs can identify intern...
Image
in Recent Advances and Applications of Machine Learning in Experimental Solid Mechanics: A Review
> Applied Mechanics Reviews
Published Online: July 28, 2023
Fig. 4 Applications of ML in constitutive parameter inversion for biomaterials. ( a ) A hybrid DL framework to identify unknown material parameters of arteries with high coefficient of determination: (i) hybrid model architecture; (ii) predicted stress–stretch curves from standard fitting method c... More about this image found in Applications of ML in constitutive parameter inversion for biomaterials. ( ...
Image
in Recent Advances and Applications of Machine Learning in Experimental Solid Mechanics: A Review
> Applied Mechanics Reviews
Published Online: July 28, 2023
Fig. 5 Applications of neural operator in constitutive modeling of biomaterials. ( a ) A DeepONet-based DL framework to infer biomechanical response and associated genotype of tissues: (i) the DL framework; (ii) reconstructed stress–stretch relationships compared with their true values (Reproduced... More about this image found in Applications of neural operator in constitutive modeling of biomaterials. (...
Image
in Recent Advances and Applications of Machine Learning in Experimental Solid Mechanics: A Review
> Applied Mechanics Reviews
Published Online: July 28, 2023
Fig. 6 Applications of ML in nano-indentation. ( a ) DL methods including single-fidelity NNs, multifidelity NNs, and residual multifidelity NNs to identify material parameters from instrumented indentation: (i) architectures of these NNs; (ii) Mean absolute percentage error as a function of train... More about this image found in Applications of ML in nano-indentation. ( a ) DL methods including single-f...
Image
in Recent Advances and Applications of Machine Learning in Experimental Solid Mechanics: A Review
> Applied Mechanics Reviews
Published Online: July 28, 2023
Fig. 7 Applications of ML in designing shape-programmable kirigami metamaterials. ( a ) The ML framework to inverse design kirigami metamaterials. ( b ) Schematics of the tandem network employed for inverse design. ( c ) Experimental verification of inverse design from shadow Moiré method (Reprodu... More about this image found in Applications of ML in designing shape-programmable kirigami metamaterials. ...
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