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At least 55 records · Page 3

Analyses of internal structures and defects in materials using physics-informed neural networks

Characterizing internal structures and defects in materials is a challenging task, often requiring solutions to inverse problems with unknown topology, geometry, material properties, and nonlinear deformation. Here, we present a general framework based on physics-informed neural networks for identifying unknown geometric and material parameters. By using a mesh-free method, we parameterize the geometry of the material using a differentiable and trainable method that can identify multiple structural features. We validate this approach for materials with internal voids/inclusions using constitutive models that encompass the spectrum of linear elasticity, hyperelasticity, and plasticity. We predict the size, shape, and location of the internal void/inclusion as well as the elastic modulus of the inclusion. Our general framework can be applied to other inverse problems in different applications that involve unknown material properties and highly deformable geometries, targeting material characterization, quality assurance, and structural design.

36 MATERIALS SCIENCE↗

On the development of explicit robust schemes for implementation of a class of hyperelastic models in large-strain analysis of rubbers

The issue of developing effective and robust schemes to implement a class of the Ogden-type hyperelastic constitutive models, for large-strain analysis of rubber-like materials, is addressed. To this end, explicit forms for the corresponding material tangent-stiffness tensors are developed, and these are valid for the entire deformation range; i.e., with both distinct as well as repeated principal-stretch values. Throughout the analysis the various implications of the underlying property of separability of the strain-energy functions are exploited, thus leading to compact final forms of the tensor expressions. In particular, this facilitated the treatment of the complex cases of uncoupled volumetric/deviatoric formulations for incompressible materials, which are becoming increasingly popular in recent years. The forms derived are also amenable for use with symbolic-manipulation packages for systematic code generation.

Saleeb, A. F.↗

Hexagonal Distributed Embedded Energy Converter (HexDEEC)

Hexagonal Distributed Embedded Energy Converters are relatively small, centimeter scale, energy transducers that leverage variable capacitance to generate electricity when their hyperelastic structure is dynamically deformed. A multitude of HexDEECs can be woven to form construction materials that can be used to build complete energy conversion structures, such as ocean wave energy converters.

BFSF↗

Explicit robust schemes for implementation of a class of principal value-based constitutive models: Theoretical development

The issue of developing effective and robust schemes to implement a class of the Ogden-type hyperelastic constitutive models is addressed. To this end, explicit forms for the corresponding material tangent stiffness tensors are developed, and these are valid for the entire deformation range; i.e., with both distinct as well as repeated principal-stretch values. Throughout the analysis the various implications of the underlying property of separability of the strain-energy functions are exploited, thus leading to compact final forms of the tensor expressions. In particular, this facilitated the treatment of complex cases of uncoupled volumetric/deviatoric formulations for incompressible materials. The forms derived are also amenable for use with symbolic-manipulation packages for systematic code generation.

Saleeb, A. F.↗

Hexagonal Distributed Embedded Energy Converters (HexDEECs)

Distributed Embedded Energy Converter Technologies (DEEC-Tec) is a new domain for marine renewable energy research that utilizes a conglomeration of small distributed embedded energy converters (DEECs) that, in aggregate, form larger metamaterial frameworks. These resulting DEEC-Tec metamaterials can then, in turn, be used to construct flexible ocean wave energy converters called flexWECs. DEEC-Tec enables flexWECs: (i) to be inherently broad-banded ocean wave frequency energy converters and (ii) to have an inherent lack of highly loaded rigid bodies. The DEEC-Tec domain also benefits the marine renewable energy domain by inherently availing ways that marine energy can be harvested and converted that heretofore has not yet been considered possible: real-time execution of transforming topologies (e.g., actively changing a flexWEC's shape and form) and morphologies (e.g., actively changing a flexWEC's stiffness and damping throughout its entire structure). Presented, is one specific type of DEEC, a HexDEEC, that shows promise in aiding the adoption and further development of the DEEC-Tec domain - it is a small energy transducer being developed by the United States National Renewable Energy Laboratory. The HexDEEC is a small (characteristic length approximating a centimeter) energy transducer that converts the dynamic deformations of an elastomer into electricity through a charging-discharging cycle of a capacitor whose capacitance is varied by those elastic deformations. The HexDEEC is composed of a hyperelastic hexagonal housing (nominally silicon rubber) with six electrodes on its inner faces. The upper three electrodes share the same charge while the lower three electrodes oppose the upper electrode charges. Externally, the HexDEEC has two arms extending away from the middle vertices of the hexagon. Via principles governing the relationship between electrical capacitance and electrical potential (voltage and charge), electricity is generated when the HexDEEC's arms are dynamically pulled or released under tensile loading as doing so causes the distance between the upper and lower sets of electrodes to change - varying the energy converter's overall capacitance. Analytical and numerical modeling have already been used to estimate the electrical energy produced by a HexDEEC. The cursory models approximate the HexDEEC as a parallel plate variable capacitor - simplifying from six to two opposing plates with a constant dielectric volume between those two plates. To account for the elastic HexDEEC material properties, software such as SolidWorks and STAR-CCM+ have been used to generate hyperelastic models; notably, Mooney-Rivlin based models. Individual HexDEECs have been fabricated by drawing uncured liquid silicon rubber into molds via vacuum pressure. To simplify manufacturing, HexDEEC sub-components - e.g., electrodes, wires - can be placed within those molds such that they are directly embedded into the hexagonal housing during the curing process. Furthermore, DEEC-Tec metamaterials can be created by interweaving or sequentially layering multiple HexDEEC strands together. The HexDEEC based metamaterial could then generate electricity through its gross deformations. Ultimately, HexDEECs represent a specific type of energy transducer that can be leveraged, by the DEEC-Tec domain, to create metamaterials used to construct novel flexWECs.

DEEC-Tec↗

Explicit robust schemes for implementation of general principal value-based constitutive models

The issue of developing effective and robust schemes to implement general hyperelastic constitutive models is addressed. To this end, special purpose functions are used to symbolically derive, evaluate, and automatically generate the associated FORTRAN code for the explicit forms of the corresponding stress function and material tangent stiffness tensors. These explicit forms are valid for the entire deformation range. The analytical form of these explicit expressions is given here for the case in which the strain-energy potential is taken as a nonseparable polynomial function of the principle stretches.

Arnold, S. M.↗

Explicit robust schemes for implementation of a class of principal value-based constitutive models: Symbolic and numeric implementation

The issue of developing effective and robust schemes to implement a class of the Ogden-type hyperelastic constitutive models is addressed. To this end, special purpose functions (running under MACSYMA) are developed for the symbolic derivation, evaluation, and automatic FORTRAN code generation of explicit expressions for the corresponding stress function and material tangent stiffness tensors. These explicit forms are valid over the entire deformation range, since the singularities resulting from repeated principal-stretch values have been theoretically removed. The required computational algorithms are outlined, and the resulting FORTRAN computer code is presented.

Arnold, S. M.↗

Physics augmented machine learning discovery of composition-dependent constitutive laws for 3D printed digital materials

Multi-material 3D printing, particularly through polymer jetting, enables the fabrication of digital materials by mixing distinct photopolymers at the micron scale within a single build to create a composite with tunable mechanical properties. Here, this work presents an integrated experimental and computational investigation into the composition-dependent mechanical behavior of 3D printed digital materials. We experimentally characterize five formulations, combining soft and rigid UV-cured polymers under uniaxial tension and torsion across three strain and twist rates. The results reveal nonlinear and rate-dependent responses that strongly depend on composition. To model this behavior, we develop a physics-augmented neural network (PANN) that combines a partially input convex neural network (pICNN) for learning the composition-dependent hyperelastic strain energy function with a quasi-linear viscoelastic (QLV) formulation for time-dependent response. The pICNN ensures convexity with respect to strain invariants while allowing non-convex dependence on composition. To enhance interpretability, we apply $L_0$ sparsification. For the time-dependent response, we introduce a multilayer perceptron (MLP) to predict viscoelastic relaxation parameters from composition. The proposed model accurately captures the nonlinear, rate-dependent behavior of 3D printed digital materials in both uniaxial tension and torsion, achieving high predictive accuracy for interpolated material compositions. This approach provides a scalable framework for automated, composition-aware constitutive model discovery for multi-material 3D printing.

Constitutive modeling↗

Inelastic equation of state for solids

In this study, a complete inelastic equation of state (IEOS) for solids is developed based on a superposition of thermodynamic energy potentials. The IEOS allows for a tensorial stress state by including an isochoric hyperelastic Helmholtz potential in addition to the zero-kelvin isotherm and lattice vibration energy contributions. Inelasticity is introduced through the nonlinear equations of finite strain plasticity which utilize the temperature dependent Johnson–Cook yield model. Material failure is incorporated into the model by a coupling of the damage history variable to the energy potentials. The numerical evaluation of the IEOS requires a nonlinear solution of stress, temperature and history variables associated with elastic trial states for stress and temperature. The model is implemented into the ALEGRA shock and multi-physics code and the applications presented include single element deformation paths, the Taylor anvil problem and an energetically driven thermo-mechanical problem.

42 ENGINEERING↗

The Role of Unit-Cell Topology in Modulating the Compaction Response of Additively Manufactured Cellular Materials using Simulations and Validation Experiments

Additive manufacturing has enabled a transformational ability to create cellular structures (or foams) with tailored topology. Compared to their monolithic polymer counterparts, cellular structures are potentially suitable for systems requiring materials with high specific energy-absorbing capability to provide enhanced damping. In this work, we demonstrate the utility of controlling unit-cell topology with the intent of obtaining a desired stress–strain response and energy density. Using mesoscale simulations that resolve the unit-cell sub-structures, we validate the role of unit-cell topology in selectively activating a buckling mode and thereby modulating the characteristic stress–strain response. Simulations incorporate a linear viscoelastic constitutive model and a hyperelastic model for simulating large deformation of the polymer under both tension and compression. Simulated results for nine different cellular structures are compared with experimental data to gain insights into three different modes of buckling and the corresponding stress–strain response.

36 MATERIALS SCIENCE↗

The role of unit cell topology in modulating the compaction response of additively manufactured cellular materials using simulations and validation experiments

Additive manufacturing has enabled a transformational ability to create cellular structures (or foams) with tailored topology. Compared to their monolithic polymer counterparts, cellular structures are potentially suitable for systems requiring materials with high specific energy-absorbing capability to provide enhanced damping. In this work, we demonstrate the utility of controlling unit-cell topology with the intent of obtaining a desired stress–strain response and energy density. Using mesoscale simulations that resolve the unit-cell sub-structures, we validate the role of unit-cell topology in selectively activating a buckling mode and thereby modulating the characteristic stress–strain response. Simulations incorporate a linear viscoelastic constitutive model and a hyperelastic model for simulating large deformation of the polymer under both tension and compression. Simulated results for nine different cellular structures are compared with experimental data to gain insights into three different modes of buckling and the corresponding stress–strain response.

36 MATERIALS SCIENCE↗

Characteristics of Fluid‐Solid Interaction Constitutive Models Within Poroelastodynamics at Higher Strain‐Rates and Large Deformations Implemented in 1D

The large deformation, mixed formulation, finite element (FE) modeling approach presented in Irwin et al. 2024 is extended herein to include improved constitutive models for representing dynamic solid-fluid interactions at higher strain rates (𝒪⁢(1⁢0 2 −1⁢0 3 )⁢s −1 ) and larger overpressure magnitudes (𝒪⁡(1⁢0 2 )⁢kPa) within a biphasic soft porous material using Theory of Porous Media (TPM) at finite strain. Specifically, these constitutive modeling improvements are the following: (i) a more physically robust constitutive model for pore fluid seepage velocity via inclusion of pore fluid viscous stress, and (ii) a modified deformation-dependent-permeability model and updated hyperelastic constitutive model better suited for handling larger volumetric compressions and extensions. The novelty of the present work is mainly the contribution (i): inclusion of pore fluid viscous stress at higher strain-rate and large deformations, which requires 𝐶 1 continuity in the weak formulation, accomplished by employing Hermite cubic interpolation functions within a mixed nonlinear poromechanical finite element formulation. In (ii), the model is updated to weakly enforce solid phase incompressibility, such that this assumption is not violated numerically, which provides improved numerical stability for achieving larger overpressure magnitudes on 𝒪⁡(1⁢0 2 ) kPa, which were not achievable with the previous Kozeny–Carman model in Irwin et al. 2024. Also in (ii), the volumetric part of the solid skeleton free energy function is modified to ensure proper bounds on the solid skeleton Jacobian of deformation 𝐽 s related to incompressibility of the solid phase. Uniaxial strain, unidirectional flow examples at higher strain rates (𝒪⁢(1⁢0 2 −1⁢0 3 )⁢s −1 ) and larger deformations (up to 0.2 (or 20%) nominal axial strain) demonstrate the improved physical representation—and numerical stability—of these constitutive model improvements.

42 ENGINEERING↗

Thermo-acoustoelastic effect of Rayleigh wave: Theory and experimental verification

Previous studies showed that the thermally-induced ultrasonic bulk wave velocity change could be used to measure acoustoelastic coefficients and third-order elastic constants of elastic materials. This method is naturally immune from the ambient temperature effect and has improved sensitivity and a simpler test setup than the conventional acoustoelastic test. However, Rayleigh wave is preferred for thick components or structures with only one accessible surface. In this work, the thermo-hyperelastic constitutive equation, along with acoustoelastic theory, is used to derive the expression of the thermo-acoustoelastic coefficient (TAEC) of Rayleigh wave. The numerical relationship between the TAEC of Rayleigh wave and Murnaghan constants ( l, m and n ) are given for common metals. Further, the TAEC expressions for Rayleigh wave and shear wave are similar, and both are dominated by the constant m . The TAEC of Rayleigh wave was measured on an aluminum 6061 specimen using the thermal modulation experiment in a temperature range of 22 ~ 35°C. The measured TAEC shows good agreement with the theoretical calculation. Then the third-order elastic constants were calculated based on TAECs of bulk waves and Rayleigh wave.

42 ENGINEERING↗

Constitutive Model of Radiation Aging Effects in Filled Silicone Elastomers under Strain

Filled silicone elastomers, an essential component in many technological applications, are often subjected to controlled or unintended radiation for a variety of reasons. Radiation exposure can lead to permanent mechanical and structural changes in the material, which is manifested as altered mechanical response, and in some cases, a permanent set. For unfilled elastomers, network theories developed and refined over decades can explain these effects in terms of chain-scission and cross-link formation and a hypothesis involving independent networks formed at different strain levels of the material. In this work, we expose a filled silicone rubber to gamma radiation while being under finite elongational strain and show that the observed mechanical and structural changes can be quantitatively modeled within the same theoretical framework developed for unfilled elastomers as long as nuances associated with the Mullins effect are accounted for in a consistent manner. In this work, we employ Ogden’s incompressible hyperelastic model within the framework of Tobolsky’s two-network scheme to describe the observed permanent set and mechanical modulus changes as a function of radiation dosage. In the process, we conclude that gamma radiation induces both direct cross-linking at chain crossings (H-links) and main-chain-scission followed by cross-linking (Y-links). We provide an estimate of the ratio of chain-scission to cross-linking rates, which is in reasonable agreement with previous experimental estimate from Charlesby–Pinner analysis. We use density functional theory (DFT)-based quantum mechanical calculations to explore the stability of –Si and –SiO radicals that form upon a radiation-induced chain-scission event, which sheds light on the relative rates of Y-linking and H-linking processes.

36 MATERIALS SCIENCE↗

Learning constitutive relations using symmetric positive definite neural networks

In this work, we present a new neural-network architecture, called the Cholesky-factored symmetric positive definite neural network (SPD-NN), for modeling constitutive relations in computational mechanics. Instead of directly predicting the stress of the material, the SPD-NN trains a neural network to predict the Cholesky factor of the tangent stiffness matrix, based on which the stress is calculated in incremental form. As a result of this special structure, SPD-NN weakly imposes convexity on the strain energy function, satisfies the second order work criterion (Hill's criterion) and time consistency for path-dependent materials, and therefore improves numerical stability, especially when the SPD-NN is used in finite element simulations. Depending on the types of available data, we propose two training methods, namely direct training for strain and stress pairs and indirect training for loads and displacement pairs. We demonstrate the effectiveness of SPD-NN on hyperelastic, elasto-plastic, and multiscale fiber-reinforced plate problems from solid mechanics. The generality and robustness of SPD-NN make it a promising tool for a wide range of constitutive modeling applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Toward Standardized Microscale Tensile Testing for Two‐Photon Polymerization‐Fabricated Materials in Liquid

Two-photon polymerization (TPP) enables the fabrication of intricate 3D microstructures with submicron precision, offering significant potential in biomedical applications like tissue engineering. In such applications, to print materials and structures with defined mechanics, it is crucial to understand how TPP printing parameters impact the material properties in a physiologically relevant liquid environment. Herein, an experimental approach utilizing microscale tensile testing (μTT) for the systematic measurement of TPP-fabricated microfibers submerged in liquid as a function of printing parameters is introduced. Using a diurethane dimethacrylate-based resin, the influence of printing parameters on microfiber geometry is first explored, demonstrating cross-sectional areas ranging from 1 to 36 μm 2 . Tensile testing reveals Young's moduli between 0.5 and 1.5 GPa and yield strengths from 10 to 60 MPa. The experimental data show an excellent fit with the Ogden hyperelastic polymer model, which enables a detailed analysis of how variations in writing speed, laser power, and printing path influence the mechanical properties of TPP microfibers. The μTT method is also showcased for evaluating multiple commercial resins and for performing cyclic loading experiments. Collectively, this study builds a foundation toward a standardized microscale tensile testing framework to characterize the mechanical properties of TPP printed structures.

mechanical characterization↗

Morphology and Dynamics of Bottlebrush Polymers

This thesis makes significant advances to the understanding of bottlebrush polymers. While bottlebrushes have received much attention due to the recent discovery of their unprecedented properties, including supersoftness, ultra-low viscosity, and hyperelasticity, this thesis is the first fundamental investigation at the molecular level that comprises structure and dynamics. Neutron scattering experiments, detailed within, reveal spherical or cylindrical shapes, instead of a random coil conformation. Another highlight is the analysis of the fast dynamics at the sub nm-length scale. The combination of three neutron spectrometers and the development of a new analysis technique enabled the calculation of the mean-square displacement over seven orders of magnitude in time scale. This unprecedented result can be applied to a broad class of samples, including polymers and other materials. The thesis is accessible to scientists from other fields, provides the reader with easily understandable guidelines for applying this analysis to other materials, and has the potential to make a significant impact on the analysis of neutron scattering data.

36 MATERIALS SCIENCE↗