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Results for “crack opening distance”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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8 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Residual Stress Limits Gridline Bridging in Cracked Solar Cells

Cracks in solar cells can be generated in various ways, but this does not mean immediate power loss. Previous studies showed that gridlines bridge cracked silicon cells, and the bridging behavior decreases during the contact and separation of gridlines within bare cells. In this study, we investigate bridging behavior in laminated monocrystalline cells. We characterize the behavior with Weibull analysis of critical crack opening distance (COD), at which the gridline is completely separated. The Weibull analysis of the laminated cell shows a good agreement with bare cells at the first cycle. However, we observe different behavior during cyclic bending. Bare cells show gradual decay of critical COD, while laminated cells show instant decay and plateau. We hypothesize that the difference is due to residual stress, squeezing gridlines, and causing plastic deformation. This is justified by the correlation between critical COD and gridline morphology. In the presentation, we shall present a Weibull analysis of the cyclic bending of a laminated cell with a reduced residual stress effect.

bending↗
DOE OSTI2023

Residual Stresses Affect Cell Fragment Movement

Predictive modeling tools such as the finite element method can be of tremendous help in assessing the reliability and long-term performance of photovoltaic modules. In order to obtain accurate results, the proper modeling of materials and manufacturing processes are of utmost importance. Module fabrication introduces thermo-mechanical stresses inside the module laminate, which need to be accounted for as residual stresses in finite element simulations. We found that cell fragment movement and crack opening displacements of fractured silicon cells within modules are affected by those residual stresses. Cell cracking remains a challenging topic in assessing the reliability and durability of damaged modules. Hence, accurately quantifying the separation and movement between cell fragments creates the foundation for establishing reliable lifetime and performance assessments of fractured silicon modules. Here, we present a modeling approach that uses upper and lower bounds to accurately account for the residual stresses introduced by the module lamination process. We designed a four-point flexure coupon test of a laminated, fractured silicon strip to validate our numerical results and found good agreement between our modeling methodology and the experimental data. Finally, we discuss the implications of the residual stresses on the normal crack opening and metallization wear-out of fractured silicon cells.

14 SOLAR ENERGY↗
DOE OSTI2023

Ribbons Affect Movement of Cracked Solar Cells [Poster]

Cracking of crystalline silicon photovoltaic cells remains a challenging topic in accurately assessing the long-term reliability and performance of affected modules. Cells can be damaged in every stage throughout the lifetime of a photovoltaic module, ranging from manufacturing, transportation, and installation to operation. Initially, the metallization can be able to bridge the gap of fractured cells and keep individual cell fragments electrically connected. However, photovoltaic modules and cells experience thermo-mechanical stresses during operation from temperature changes and pressure cycles of wind and snow loads. This causes the cell fragments to move, which, in turn, can lead to the wear out of the metallization and, consequently, to power loss or a safety hazard. The rate at which this degradation mechanism proceeds is currently unknown. Hence, in this work, we quantify the cell fragment movement of polycrystalline and monocrystalline mini-modules. By using digital image correlation, we were able to extract the normal crack opening and tangential sliding distances of adjacent cell fragments during heating of the mini-modules. Those distances are essential to develop wear-out models for the metallization and determine the rate of the degradation mechanism. We found that the interconnect technology has a significant impact on the direction and quantity of the cell fragment movements.

14 SOLAR ENERGY↗
DOE OSTI2024

Image-Based Digital Twin for Assessing the Coupled Electro-Chemo-Mechanical Behavior of Li-Ion Batteries

In energy storage materials, strong electrochemical-mechanical coupling and highly anisotropic material properties contribute to the formation and propagation of micro-cracking during charge/discharge cycling, resulting in reduced performance and service life. In this work, a digital twin is created to investigate the performance of a Li-ion battery cathode and simulate degradation accumulation. Pixel-based model construction is used to represent the complex material geometries from microstructural images supplied by the National Renewable Energy Laboratory (NREL). Because of the expected large deformation and crack opening, the reproducing kernel particle method (RKPM), a meshfree method with discretization at the image pixels, is used to approximate the field variables: electrostatic potential, concentration, and displacement. An interface modified reproducing kernel (IM-RK) is constructed by scaling a smooth kernel function with an interface-distance function to achieve strategic discontinuity types (i.e. weak discontinuities for strain discontinuities and strong discontinuities for cracks) and alleviate Gibbs oscillations near these transition zones. The discrete nature of the images' pixel points is employed throughout the model and approximation construction. The mechanical model is verified using an image-based microstructure under tensile loading. A transient electro-chemo-mechanical coupled simulation is performed to evaluate the potential micro-cracking induced degradation of the battery cathode material subjected to charge/discharge cycling.

battery degradation↗
DOE OSTI2024

Image-Based Failure Assessment of Li-Ion Batteries

In energy storage materials, strong electrochemical-mechanical coupling and highly anisotropic material properties contribute to the formation and propagation of micro-cracking during charge/discharge cycling, resulting in reduced performance and service life. In this work, a digital twin is created to investigate the performance of a heterogeneous Li-ion battery cathode and simulate degradation accumulation. Pixel-based model construction is used to represent the complex material geometries from microstructural images supplied by the National Renewable Energy Laboratory (NREL). Because of the expected large deformation and crack opening, the reproducing kernel particle method (RKPM), a meshfree method with discretization at the image pixels, is used to approximate the field variables: electrostatic potential, concentration, and displacement. An interface modified reproducing kernel (IM-RK) is constructed by scaling a smooth kernel function with an interface-distance function to achieve strategic discontinuity types (i.e. weak discontinuities for strain discontinuities and strong discontinuities for cracks) and alleviate Gibbs oscillations near these transition zones. Applications to the heterogeneous microstructures of Li-ion battery cathodes will be presented to demonstrate the effectiveness of the proposed methods. IM-RK is additionally used to inform how crack evolution in turn affects the coupled electro-chemo-mechanical behavior of the Li-ion battery cathode.

image-based modeling↗
DOE OSTI2022

Mechanical joint performances of friction self-piercing riveted carbon fiber reinforced polymer and AZ31B Mg alloy

Carbon fiber reinforced polymer (CFRP) and AZ31B Mg alloy were joined by the friction self-piercing riveting (F-SPR) with different steel rivet shank sizes. With the increase of rivet shank size, lap shear fracture load and mechanical interlock distance increased. Ultrafine grains were formed at the joint in AZ31B as a result of dynamic recrystallization, which contributed to the higher hardness. Fatigue life of the CFRP-AZ31B joint was studied at various peak loads of 0.5, 1, 2, and 3 kN and compared with the resistance spot welded AZ31B-AZ31B from the open literature. The fatigue performance was better at higher peak load (>2 kN) and comparable to that of resistance spot welding of AZ31B to AZ31B at lower peak loads (<1 kN). From fractography, the crack initiation for lower peak load (<1 kN) case was observed at the fretting positions on the top and bottom surfaces of AZ31B sheet. When peak load was increased, fretting between the rivet and the top of AZ31B became more dominant to initiate a crack during fatigue testing.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Multiphysics Meshfree Degradation Modeling of Energy Storage Materials with Kernel Enrichment

Energy storage materials exhibit strong electro-chemo-mechanical coupling and highly anisotropic material properties, contributing to the formation and propagation of micro-cracking during charge/discharge cycling and ultimately diminishing performance and service life. With microstructural images supplied by the National Renewable Energy Laboratory (NREL), pixel-based meshfree model construction by the reproducing kernel particle method (RKPM) is used to represent the complex material microstructures that dictate the coupled physics of these systems. Traditional electro-chemo-mechanical models rely on mesh-based finite element methods, which can lead to difficulties in meshing such complex geometries and capturing crack propagation due to mesh dependency. The first kernel enrichment discussed will be the interface modified reproducing kernel (IM-RK) [1, 2], constructed by scaling a smooth kernel function with an interface-distance function to achieve strategic discontinuity types (i.e. weak discontinuities for strain discontinuities and strong discontinuities for cracks) and alleviate Gibbs oscillations near these transition zones. The IM-RK is especially useful for areas in which a known discontinuity-type is expected a priori. The second kernel enrichment to be discussed is a neural network-enhanced reproducing kernel (NN-RK) [3, 4], which is introduced to effectively model non-obvious damage and crack propagation in the material microstructures; the location, orientation, and solution transition near a localization are automatically captured by superimposed block-level NN optimizations. This NN enrichment approach allows for effective modeling of localizations via a fixed background discretization, relieving tedious efforts for adaptive refinement in traditional mesh-based methods. Applications to the heterogeneous microstructures of Li-ion battery cathodes will be presented to demonstrate the effectiveness of the proposed methods. NN-RK is additionally used to inform how crack opening and closure in turn affect the electro-chemo-mechanical responses in the material microstructure. Reference: [1] Wang, Y., Baek, J., Tang, Y. et al. "Support vector machine guided reproducing kernel particle method for image-based modeling of microstructures," Comput Mech 73, 907-942 (2024). https://doi.org/10.1007/s00466-023-02394-9. [2] Susuki, K., Allen, J. & Chen, J. S.. "Image-based modeling of coupled electro-chemo-mechanical behavior of Li-ion battery cathode using an interface-modified reproducing kernel particle method," Engineering with Computers (2024). https://doi.org/10.1007/s00366-024-02016-9. [3] Baek, J., Chen, J. S., Susuki, K., "Neural Network enhanced Reproducing Kernel Particle Method for Modeling Localizations," International Journal for Numerical Methods in Engineering, Vol. 123, 4422-4454 (2022). https://doi.org/10.1002/nme.7040.

25 ENERGY STORAGE↗
DOE OSTI2026

Kernel Enriched Meshfree Multiphysics Degradation Modeling of Energy Storage Materials

Energy storage materials exhibit strong electro-chemo-mechanical coupling and highly anisotropic material properties, contributing to the formation and propagation of micro-cracking during charge/discharge cycling and ultimately diminishing performance and service life. With microstructural images supplied by the National Laboratory of the Rockies (NLR), pixel-based meshfree model construction by the reproducing kernel particle method (RKPM) is used to represent the complex material microstructures that dictate the coupled physics of these systems. Traditional electro-chemo-mechanical models rely on mesh-based finite element methods, which can lead to difficulties in meshing such complex geometries and capturing crack propagation due to mesh dependency. The first kernel enrichment discussed will be the interface modified reproducing kernel (IM-RK) [1, 2], constructed by scaling a smooth kernel function with an interface-distance function to achieve strategic discontinuity types (i.e. weak discontinuities for strain discontinuities and strong discontinuities for cracks) and alleviate Gibbs oscillations near these transition zones. The IM-RK is especially useful for areas in which a known discontinuity-type is expected a priori. The second kernel enrichment to be discussed is a neural network-enhanced reproducing kernel (NN-RK) [3, 4], which is introduced to effectively model non-obvious damage and crack propagation in the material microstructures; the location, orientation, and solution transition near a localization are automatically captured by superimposed block-level NN optimizations. This NN enrichment approach allows for effective modeling of localizations via a fixed background discretization, relieving tedious efforts for adaptive refinement in traditional mesh-based methods. Applications to the heterogeneous microstructures of Li-ion battery cathodes will be presented to demonstrate the effectiveness of the proposed methods. NN-RK is additionally used to inform how crack opening and closure in turn affect the electro-chemo-mechanical responses in the material microstructure. References: [1] Wang, Y., Baek, J., Tang, Y. et al. "Support vector machine guided reproducing kernel particle method for image-based modeling of microstructures," Comput Mech 73, 907-942 (2024). https://doi.org/10.1007/s00466-023-02394-9. [2] Susuki, K., Allen, J. & Chen, J. S.. "Image-based modeling of coupled electro-chemo-mechanical behavior of Li-ion battery cathode using an interface-modified reproducing kernel particle method," Engineering with Computers (2024). https://doi.org/10.1007/s00366-024-02016-9. [3] Baek, J., Chen, J. S., Susuki, K., "Neural Network enhanced Reproducing Kernel Particle Method for Modeling Localizations," International Journal for Numerical Methods in Engineering, Vol. 123, 4422-4454 (2022). https://doi.org/10.1002/nme.7040.

97 MATHEMATICS AND COMPUTING↗