Engineering PapersSearch

DOE OSTI · 3013803

Reformulating a Gurson-based dynamic damage model and demonstrating improved predictive power and numerical robustness

Abstract

The original Tepla (TEnsile PLAsticity) ductile damage model, based on the Gurson yield surface, has long been used to model damage evolution and material failure under dynamic loading. Unfortunately, Tepla suffered from mesh sensitivity, numerical instability, and limited predictive capability. Here, we theoretically reformulate Tepla to address these issues. We especially focus on the prediction of porosity, which is the key state variable used for modeling ductile damage, as compared to more easily measured surface velocities, which are at best an indirect measure of damage. Key model changes include separating the viscosity during volumetric void growth from underlying shear strength behavior and switching to an iterative bisection solver. The new Tepla is then calibrated on incipient spall experiments on half-hard copper and tantalum, which demonstrate its ability to simultaneously fit the model to recovered porosity distributions and measured surface velocities, a stringent test. Improved numerical behavior, such as greatly reduced mesh sensitivity, is also shown in those simulations. Finally, the new Tepla model is applied to several high-explosive loaded, sweeping wave experiments, showing the ability of the model to predict behavior on tests with significantly different loading conditions and histories than the calibration data.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Nguyen, Thao Thi Tam [Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)] (ORCID:0000000246054341), Luscher, Darby Jon [Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)] (ORCID:0000000329296119), Buechler, Miles Allen [Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)] (ORCID:0000000156354594), Prime, Michael Bruce [Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)] (ORCID:0000000240985620), Fensin, Saryu Jindal [Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)] (ORCID:0000000181355353). 2026-01-16. Reformulating a Gurson-based dynamic damage model and demonstrating improved predictive power and numerical robustness. https://doi.org/10.1016/j.ijsolstr.2026.113833

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related reports

Cyclic moisture reactivation of calcium sorbents for long duration thermochemical energy storage

The transition to a flexible and reliable energy infrastructure, using electro-thermal energy generation technologies such as geothermal, concentrated solar power, and nuclear, usually demands simultaneous advancement of thermal energy storage (TES) to support on-demand electricity generation and industrial applications while mitigating the inherent intermittency of renewable energy sources and power outages from direct energy generation. Among TES technologies, thermochemical energy storage (TCES) based on calcium looping emerges as a compelling high-power energy storage candidate due to its high reaction enthalpy, compatibility with elevated operating temperatures, and abundance of low-cost materials. However, the long-term durability of calcium-based sorbents for TCES is hindered by surface sintering and particle aggregation, leading to performance degradation over repeated thermal cycles. This study explores a moisture hydration-based strategy to regenerate a degraded calcium sorbent and mitigate performance degradation for long duration TCES. The addition of moisture transforms calcium oxide into calcium hydroxide and produces intercalation water layers, associated with a regenerated surface area and reduced calcium oxide crystallite size. Both these effects are beneficial in restoring the sorbents' reactivity for carbonization. Additionally, an optimized hydration-assisted reactivation protocol balances the recovered energy storage capacity with heating penalty required for moisture removal from hydrated samples, resulting in an enhanced energy storage capacity up to 176% compared to benchmark sorbents that undergo cycling without reactivation after 60 cycles. In conclusion, these results highlight the potential of hydration-assisted reactivation to enhance the long-term performance of TCES, providing an effective pathway to advancing electro-thermal storage technologies.

36 MATERIALS SCIENCE