Modeling the Mechanics of Multiaxial Ratcheting
Abstract
Ratcheting is the accumulation of plastic strains due to cyclic loading. This phenomenon is highly non-linear and depends on the load, the load history, and the material. Ratcheting is known to reduce the life and lead to unexpected failure of a wide variety of structures subject to extreme weather, earthquakes, and/or repetitive mechanical or thermal service conditions, including structures that important for national security and military dominance. In this work, we will develop a means to analyze and predict multiaxial ratcheting in ductile metals, which can be leveraged to improve safety, reliability, material waste and efficiency in a many structures and Systems. This fundamental research will be a major step forward in the field, as despite years of research on the topic, predictions made with state-of-the-art models often differ dramatically from experimental findings. We believe that past and current ratcheting predictions have significantly deviated from experimental data because the corresponding constitutive models use empirical constitutive features that work only for specific loading conditions. To improve future predictions, our research objective is to use the principles of continuum mechanics and thermodynamics to investigate the mechanics of ratcheting and derive a rigorous, simple, and accurate constitutive model for ratcheting that is applicable to a wide array of ductile metals and loading conditions. We aim to succeed where others have failed by thinking differently when answering the following fundamental questions: Under repetitive loading causing plastic deformations, which are the changes in the material state at the continuum level, and how can these changes of the material state be modeled in order to successfully simulate ratcheting? These changes in the material state will be expressed by properly defined and evolving internal variables in the model. The largest challenge associated with finding a realistic constitutive model for ratcheting is that any systematic error in a single cycle in the internal variables accumulates over many cycles, so it is imperative that the material state be described with a high degree of accuracy. Ratcheting predictions are most unrealistic when strains accumulate in multiple directions, and the model must not only predict correctly the absolute value of the plastic strain accumulation per cycle, but also the relative magnitudes of the accumulated plastic strain components. The model we will develop will combine, for the first time, bounding surface (BS) plasticity theory with Directional Distortional Hardening (DDH) and novel, advanced kinematic hardening (KH) rules. BS theory should accurately predict the plastic modulus during loading reversals, which will help to accurately predict the absolute size of plastic strain components. DDH should accurately capture the evolving shape of the yield surface and the direction of the plastic strain increment, since according to established theories for polycrystalline metals such plastic strain rate increment is normal to the yield surface at the current stress point on it. The changing location of the yield surface, as determined by the KH rule, affects both the plastic modulus and the direction of the normal to it, hence both the size and the direction of the plastic strain accumulation. Once the new model is developed, we will calibrate and validate the model with experimental data, including new data that we will collect, and implement the model into a finite element code, so that complex geometries and load conditions can be studied. The calibration will help give physical meaning to model parameters. The results of this work will help increase the safety and reliability of metallic structural components used by the Army under normal repetitive loading or extreme loading events, which could potentially reduce weight, minimize cost, and maximize the efficiency of our military equipment and structures.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Feb 14, 2019
- Source ID
- W911NF1910040
Entities
People
- Heidi Feigenbaum
Organizations
- Army Contracting Command
- Northern Arizona University
- United States Army