Session: 03-20-02: Space Manufacturing II

Paper Number: 166646

Effect of Ultrasonic Vibration on the Solid-State Processing of Stainless Steel: An Atomic-Scale Analysis of the Fe-Ni-Cr Ternary System 

Stainless steel, particularly Fe-Ni-Cr ternary alloys, is indispensable in high-performance industries such as aerospace and automotive due to its exceptional strength and corrosion resistance. Solid-state manufacturing processes like Additive Friction Stir Deposition (AFSD) and Friction Stir Welding (FSW) rely on optimizing tensile properties to ensure defect-free microstructures. Ultrasonic vibrations, which apply high-frequency (>20 kHz) mechanical oscillations beyond the audible range, are increasingly used to enhance material flow, reduce residual stresses, and improve machining efficiency. However, the atomic-scale mechanisms by which these vibrations influence tensile behavior across varying alloy compositions remain underexplored. This study bridges this gap by combining molecular dynamics (MD) simulations, machine learning (ML), and kinematic parametric analysis to investigate how vibrational frequency and amplitude modulate the mechanical response of multiple Fe-Ni-Cr alloy compositions. The goal is to establish a framework for tailoring ultrasonic parameters and alloy design to enhance solid-state manufacturing outcomes.

The kinematic study of ultrasonic vibration forms the foundation of this work. The high-frequency harmonic excitation generates periodic displacement, velocity, and acceleration. The analytical calculations of kinetic energy from vibration source and energy density highlight how higher frequencies and amplitudes amplify energy transfer into the material. This energy drives atomic rearrangement, reduces axial forces, and enhances strain distribution—critical for processes like ultrasonic vibration-assisted FSW or AFSD. By varying amplitude, frequency, and alloy compositions, the study explores how vibrational energy dissipation influences yield strength, ductility, and ultimate tensile strength (UTS) of the Fe-Ni-Cr alloy at the atomic scale.

Methodologically, MD simulations are conducted using LAMMPS to model multiple Fe-Ni-Cr compositions with defect-free FCC lattice structures. Periodic boundary conditions are used to ensure the lattices behave as bulk materials. The Modified Embedded-Atom Method (MEAM) potential is employed to capture multi-element interactions, with tailored cross-species bonding terms ensuring accuracy. Ultrasonic vibrations are simulated as sinusoidal displacements applied to 20 spatial blocks along the tensile axis, with frequencies (1–100 GHz) and amplitudes (1–5 Å) reflecting industrial AFSD or FSW conditions. Tensile loading is imposed at 0.0001/ps strain rates, coupled with thermal cycling (300–800 K) to mimic thermo-mechanical processing. The ML models, trained on datasets spanning diverse alloy compositions and vibrational parameters, are developed to predict optimal processing conditions, while Ovito is used for visualizing dislocation-free deformation patterns.

Key findings reveal that ultrasonic vibrations and alloy composition synergistically govern tensile behavior. For example, nickel-rich compositions exhibit a 20% increase in ductility under moderate frequencies (30–50 GHz), attributed to enhanced atomic mobility and homogeneous strain distribution. Conversely, chromium-dominant alloys show superior fracture resistance at higher amplitudes (3–4 Å), with delayed void nucleation due to stronger lattice cohesion. Across all compositions, resonant frequency effects at 50 GHz reduce yield strength by 10–25%, while frequencies >75 GHz universally degrade UTS by 25–35% due to chaotic atomic motion. Thermal cycling amplifies dislocation-free plasticity in iron-rich alloys, though UTS peaked at 300 K, consistent with thermally activated grain refinement trends.

Model validation is achieved through comparisons with experimental data and literature benchmarks. ML models show 94% accuracy in replicating stress-strain trends from FSW experiments, confirming the MEAM potential’s reliability.

Future work will expand the compositional parameter space to include adding more alloying elements, defects and dislocations in the model, and integrate MD-derived insights into finite element analysis (FEA) for macro-scale component modeling. ML tools will also be refined for real-time optimization of vibrational parameters in industrial settings, targeting defect reduction and energy efficiency.

In conclusion, this study demonstrates that ultrasonic vibrations and alloy composition jointly dictate the mechanical response of Fe-Ni-Cr systems. By modulating vibrational parameters and compositional ratios, manufacturers can selectively enhance ductility, fracture resistance, or thermal stability. The integration of MD simulations, kinematic analysis, and ML modeling provides a versatile framework for optimizing solid-state manufacturing, bridging atomic-scale mechanisms to industrial applications. These insights pave the way for designing next-generation stainless steel alloys tailored to specific manufacturing challenges, reinforcing their role in high-performance engineering.

Presenting Author: Ahsanul Alam Kabhi Louisiana Tech University

Presenting Author Biography: Ahsanul Alam Kabhi is a Graduate Research Assistant in the Department of Mechanical Engineering at Louisiana Tech University. Their research focuses on additive manufacturing of metals and alloys, utilizing computational modeling, multiscale simulations, and experimental techniques. They have experience in Molecular Dynamics, Finite Element Analysis, Manufacturing, Materials Processing, and Characterization, with two publications in the field.

Authors:

Ahsanul Alam Kabhi Louisiana Tech University
Pouria Nourian Louisiana Tech University
M Shafiqur Rahman Louisiana Tech University