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Kevin R Wheeler

Publications and source records attributed to Kevin R Wheeler.

6 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2024

Finite Element Simulation of the Direct Energy Deposition using Comsol Multiphysics

Direct Energy Deposition (DED) is an emerging technology extensively employed in metal Additive Manufacturing (AM). Despite its widespread industrial application, mathematical modeling in this domain remains challenging. This complexity arises from the intricate nature of the modeling approach and the nonlinear behavior of material parameters across a broad temperature range. Consequently, experimentalists often resort to a trial-and-error method to achieve structures with desired properties. However, this approach can be time-consuming and may not always yield parts with the requisite characteristics, highlighting the necessity for mathematical modeling to enhance manufacturing success. This study focuses on thin-walled manufacturing with a single bead thickness, adjusting laser parameters to produce such structures. The laser cladding speed, typical for DED manufacturing, is considered to be on the order of centimeters per second. The various wall thicknesses and heights are explored to discern the general characteristics of walls manufactured via this DED approach. Our modeling approach diverges from the conventional DED modeling based on activation-deactivation of predefined mesh domains, commonly implemented in many finite element codes. Instead, a method is proposed that effectively models layer cladding and melt pool dynamics, enabling predictions of the microstructure in the resulting structures. The formation mechanisms of cellular, dendritic columnar, and stray (equiaxed) grains, which arise from the interplay between nucleation and growth from the surface is analyzed. The study also examines the feasibility of microstructure formation to demonstrate the various thermal characteristics inherent in wall manufacturing. Our results illustrate how different process parameters influence the temperature gradient and cooling rate of the molten pool, subsequently affecting the primary dendrite arm spacing (PDAS). This modeling technique allows for the investigation of diverse thermal conditions, facilitating the prediction of microstructure and residual stresses in the manufactured parts.

modeling↗
NASA NTRS2021

Analysis of Arc Welding Process in Space

This work is motivated by NASA plans to conduct welding experiments on the ISS. It is expected that deployment of welding and additive manufacturing technologies in the space environment has the potential to revolutionise how orbiting platforms are designed, manufactured, and assembled. However, the structure, composition and quality of a weld is extremely dependent on the environment and can be difficult to control in space. Shielding gases would also be tough to manage as gases behave differently in zero gravity and airless environments. Additional points of concern are related to the spatter and sparks dynamics in space. Therefore, there is a need for a more basic understanding of welding processes by computational modelling. To provide such an insight we developed state of art models of the ARC torch, droplet detachment and transfer, and the melt pool build up using magnetohydrodynamics approximation and level set method for two-phase liquid metal/-gas flow modelling. Two finite element models were built using 2D axisymmetric geometry in COMSOL Multiphysics®: (i) stationary model of the ARC torch and (ii) dynamical model of droplet detachment and transfer. Both models demonstrate reasonable agreement with earlier experimental observations and high sensitivity to the temperature dependence of the thermophysical parameters on the system materials. The models were used to provide physical insight into ARC welding in various environments and geometries. It was shown, in particular, that there is a significant probability of gas bubbles trapping in the meltpool and a possibility of unbounded wondering of sparks in the welding chamber in zero gravity. In addition, we estimated metal evaporation rate that may be hazardous in the confined environment of the ISS. These issues raise concern of quality of the weld and safety for ISS applications.

ARC welding↗
NASA NTRS2021

Analysis of Nonlinear Shrinkage for the Bound Metal Deposition Manufacturing using Multi-scale Approach

We consider problem of nonlinear shrinkage of the metal part during bound metal deposition manufacturing on the ground and in zero-G. To analyze this problem we developed multi-scale physics-based approach that spans atomistic dynamics at the scale of nanoseconds and the full part shrinkage at the time scale of hours. Using this approach we estimated the key parameters of the problem including grain boundary width, coefficient of surface diffusion, initial redistribution of particles during debinding stage, micro-structure evolution from round particles to densely packed grains and corresponding change of the total and chemical free energy, and sintering stress. The introduced method was used to predict shrinkage at the level of two particles, filament cross-section, sub-model, and the whole green, brown, and metal parts. To further improve accuracy and reliability of the shrinkage predictions we propose concept of intelligent additive manufacturing of metal powders in space that combines the strengths of both physics-based and data-driven methods of analysis of AM.

bound metal deposition↗
NASA NTRS2017

Simulation of Guided-Wave Ultrasound Propagation in Composite Laminates: Benchmark Comparisons of Numerical Codes and Experiment

Ultrasonic wave methods constitute the leading physical mechanism for nondestructive evaluation (NDE) and structural health monitoring (SHM) of solid composite materials, such as carbon fiber reinforced polymer (CFRP) laminates. Computational models of ultrasonic wave excitation, propagation, and scattering in CFRP composites can be extremely valuable in designing practicable NDE and SHM hardware, software, and methodologies that accomplish the desired accuracy, reliability, efficiency, and coverage. The development and application of ultrasonic simulation approaches for composite materials is an active area of research in the field of NDE. This paper presents comparisons of guided wave simulations for CFRP composites implemented using four different simulation codes: the commercial finite element modeling (FEM) packages ABAQUS, ANSYS, and COMSOL, and a custom code executing the Elastodynamic Finite Integration Technique (EFIT). Benchmark comparisons are made between the simulation tools and both experimental laser Doppler vibrometry data and theoretical dispersion curves. A pristine and a delamination type case (Teflon insert in the experimental specimen) is studied. A summary is given of the accuracy of simulation results and the respective computational performance of the four different simulation tools.

Composite↗
NASA NTRSDate not supplied

Fast Assessment of Metal Performance through Dislocation Physics and Machine Learning

The microstructure of metals is key to their mechanical properties. The types, density, composition and morphology of crystal defects all have pronounced impact on the properties. Changes to the microstructure occurring during processing and use can be very striking. The emerging technology additive manufacturing (AM) has the potential to improve performance by allowing optimized designs, but the process and environments can lead to unusual microscale features whose properties must be understood and characterized to enable higher technological readiness levels and application. Experimentally, an extensive evaluation of mechanical properties of 3D printed metals is a challenge, and anomalous effects related to the AM process add complexity. We present a new machine learning (ML) model predicting mechanical response based on dislocation mediated plasticity simulations. A large set of 3D discrete dislocation dynamics simulations with wide ranges of loading conditions is transformed to preprocessed data ready for training with the ML model. The trained model can predict the mechanical response of Mo30W for a given microstructure evolution, providing key information essential for optimization of AM processing.

Jaehyun Cho↗