29 May 2024

Mesoscale Multiphysics Simulations of the Fused Deposition Additive Manufacturing Process

Abstract: As part of an ongoing effort to better understand the multiscale effects of fused deposition additive manufacturing, this work centers on a multiphysics, mesoscale approach for the simulation of the extrusion and solidification processes associated with fused deposition modeling. Restricting the work to a single line scan, we focus on the application of polylactic acid. In addition to heat, momentum, and mass transfer, the solid-liquid–vapor interface is simulated using a front-tracking, level-set method. The results focus on the evolving temperature, viscosity, and volume fraction and are cast within a set of parametric studies to include the nozzle and extrusion velocities as well as the extrusion temperature. Among other findings, it was observed that fused deposition modeling can be effectively modeled using a front-tracking method (i.e., the level-set method) in concert with a moving mesh and temperature-dependent porosity function.

28 Mar 2023

Exploration of Two Polymer Nanocomposite Structure-Property Relationships Facilitated by Molecular Dynamics Simulation and Multiscale Modeling

Abstract: Polyamide 6 (PA6) is a semi-crystalline thermoplastic used in many engineering applications due to good strength, stiffness, mechanical damping, wear/abrasion resistance, and excellent performance-to-cost ratio. In this report, two structure-property relationships were explored. First, carbon nanotubes (CNT) and graphene (G) were used as reinforcement molecules in simulated and experimentally prepared PA6 matrices to improve the overall mechanical properties. Molecular dynamics (MD) simulations with INTERFACE and reactive INTERFACE force fields (IFF and IFF-R) were used to predict bulk and Young's moduli of amorphous PA6-CNT/G nanocomposites as a function of CNT/G loading. The predicted values of Young's modulus agree moderately well with the experimental values. Second, the effect of crystallinity and crystal form (α/γ) on mechanical properties of semi-crystalline PA6 was investigated via a multiscale simulation approach. The National Aeronautics and Space Administration, Glenn Research Center's micromechanics software was used to facilitate the multiscale modeling. The inputs to the multiscale model were the elastic moduli of amorphous PA6 as predicted via MD and calculated stiffness matrices from the literature of the PA6 α and γ crystal forms. The predicted Young's and shear moduli compared well with experiment.

16 Sep 2021

Penetration Modeling of Ultra‐High Performance Concrete using Multiscale Meshfree Methods

Abstract: Terminal ballistics of concrete is of extreme importance to the military and civil communities. Over the past few decades, ultra‐high performance concrete (UHPC) has been developed for various applications in the design of protective structures because UHPC has an enhanced ballistic resistance over conventional strength concrete. Developing predictive numerical models of UHPC subjected to penetration is critical in understanding the material's enhanced performance. This study employs the advanced fundamental concrete (AFC) model, and it runs inside the reproducing kernel particle method (RKPM)‐based code known as the nonlinear meshfree analysis program (NMAP). NMAP is advantageous for modeling impact and penetration problems that exhibit extreme deformation and material fragmentation. A comprehensive experimental study was conducted to characterize the UHPC. The investigation consisted of fracture toughness testing, the utilization of nondestructive microcomputed tomography analysis, and projectile penetration shots on the UHPC targets. To improve the accuracy of the model, a new scaled damage evolution law (SDEL) is employed within the microcrack informed damage model. During the homogenized macroscopic calculation, the corresponding microscopic cell needs to be dimensionally equivalent to the mesh dimension when the partial differential equation becomes ill posed and strain softening ensues. Results of numerical investigations will be compared with results of penetration experiments.

20 Apr 2020

PUBLICATION NOTIFICATION: Local Spatial Dispersion for Multiscale Modeling of Geospatial Data: Exploring Dispersion Measures to Determine Optimal Raster Data Sample Sizes

ABSTRACT: Scale, or spatial resolution, plays a key role in interpreting the spatial structure of remote sensing imagery or other geospatially dependent data. These data are provided at various spatial scales. Determination of an optimal sample or pixel size can benefit geospatial models and environmental algorithms for information extraction that require multiple datasets at different resolutions. To address this, an analysis was conducted of multiple scale factors of spatial resolution to determine an optimal sample size for a geospatial dataset. Under the NET-CMO project at ERDC-GRL, a new approach was developed and implemented for determining optimal pixel sizes for images with disparate and heterogeneous spatial structure. The application of local spatial dispersion was investigated as a three-dimensional function to be optimized in a resampled image space. Images were resampled to progressively coarser spatial resolutions and stacked to create an image space within which pixel-level maxima of dispersion was mapped. A weighted mean of dispersion and sample sizes associated with the set of local maxima was calculated to determine a single optimal sample size for an image or dataset. This size best represents the spatial structure present in the data and is optimal for further geospatial modeling.