GOMA 6.0 - A Full-Newton Finite Element Program for Free and Moving Boundary Problems with Coupled Fluid/ Solid Momentum, Energy, Mass, and Chemical Species Transport: User’s Guide

Schunk, Peter Randall; Rao, Rekha R.; Chen, Ken; Labreche, Duane A.; Sun, Amy Cha-Tien; Hopkins, Matthew M.; Moffat, Harry K.; Roach, Robert Allen; Hopkins, P.L.; Notz, Patrick; Roberts, Scott Alan; Sackinger, Philip A.; Subia, Samuel R.; Wilkes, Edward D.; Baer, Thomas A.; Noble, David R.; Secor, R. B.

doi:10.2172/1089869

Cited by 12 publications

(6 citation statements)

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“…The multiphase lubrication and porous flow equations of §2 are implemented into the Galerkin finite element method code Goma [34]. We chose isoparametric quadrilateral shell elements with bi-linear (Q1) Lagrange interpolation functions, the implementation of which was discussed in a previous work [11].…”

Section: Methodsmentioning

confidence: 99%

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A reduced-order model for porous flow through thin, structured materials

Roberts

Schunk

2014

International Journal of Multiphase Flow

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Darcy's equations are frequently used as a coarse-grained numerical expedient for modeling multiphase flow through complex porous materials. In some applications, the porous material may be quite thin, allowing the possibility of further simplification of the equations.In this paper we derive a reduced-order shell finite-element model for flow through thin porous materials using an approach similar to that taken to derive the Reynolds' lubrication equation. We advance first a formulation that addresses generalized unstructured porous materials and then specialize the equations for certain structured cases. We also extend the model to account for multiphase, confined lubrication flow in an adjoining layer and gas transport within the pores. We apply the model to several problems of topical interest in micro-and nano-manufacturing processes.

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Section: Methodsmentioning

confidence: 99%

“…Of course, (29)(30)(31)(32)(33)(34)(35) were derived specifically for the assumed geometry of figure 3. When full saturation (S = 1) is reached, this equation is replaced by ∂S ∂t = 0.…”

Section: Open-feature Flowmentioning

confidence: 99%

A reduced-order model for porous flow through thin, structured materials

Roberts

Schunk

2014

International Journal of Multiphase Flow

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“…We solve our governing equations using the finite element program Goma. 24 Our foaming volume is captured using an ALE method where the interface is treated as Lagrangian while the fluid is treated as Eulerian. Details of the 3D ALE implementation in Goma, in which the deformable mesh is treated as a compressible elastic solid, were published by Cairncross et al 25 The ALE implementation results in additional unknowns representing the displacement of our mesh d from its initial state X, resulting in a stressed mesh state x. Deformation is governed by a quasi-static momentum equation:…”

Section: Extension To 3d Modelmentioning

confidence: 99%

“…Here we use a moving mesh coupled to a finite element method. We solve our governing equations using the finite element program Goma 24 . Our foaming volume is captured using an ALE method where the interface is treated as Lagrangian while the fluid is treated as Eulerian.…”

Section: Extension To 3d Modelmentioning

confidence: 99%

Population balance modeling of polyurethane foam formation with pressure‐dependent growth kernel

et al. 2021

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Polyurethane foams are widely used materials often chosen for their useful characteristics such as low thermal conductivity, ease of application, and high strength-toweight ratios. Computational models are needed to predict the dynamics of the flow and expansion, and the resulting material properties, to improve manufacturing processes. In this paper, a model for PMDI, a water-blown polyurethane foam, is presented. By extending a kinetics-based approach by adding bubble-scale information via a population balance equation (PBE) using the quadrature method of moments, we can track bubble size distributions during foaming. We present results from a three-dimensional computational fluid dynamics model using arbitrary Lagrangian-Eulerian interface tracking implemented in finite element software. The model compares favorably with experimental data, including dynamics, bubble distributions measured by both camera and diffusion wave spectroscopy, and post-test bubble size from scanning electron microscopy and density measurements from x-ray computed tomography.

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“…While DAKOTA manages the interval halving and function evaluation invocations, the user is responsible for managing the initial guess for the simulation program. For example, in a GOMA input file [123], the user specifies the files to be used for reading initial guess data and writing solution data. When using the last successful evaluation in the continuation algorithm, the translation of initial guess data can be accomplished by simply copying the solution data file leftover from the last evaluation to the initial guess file for the current evaluation (and in fact this is useful for all evaluations, not just continuation).…”

Section: Continuationmentioning

confidence: 99%

Dakota, A Multilevel Parallel Object-Oriented Framework for Design Optimization, Parameter Estimation, Uncertainty Quantification, and Sensitivity Analysis: Version 6.13 User's Manual

Adams

Bohnhoff

Dalbey

et al. 2020

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The DAKOTA (Design Analysis Kit for Optimization and Terascale Applications) toolkit provides a flexible and extensible interface between simulation codes and iterative analysis methods. DAKOTA contains algorithms for optimization with gradient and nongradient-based methods; uncertainty quantification with sampling, reliability, and stochastic finite element methods; parameter estimation with nonlinear least squares methods; and sensitivity/variance analysis with design of experiments and parameter study methods. These capabilities may be used on their own or as components within advanced strategies such as surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty. By employing object-oriented design to implement abstractions of the key components required for iterative systems analyses, the DAKOTA toolkit provides a flexible and extensible problem-solving environment for design and performance analysis of computational models on high performance computers.This report serves as a user's manual for the DAKOTA software and provides capability overviews and procedures for software execution, as well as a variety of example studies.

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GOMA 6.0 - A Full-Newton Finite Element Program for Free and Moving Boundary Problems with Coupled Fluid/ Solid Momentum, Energy, Mass, and Chemical Species Transport: User’s Guide

Cited by 12 publications

References 0 publications

A reduced-order model for porous flow through thin, structured materials

A reduced-order model for porous flow through thin, structured materials

Population balance modeling of polyurethane foam formation with pressure‐dependent growth kernel

Dakota, A Multilevel Parallel Object-Oriented Framework for Design Optimization, Parameter Estimation, Uncertainty Quantification, and Sensitivity Analysis: Version 6.13 User's Manual

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