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NASA NTRS1990

Adaptive quadrilateral and triangular finite-element scheme for compressible flows

The development of an adaptive mesh refinement procedure for analyzing high-speed compressible flows using the finite-element method is described. This new adaptation procedure, which uses both quadrilateral and triangular elements, was implemented with two explicit finite-element algorithms - the two-step Taylor-Galerkin and the multistep Galerkin-Runge-Kutta schemes. A von Neumann stability analysis and a rotating 'cosine hill'problem demonstrate the instability of the Taylor-Galerkin scheme when coupled with the adaptation procedure. For the same adaptive refinement scheme, the Galerkin-Runge-Kutta procedure yields stable solutions within its explicit stability limit. The utility of this new adaptation procedure for the prediction of compressible flow features is illustrated for inviscid problems involving strong shock interactions at hypersonic speeds.

Ramakrishnan, R.↗

DOE OSTI2024

Adamantine 1.0: A Thermomechanical Simulator for Additive Manufacturing

Adamantine is a thermomechanical simulation code that is written in C++ and built on top of deal.II (Arndt et al., 2023), p4est (Burstedde et al., 2011), ArborX (Lebrun-Grandié et al., 2020), Trilinos (The Trilinos Project Team, 2020), and Kokkos (Trott et al., 2022). Adamantine was developed with additive manufacturing in mind and it is particularly well adapted to simulate fused filament fabrication, directed energy deposition, and powder bed fusion. Adamantine employs the finite element method with adaptive mesh refinement to solve a nonlinear anisotropic heat equation, enabling support for various additive manufacturing processes. It can also perform elastoplastic and thermoelastoplastic simulations. It can handle materials in three distinct phases (solid, liquid, and powder) to accurately reflect the physical state during different stages of the manufacturing process. To enhance simulation accuracy, adamantine incorporates data assimilation techniques (Asch et al., 2016). This allows it to integrate experimental data from sensors like thermocouples and infrared (IR) cameras. This combined approach helps account for errors arising from input parameters, material properties, models, and numerical calculations, leading to more realistic simulations that reflect what occurs in a particular print.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Benchmarking of massively parallel phase-field codes for directional solidification

We present a detailed benchmark comparing two state-of-the-art phase-field implementations for simulating alloy solidification under experimentally relevant conditions. The study investigates the directional solidification of Al-3wt%Cu under high-velocity solidification conditions and SCN-0.46wt% camphor under microgravity conditions from National Aeronautics and Space Administration (NASA) DECLIC-DSI-R experiments. Both codes, one employing finite-difference discretization with uniform mesh and GPU-acceleration (GPU-PF) and the other one employing finite-element discretization with adaptive-mesh and CPU-parallelization (PRISMS-PF), solve the same quantitative phase-field formulation that incorporates an anti-trapping current for the solidification of dilute alloys. We evaluate the predictions of each code for dendritic morphology, primary spacing, and tip dynamics in both 2D and 3D, as well as their numerical convergence and computational performance. While existing benchmark problems have primarily focused on simplified or small-scale simulations, they do not reflect the computational and modeling challenges posed by employing experimentally relevant time and length scales. Our results provide a practical framework for assessing phase-field code performance as well as validating and facilitating their application in integrated computational materials engineering (ICME) workflows that require integration with realistic experimental data.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Multi-Objective Adaptive Mesh Refinement Using Reinforcement Learning

Finite element methods approximate the solution to a partial differential equation (PDE) on a mesh consisting of many elements. In general, using more, smaller elements results in a lower error in the approximation. However, it is often possible to lower the error substantially by only refining, or decreasing the size of, the few elements in the mesh that have the highest error. Adaptive mesh refinement (AMR) is a process that selectively refines regions of a mesh with high error to achieve a desired accuracy in as few degrees of freedom (DOFs) as possible. AMR is favorable compared to uniform refinement, which refines all elements of the mesh equally, because it can often achieve the same accuracy without wasting extra computation time on refinement of elements that already have low error. However, it is difficult to know which elements to refine. In this report we explore ways to choose which elements to refine such that we minimize both the resulting error and the cumulative DOFs used in computation. In particular, we introduce a Pareto-front learning algorithm that trains a policy to give the optimal refinement actions to minimize the cumulative DOFs used to achieve a given target error. Such a policy is useful because it can be deployed on many different problem types where different accuracy levels are desired. Furthermore, training a single policy for a range of target errors allows us to use transfer learning to reduce the required training time.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2020

Verification of Anisotropic Mesh Adaptation for Turbulent Simulations over ONERA M6 Wing

Unstructured anisotropic mesh adaptation is known to be an efficient way to control discretization errors in Computational Fluid Dynamics (CFD) simulations. Method verification is required to provide the confidence for routine use in production analysis. The current work aims at verification of anisotropic mesh adaptation for RANS simulations over the ONERA M6 wing. The present verification study is performed using four different flow solvers, three different implementations of the metric field, and three mesh mechanics packages. Two of the flow solvers use stabilized finite-element discretizations (FUN3D-SFE and GGNS), one uses finite-volume discretization (FUN3D-FV), and the last one uses mixed finite-volume and finite element discretizations (Wolf). The mesh adaptation is based on an error estimator that aims to control the quadratic error term in the linear interpolation of Mach number. Two sets of adaptations were performed; the first one controls the interpolation error in L2 norm and the second one controls the interpolation error in L4 norm. Convergence studies were performed on the forces and the pitching moment using all four solvers, and the results are compared with previously verified convergence studies on fixed (nonadapted) meshes. Both forces and pitching moment on adapted meshes are found to be converging to the fine mesh values faster than those on fixed meshes. In addition to forces and moments, convergence of surface pressure and skin friction coefficients at various measurement locations on the wing are also presented. Adapted-mesh surface pressure distributions agree with the fine fixed mesh pressure distributions. Adapted-mesh skin friction distributions contain high frequency noise with mean values approaching the fixed mesh pressure skin friction distributions.

Aravind Balan↗

NASA NTRS2014

Adaptive Shape Functions and Internal Mesh Adaptation for Modelling Progressive Failure in Adhesively Bonded Joints

Enhanced finite elements are elements with an embedded analytical solution that can capture detailed local fields, enabling more efficient, mesh independent finite element analysis. The shape functions are determined based on the analytical model rather than prescribed. This method was applied to adhesively bonded joints to model joint behavior with one element through the thickness. This study demonstrates two methods of maintaining the fidelity of such elements during adhesive non-linearity and cracking without increasing the mesh needed for an accurate solution. The first method uses adaptive shape functions, where the shape functions are recalculated at each load step based on the softening of the adhesive. The second method is internal mesh adaption, where cracking of the adhesive within an element is captured by further discretizing the element internally to represent the partially cracked geometry. By keeping mesh adaptations within an element, a finer mesh can be used during the analysis without affecting the global finite element model mesh. Examples are shown which highlight when each method is most effective in reducing the number of elements needed to capture adhesive nonlinearity and cracking. These methods are validated against analogous finite element models utilizing cohesive zone elements.

computational mechanics↗

DOE OSTI2023

Linearization errors in discrete goal-oriented error estimation

This paper is concerned with goal-oriented a posteriori error estimation for nonlinear functionals in the context of nonlinear variational problems solved with continuous Galerkin finite element discretizations. A two-level, or discrete, adjoint-based approach for error estimation is considered. The traditional method to derive an error estimate in this context requires linearizing both the nonlinear variational form and the nonlinear functional of interest which introduces linearization errors into the error estimate. In this paper, we investigate these linearization errors. In particular, we develop a novel discrete goal-oriented error estimate that accounts for traditionally neglected nonlinear terms at the expense of greater computational cost. We demonstrate how this error estimate can be used to drive mesh adaptivity. Here, we show that accounting for linearization errors in the error estimate can improve its effectivity for several nonlinear model problems and quantities of interest. We also demonstrate that an adaptive strategy based on the newly proposed estimate can lead to more accurate approximations of the nonlinear functional with fewer degrees of freedom when compared to uniform refinement and traditional adjoint-based approaches.

42 ENGINEERING↗

NASA NTRS1990

Integrated fluid-thermal-structural analysis using adaptive unstructured meshes

An integrated fluid-thermal-structural analysis approach using adaptive unstructured meshes is presented. The approach combines the finite-element method and an adaptive remeshing technique to solve the Navier-tokes equations for high-speed compressible flow, the energy equation for the thermal response of the structure, and the quasi-static equilibrium equations for the structural response. The analysis solution procedure and the adaptive unstructured remeshing technique are described. The effectiveness of the approach is evaluated with three application studies. The adaptive unstructured remeshing procedure and finite-element solution algorithms combine to yield increased accuracy and effiency over standard structured meshes.

Dechaumphai, Pramote↗

NASA NTRS1999

Adaptive Mesh Refinement for Microelectronic Device Design

Finite element and finite volume methods are used in a variety of design simulations when it is necessary to compute fields throughout regions that contain varying materials or geometry. Convergence of the simulation can be assessed by uniformly increasing the mesh density until an observable quantity stabilizes. Depending on the electrical size of the problem, uniform refinement of the mesh may be computationally infeasible due to memory limitations. Similarly, depending on the geometric complexity of the object being modeled, uniform refinement can be inefficient since regions that do not need refinement add to the computational expense. In either case, convergence to the correct (measured) solution is not guaranteed. Adaptive mesh refinement methods attempt to selectively refine the region of the mesh that is estimated to contain proportionally higher solution errors. The refinement may be obtained by decreasing the element size (h-refinement), by increasing the order of the element (p-refinement) or by a combination of the two (h-p refinement). A successful adaptive strategy refines the mesh to produce an accurate solution measured against the correct fields without undue computational expense. This is accomplished by the use of a) reliable a posteriori error estimates, b) hierarchal elements, and c) automatic adaptive mesh generation. Adaptive methods are also useful when problems with multi-scale field variations are encountered. These occur in active electronic devices that have thin doped layers and also when mixed physics is used in the calculation. The mesh needs to be fine at and near the thin layer to capture rapid field or charge variations, but can coarsen away from these layers where field variations smoothen and charge densities are uniform. This poster will present an adaptive mesh refinement package that runs on parallel computers and is applied to specific microelectronic device simulations. Passive sensors that operate in the infrared portion of the spectrum as well as active device simulations that model charge transport and Maxwell's equations will be presented.

Cwik, Tom↗

NASA NTRS1984

Adaptive grid refinement for the Euler and compressible Navier-Stokes equations

The incorporation of a simple a posteriori adaptive mesh method into an explicit finite element based procedure for the solution of compressible flow problems is described. The re-interpolation problem is discussed and results are presented that indicate the improvement in solution quality which can be obtained via such an adaptive mesh approach. The method may lead to the appearance of some badly deformed elements which are removed from the domain of computation.

Lohner, R.↗

DOE OSTI2024

Dyn$\mathrm{AMO}$: Multi-agent reinforcement learning for dynamic anticipatory mesh optimization with applications to hyperbolic conservation laws

Here we introduce DynAMO, a reinforcement learning paradigm for Dynamic Anticipatory Mesh Optimization. Adaptive mesh refinement is an effective tool for optimizing computational cost and solution accuracy in numerical methods for partial differential equations. However, traditional adaptive mesh refinement approaches for time-dependent problems typically rely only on instantaneous error indicators to guide adaptivity. As a result, standard strategies often require frequent remeshing to maintain accuracy. In the DynAMO approach, multi-agent reinforcement learning is used to discover new local refinement policies that can anticipate and respond to future solution states by producing meshes that deliver more accurate solutions for longer time intervals. By applying DynAMO to discontinuous Galerkin methods for the linear advection and compressible Euler equations in two dimensions, we demonstrate that this new mesh refinement paradigm can outperform conventional threshold-based strategies while also generalizing to different mesh sizes, remeshing and simulation times, and initial conditions.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1999

Drop Ejection From an Oscillating Rod

The dynamics of a drop of a Newtonian liquid that is pendant from or sessile on a solid rod that is forced to undergo time-periodic oscillations along its axis is studied theoretically. The free boundary problem governing the time evolution of the shape of the drop and the flow field inside it is solved by a method of lines using a finite element algorithm incorporating an adaptive mesh. When the forcing amplitude is small, the drop approaches a limit cycle at large times and undergoes steady oscillations thereafter. However, drop breakup is the consequence if the forcing amplitude exceeds a critical value. Over a wide range of amplitudes above this critical value, drop ejection from the rod occurs during the second oscillation period from the commencement of rod motion. Remarkably, the shape of the interface at breakup and the volume of the primary drop formed are insensitive to changes in forcing amplitude. The interface shape at times close to and at breakup is a multi-valued function of distance measured along the rod axis and hence cannot be described by recently popularized one-dimensional approximations. The computations show that drop ejection occurs without the formation of a long neck. Therefore, this method of drop formation holds promise of preventing formation of undesirable satellite droplets.

Wilkes, E. D.↗

NASA NTRSDate not supplied

Fluid-Structure Interaction Simulations of the ASPIRE SR03 Supersonic Parachute Flight Test

Research into parachute performance continues to be a source of significant investment from the National Aeronautics and Space Administration to mitigate risks and to enable a variety of exploration missions, including landing on Mars as well as returning to Earth. The cost of flight tests to certify any changes to the current state-of-the-art parachute designs limits the development of next generation parachute systems. Fluid-structure interaction simulations could help accelerate this process once validated. The Launch, Ascent, and Vehicle Aerodynamics team is developing the capability to perform such fluid-structure interaction simulations by coupling a higher-order Cartesian immersed boundary computational fluid dynamics solver with adaptive mesh refinement to a finite element structural dynamics solver in space and time. We continue the effort to validate this tool with the Advanced Supersonic Parachute Inflation Research Experiments SR03 flight test featuring a strengthened parachute akin to the Mars 2020 mission that landed the Perseverance rover on Mars, and a higher freestream dynamic pressure prior to inflation. The effect of the flow conditions’ angle of attack and of the initial parachute shape are quantified. The impact of relaxing modeling assumptions with regards to radial stiffeners on the parachute canopy is also investigated. Results demonstrate improvements in agreement with the pull force recorded during the SR03 flight test as the initial conditions of the flow and parachute are brought closer to those experienced in flight, and further improved when the radial stiffener modeling assumptions are relaxed.

ESM↗

NASA NTRSDate not supplied

Fluid-Structure Interaction Simulations of the ASPIRE SR03 Supersonic Parachute Flight Test

ESM↗

NASA NTRSDate not supplied

Verification of Anisotropic Mesh Adaptation for Complex Aerospace Applications

The stabilized finite element solver, FUN3D-SFE, along with the grid mechanics package refine are verified for aerospace applications of laminar and turbulent flow simulations. The current verification exercise represents an extension of previous research using FUN3D-SFEwith adjoint-based mesh adaptation to generate highly anisotropic adapted meshes for inviscid problems. Adaptations are performed using a solution-based approach that controls the Lpnorm of Mach number interpolation error and an adjoint-based approach that controls the error in some output functional. Adaptive results are shown for laminar subsonic flow over a delta wing, laminar subsonic flow over ONERA M6 wing, inviscid supersonic flow over a sonic boom test case, and a turbulent flow over a high lift configuration (JAXA Standard Model). Mesh convergence results are also compared with results from FUN3D-FV (Finite Volume) whenever available. For all test cases considered, FUN3D-SFE gives significantly better accurate results than FUN3D-FV on coarse meshes.

Aravind Balan↗

DOE OSTI2021

Automatically adaptive stabilized finite elements and continuation analysis for compaction banding in geomaterials

Under compressive creep, viscoplastic solids experiencing internal mass transfer processes can accommodate singular cnoidal wave solutions as material instabilities at the stationary wave limit. These instabilities appear when the loading rate is significantly faster than the material's capacity to diffusive internal perturbations, leading to localized failure features (e.g., cracks and compaction bands). These cnoidal waves, generally found in fluids, have strong nonlinearities that produce periodic patterns. Due to the singular nature of the solutions, the applicability of the theory is currently limited. Additionally, practical simulation tools require proper regularization to overcome the challenges that singularity induces. We focus on the numerical treatment of the governing equation using a nonlinear approach building on a recent adaptive stabilized finite element method. This automatic refinement method provides an error estimate that drives mesh adaptivity, a crucial feature for the problem at hand. We compare the performance of this adaptive strategy against analytical and standard finite element solutions. We then investigate the sensitivity of the diffusivity ratio, the parameter controlling the process, and identify multiple possible solutions with several stress peaks. We also show the evolution of the spacing between peaks for all solutions as a function of that parameter.

42 ENGINEERING↗

DOE OSTI2021

hr-Adaptivity for nonconforming high-order meshes with the target matrix optimization paradigm

In this study, we present an $hr$ -adaptivity framework for optimization of high-order meshes. This work extends the r -adaptivity method by Dobrev et al. (Comput Fluids, 2020), where we utilized the Target-Matrix Optimization Paradigm (TMOP) to minimize a functional that depends on each element’s current and target geometric parameters: element aspect-ratio , size , skew , and rotation . Since fixed mesh topology limits the ability to achieve the target size and aspect-ratio at each position, in this paper, we augment the r -adaptivity framework with nonconforming adaptive mesh refinement to further reduce the error with respect to the target geometric parameters. The proposed formulation, referred to as $hr$ -adaptivity, introduces TMOP-based quality estimators to satisfy the aspect-ratio target via anisotropic refinements and size target via isotropic refinements in each element of the mesh. The methodology presented is purely algebraic, extends to both simplices and hexahedra/quadrilaterals of any order, and supports nonconforming isotropic and anisotropic refinements in 2D and 3D. Using a problem with a known exact solution, we demonstrate the effectiveness of $hr$ -adaptivity over both r - and $h$ -adaptivity in obtaining similar accuracy in the solution with significantly fewer mesh nodes. We also present several examples that show that $hr$ -adaptivity can help satisfy geometric targets even when $r$ -adaptivity fails to do so, due to the topology of the initial mesh.

42 ENGINEERING↗

NASA NTRS1987

Finite element methods for compressible flows

The problems of mesh generation and developing effective algorithms for the solution of the equations of compressible flow on unstructured meshes are discussed. Adaptive mesh refinement methods can be implemented in a straightforward manner. Possible adaptive strategies are examined. A finite element method adapted to problems involving high speed compressible flow is described. The adaptive mesh regeneration procedure appears to offer the possibility of large computational savings in three dimensional flow computation.

Morgan, K.↗