Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “mesh optimization”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 361 records · Page 20
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

A cell-centered AMR-ALE framework for 3D multi-material hydrodynamics. Part II: linesweep ALE rezoning for nonconformal block-structured AMR meshes

The simulation of flows presenting contact discontinuities, vorticity, and large variations in spatial scales can be performed in a framework coupling Arbitrary Lagrangian Eulerian (ALE) algorithms and Adaptive Mesh Refinement (AMR). This coupling requires adaptation of ALE rezoning techniques to meshes containing nonconformal nodes arising from both the AMR topology and the junction of mesh blocks. Here, in this paper, we present an ALE rezoning strategy that is compatible with such meshes, and that can also act as a disentangling algorithm. Emphasis is put on an algorithm that respects intrinsic Lagrangian mesh properties in order to preserve accuracy around discontinuities. To that end, we adapt the weighted linesweep algorithm to nonconformal block-structured AMR meshes. Then, we present control parameters introduced in the method for it to be applicable in practical situations. Notably, the method is coupled to a specific metric optimization in order to palliate some shortcomings of the linesweep method. Finally, numerical test cases are presented that feature the capabilities of the ALE-AMR algorithm for flows that present discontinuities, vorticity, and a variety of scales. Notably, we show that our ALE-AMR algorithm gives results at least similar to Euler-AMR, but provides better accuracy in cases where discontinuities are involved, thanks to a method that respects the Lagrangian features of the mesh. Additionally, it enables Euler-AMR-like computations on domains with temporally varying domain boundaries.

Adaptive mesh refinement↗
DOE OSTI2022

Reduced order modeling for flow and transport problems with Barlow Twins self-supervised learning

Abstract We propose a unified data-driven reduced order model (ROM) that bridges the performance gap between linear and nonlinear manifold approaches. Deep learning ROM (DL-ROM) using deep-convolutional autoencoders (DC–AE) has been shown to capture nonlinear solution manifolds but fails to perform adequately when linear subspace approaches such as proper orthogonal decomposition (POD) would be optimal. Besides, most DL-ROM models rely on convolutional layers, which might limit its application to only a structured mesh. The proposed framework in this study relies on the combination of an autoencoder (AE) and Barlow Twins (BT) self-supervised learning, where BT maximizes the information content of the embedding with the latent space through a joint embedding architecture. Through a series of benchmark problems of natural convection in porous media, BT–AE performs better than the previous DL-ROM framework by providing comparable results to POD-based approaches for problems where the solution lies within a linear subspace as well as DL-ROM autoencoder-based techniques where the solution lies on a nonlinear manifold; consequently, bridges the gap between linear and nonlinear reduced manifolds. We illustrate that a proficient construction of the latent space is key to achieving these results, enabling us to map these latent spaces using regression models. The proposed framework achieves a relative error of 2% on average and 12% in the worst-case scenario (i.e., the training data is small, but the parameter space is large.). We also show that our framework provides a speed-up of $$7 \times 10^{6}$$ 7 × 10 6 times, in the best case, and $$7 \times 10^{3}$$ 7 × 10 3 times on average compared to a finite element solver. Furthermore, this BT–AE framework can operate on unstructured meshes, which provides flexibility in its application to standard numerical solvers, on-site measurements, experimental data, or a combination of these sources.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Multilevel Techniques for Compression and Reduction of Scientific Data---The Unstructured Case

Previous work on multilevel techniques for compression and reduction of scientific data is extended to the case of data given on unstructured meshes in two and three dimensions. The centerpiece of the work is a decomposition algorithm which is shown to be optimal, in terms of both storage and operational complexity, applicable to unstructured grids in both two and three dimensions, and which implicitly gives a Riesz basis that can be exploited to reduce the data while maintaining rigorous bounds on the loss incurred. The flexibility of the approach is illustrated by applications to potential flow around an airfoil and the effect of compression on quantities of interest relevant to airfoil design; compression of computational simulation of a nonlinear reaction-diffusion system with special attention given to the problem of time series reduction; and, data from a simulation of magnetically confined plasma in a fusion reactor reduced so as to preserve the electric field computed from the data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

BiRD (BioReactorDesign) [SWR-24-35]

Numerical simulations can accelerate scale up and optimization of bioreactors. This project provides a toolbox to facilitate such numerical simulations in OpenFOAM. The tool box contains 1) mesh generations tools for several typical bio reactor types in OpenFOAM 2) Inverse modeling tools to calibrate models using available experimental data 3) post processing tools that accelerate and streamline the analysis of the numerical simulations.

Hassanaly, Malik↗
DOE OSTI2018

In Situ Indexing and Query Processing of AMR Data

We have developed the first, holistic, Adaptive Mesh Refinement (AMR) capable, in situ query framework to ensure the tractability of the current- and next-generation AMR simulation analysis on the path to extreme scale. We have addressed key issues pertaining to in situ analysis, memory hierarchy, generalized parallel indexing, index-compression, and real-time access pattern detection. We have published the following research papers in high profile peer reviewed computer science conferences: (a) Parallel In Situ Detection of Connected Components in Adaptive Mesh Refinement Data; (b) AMR-aware In Situ Indexing and Scalable Querying; (c) Pattern-driven dynamic data layout optimization; (d) In situ Storage Layout Optimization for AMR Spatio-temporal Read Accesses; (e) AMRZone: A Runtime AMR Data Sharing Framework for Scientific Applications; (f) Exploring Memory Hierarchy and Network Topology for Runtime AMR Data Sharing Across Scientific Applications.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
NASA NTRSDate not supplied

OVERFLOW Analysis of Supersonic Retropropulsion Testing on a Blunt Mars Entry Vehicle Concept

Supersonic retropropulsion (SRP) flow over a Hypersonic Inflatable Aerodynamic Decelerator (HIAD) blunt-body vehicle was simulated using the Overflow Computational Fluid Dynamics (CFD) solver. Two nozzle configurations were tested (1E and 1F) as a subset of the seven total configurations in the Descent System Study (DSS) testing campaign. A generalized, Adaptive Mesh Refinement (AMR) shock capturing and plume refinement technique was developed and calibrated for producing automatic and unique grid systems optimized for any given testing condition. Solution independence from grid resolution was determined by successively increasing grid refinement until asymptotic convergence of the mean aerodynamic loads was observed. Overflow Reynolds-averaged Navier-Stokes (RANS) solutions produced realistic SRP flow phenomena, including Mach disk normal shocks contained in high-thrust plumes and bow shock triple-points. Solutions for the 1E nozzle configuration were steady. Conversely, a subset of the 1F test conditions were unsteady and exhibited periodic, non-sinusoidal expansions and contractions of the streamwise-oriented plume, resulting in unsteady aerodynamic loads on the vehicle. Initial investigations into the effect of turbulence modeling fidelity demonstrated significant differences between the aerodynamic loads simulated with RANS and Detached Eddy Simulation (DES). Multiple flow mechanisms were identified as root causes of these differences, including bow shock shape augmentation and reduced entrainment due to reduced turbulence in the DES simulations. Initial comparisons of pitching moment control authority and aerodynamic drag performance between the tested nozzle configurations demonstrated that the 1E configuration may be more advantageous for the Mars Entry, Descent, and Landing (EDL) task.

Supersonic Retropropulsion↗
NASA NTRSDate not supplied

OVERFLOW Analysis of Supersonic Retropropulsion Testing on a Blunt Mars Entry Vehicle Concept

Supersonic retropropulsion (SRP) flow over a Hypersonic Inflatable Aerodynamic Decelerator (HIAD) blunt-body vehicle was simulated using the Overflow Computational Fluid Dynamics (CFD) solver. Two nozzle configurations were tested (1E and 1F) as a subset of the seven total configurations in the Descent System Study (DSS) testing campaign. A generalized, Adaptive Mesh Refinement (AMR) shock capturing and plume refinement technique was developed and calibrated for producing automatic and unique grid systems optimized for any given testing condition. Solution independence from grid resolution was determined by successively increasing grid refinement until asymptotic convergence of the mean aerodynamic loads was observed. Overflow Reynolds-averaged Navier-Stokes (RANS) solutions produced realistic SRP flow phenomena, including Mach disk normal shocks contained in high-thrust plumes and bow shock triple-points. Solutions for the 1E nozzle configuration were steady. Conversely, a subset of the 1F test conditions were unsteady and exhibited periodic, non-sinusoidal expansions and contractions of the streamwise-oriented plume, resulting in unsteady aerodynamic loads on the vehicle. Initial investigations into the effect of turbulence modeling fidelity demonstrated significant differences between the aerodynamic loads simulated with RANS and Detached Eddy Simulation (DES). Multiple flow mechanisms were identified as root causes of these differences, including bow shock shape augmentation and reduced entrainment due to reduced turbulence in the DES simulations. Initial comparisons of pitching moment control authority and aerodynamic drag performance between the tested nozzle configurations demonstrated that the 1E configuration may be more advantageous for the Mars Entry, Descent, and Landing (EDL) task.

Supersonic Retropropulsion↗
NASA NTRS2015

Full-Carpet Design of a Low-Boom Demonstrator Concept

The Cart3D adjoint-based design framework is used to mitigate the undesirable o -track sonic boom properties of a demonstrator concept designed for low-boom directly under the flight path. First, the requirements of a Cart3D design mesh are determined using a high-fidelity mesh adapted to minimize the discretization error of the CFD analysis. Low-boom equivalent area targets are then generated at the under-track and one off-track azimuthal position for the baseline configuration. The under-track target is generated using a trim- feasible low-boom target generation process, ensuring that the final design is not only low-boom, but also trimmed at the specified flight condition. The o -track equivalent area target is generated by minimizing the A-weighted loudness using an efficient adjoint-based approach. The configuration outer mold line is then parameterized and optimized to match the off-body pressure distributions prescribed by the low-boom targets. The numerical optimizer uses design gradients which are calculated using the Cart3D adjoint- based design capability. Optimization constraints are placed on the geometry to satisfy structural feasibility. The low-boom properties of the final design are verified using the adaptive meshing approach. This analysis quantifies the error associated with the CFD mesh that is used for design. Finally, an alternate mesh construction and target positioning approach offering greater computational efficiency is demonstrated and verified.

Ordaz, Irian↗
DOE OSTI2025

Computing material volume fractions on a superimposed mesh as applied to Monte Carlo particle transport simulations

Here, we present a newly implemented ray tracing algorithm in OpenMC for efficiently computing material volume fractions on superimposed meshes in complex geometries. By firing rays along each coordinate direction through the geometry, the approach accumulates track-length data in each mesh element, thereby determining the fractional composition of each material. Scaling studies on three different models—a random tetrahedra configuration, the Frascati Neutron Generator ITER dose rate benchmark, and a stellarator design—show excellent parallel performance, with nearly linear speedup on modern multi-threaded and distributed-memory systems. An analysis of the residual error relative to high-resolution reference solutions demonstrated that under optimal conditions it decreases as 1/R, where R is the number of rays fired, making it straightforward to achieve user-prescribed accuracy. This new functionality enables practical, mesh-based approaches for detailed nuclear analyses in production Monte Carlo workflows without resorting to expensive, fully conformal or unstructured meshing.

Monte Carlo↗
DOE OSTI2025

Multiphysics Meshfree Degradation Modeling of Energy Storage Materials with Kernel Enrichment

Energy storage materials exhibit strong electro-chemo-mechanical coupling and highly anisotropic material properties, contributing to the formation and propagation of micro-cracking during charge/discharge cycling and ultimately diminishing performance and service life. With microstructural images supplied by the National Renewable Energy Laboratory (NREL), pixel-based meshfree model construction by the reproducing kernel particle method (RKPM) is used to represent the complex material microstructures that dictate the coupled physics of these systems. Traditional electro-chemo-mechanical models rely on mesh-based finite element methods, which can lead to difficulties in meshing such complex geometries and capturing crack propagation due to mesh dependency. The first kernel enrichment discussed will be the interface modified reproducing kernel (IM-RK) [1, 2], constructed by scaling a smooth kernel function with an interface-distance function to achieve strategic discontinuity types (i.e. weak discontinuities for strain discontinuities and strong discontinuities for cracks) and alleviate Gibbs oscillations near these transition zones. The IM-RK is especially useful for areas in which a known discontinuity-type is expected a priori. The second kernel enrichment to be discussed is a neural network-enhanced reproducing kernel (NN-RK) [3, 4], which is introduced to effectively model non-obvious damage and crack propagation in the material microstructures; the location, orientation, and solution transition near a localization are automatically captured by superimposed block-level NN optimizations. This NN enrichment approach allows for effective modeling of localizations via a fixed background discretization, relieving tedious efforts for adaptive refinement in traditional mesh-based methods. Applications to the heterogeneous microstructures of Li-ion battery cathodes will be presented to demonstrate the effectiveness of the proposed methods. NN-RK is additionally used to inform how crack opening and closure in turn affect the electro-chemo-mechanical responses in the material microstructure. Reference: [1] Wang, Y., Baek, J., Tang, Y. et al. "Support vector machine guided reproducing kernel particle method for image-based modeling of microstructures," Comput Mech 73, 907-942 (2024). https://doi.org/10.1007/s00466-023-02394-9. [2] Susuki, K., Allen, J. & Chen, J. S.. "Image-based modeling of coupled electro-chemo-mechanical behavior of Li-ion battery cathode using an interface-modified reproducing kernel particle method," Engineering with Computers (2024). https://doi.org/10.1007/s00366-024-02016-9. [3] Baek, J., Chen, J. S., Susuki, K., "Neural Network enhanced Reproducing Kernel Particle Method for Modeling Localizations," International Journal for Numerical Methods in Engineering, Vol. 123, 4422-4454 (2022). https://doi.org/10.1002/nme.7040.

25 ENERGY STORAGE↗
DOE OSTI2026

Kernel Enriched Meshfree Multiphysics Degradation Modeling of Energy Storage Materials

Energy storage materials exhibit strong electro-chemo-mechanical coupling and highly anisotropic material properties, contributing to the formation and propagation of micro-cracking during charge/discharge cycling and ultimately diminishing performance and service life. With microstructural images supplied by the National Laboratory of the Rockies (NLR), pixel-based meshfree model construction by the reproducing kernel particle method (RKPM) is used to represent the complex material microstructures that dictate the coupled physics of these systems. Traditional electro-chemo-mechanical models rely on mesh-based finite element methods, which can lead to difficulties in meshing such complex geometries and capturing crack propagation due to mesh dependency. The first kernel enrichment discussed will be the interface modified reproducing kernel (IM-RK) [1, 2], constructed by scaling a smooth kernel function with an interface-distance function to achieve strategic discontinuity types (i.e. weak discontinuities for strain discontinuities and strong discontinuities for cracks) and alleviate Gibbs oscillations near these transition zones. The IM-RK is especially useful for areas in which a known discontinuity-type is expected a priori. The second kernel enrichment to be discussed is a neural network-enhanced reproducing kernel (NN-RK) [3, 4], which is introduced to effectively model non-obvious damage and crack propagation in the material microstructures; the location, orientation, and solution transition near a localization are automatically captured by superimposed block-level NN optimizations. This NN enrichment approach allows for effective modeling of localizations via a fixed background discretization, relieving tedious efforts for adaptive refinement in traditional mesh-based methods. Applications to the heterogeneous microstructures of Li-ion battery cathodes will be presented to demonstrate the effectiveness of the proposed methods. NN-RK is additionally used to inform how crack opening and closure in turn affect the electro-chemo-mechanical responses in the material microstructure. References: [1] Wang, Y., Baek, J., Tang, Y. et al. "Support vector machine guided reproducing kernel particle method for image-based modeling of microstructures," Comput Mech 73, 907-942 (2024). https://doi.org/10.1007/s00466-023-02394-9. [2] Susuki, K., Allen, J. & Chen, J. S.. "Image-based modeling of coupled electro-chemo-mechanical behavior of Li-ion battery cathode using an interface-modified reproducing kernel particle method," Engineering with Computers (2024). https://doi.org/10.1007/s00366-024-02016-9. [3] Baek, J., Chen, J. S., Susuki, K., "Neural Network enhanced Reproducing Kernel Particle Method for Modeling Localizations," International Journal for Numerical Methods in Engineering, Vol. 123, 4422-4454 (2022). https://doi.org/10.1002/nme.7040.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1993

Development of an hp-version finite element method for computational optimal control

The purpose of this research effort is to develop a means to use, and to ultimately implement, hp-version finite elements in the numerical solution of optimal control problems. The hybrid MACSYMA/FORTRAN code GENCODE was developed which utilized h-version finite elements to successfully approximate solutions to a wide class of optimal control problems. In that code the means for improvement of the solution was the refinement of the time-discretization mesh. With the extension to hp-version finite elements, the degrees of freedom include both nodal values and extra interior values associated with the unknown states, co-states, and controls, the number of which depends on the order of the shape functions in each element.

Hodges, Dewey H.↗
NASA NTRS1995

SEEK: A FORTRAN optimization program using a feasible directions gradient search

This report describes the use of computer program 'SEEK' which works in conjunction with two user-written subroutines and an input data file to perform an optimization procedure on a user's problem. The optimization method uses a modified feasible directions gradient technique. SEEK is written in ANSI standard Fortran 77, has an object size of about 46K bytes, and can be used on a personal computer running DOS. This report describes the use of the program and discusses the optimizing method. The program use is illustrated with four example problems: a bushing design, a helical coil spring design, a gear mesh design, and a two-parameter Weibull life-reliability curve fit.

Savage, M.↗
NASA NTRS1997

National Combustion Code: A Multidisciplinary Combustor Design System

The Internal Fluid Mechanics Division conducts both basic research and technology, and system technology research for aerospace propulsion systems components. The research within the division, which is both computational and experimental, is aimed at improving fundamental understanding of flow physics in inlets, ducts, nozzles, turbomachinery, and combustors. This article and the following three articles highlight some of the work accomplished in 1996. A multidisciplinary combustor design system is critical for optimizing the combustor design process. Such a system should include sophisticated computer-aided design (CAD) tools for geometry creation, advanced mesh generators for creating solid model representations, a common framework for fluid flow and structural analyses, modern postprocessing tools, and parallel processing. The goal of the present effort is to develop some of the enabling technologies and to demonstrate their overall performance in an integrated system called the National Combustion Code.

Stubbs, Robert M.↗
DOE OSTI2026

Hydrodynamic Analysis and Optimization of Aquantis Marine Turbine: Cooperative Research and Development (Final Report)

The primary aim of this proposal is to improve the accurate prediction of hydrodynamic performance and dynamic load responses of the AQ10 floating axial-flow tidal turbine with a tri-cat mooring configuration. The validation of reduced-order modeling approaches with high-fidelity model will be implemented. Additionally, the frequency response domain, Response Amplitude Floating Wind (RAFT) toolbox plus an optimizer expanded for marine hydrokinetic turbines under the Submarine Hydrokinetic And Riverine Kilo-megawatt. Systems (SHARKS) program will be used for designing and exploring different key design parameters (platform dimension, mooring layout and its parameters) of next marine hydrokinetic (MHK) turbine generation.

16 TIDAL AND WAVE POWER↗
NASA NTRS2000

A Parallel Multiblock Mesh Movement Scheme For Complex Aeroelastic Applications

A scheme has been developed for the movement of multiblock, structured grids due to surface deformation arising from aeroelastics, control surface movement, or design optimization. Elements of the method include a blending of a surface spline approximation and nearest surface point movement for block boundaries. Transfinite interpolation is employed for volume grid deformation. The scheme is demonstrated on a range of simple and complex aeroelastic aircraft applications using Navier-Stokes computational fluid dynamics and modal structural analyses on parallel processors. Results are robust and accurate, requiring only minimal user input specification.

Potsdam, Mark A.↗
DOE OSTI2021

Serpent and MCNP Calculations of the Energy Deposition in the Transformational Challenge Reactor

This paper focuses on the calculation of the energy deposition in the Transformational Challenge Reactor by two major Monte Carlo codes: Serpent and MCNP. The first software computation relies on Kinetic Energy Released per unit Mass (KERMA) factors while the second one relies on Q-values. The results from these two independent computation methodologies are in very good agreement; however, Serpent runs much faster than MCNP (for the same computational model) and allows for a detailed energy deposition distribution from a 1-mm-side square mesh with a relative statistical error between 0.5% and 1%. This detailed energy deposition is suitable for multiphysics analyses aimed at design optimizations. In order to calculate the energy deposition, Serpent needs enhanced ACE files (distributed by the software developers). Unlike other Monte Carlo software that uses inputs based on Python or Java languages, the Serpent input syntax is very similar to that of MCNP; a Python script can convert a MCNP input to a Serpent input in seconds. For simulations not requiring the calculation of the energy deposition, Serpent can also read nuclear data from MCNP ACE files, which eventually improves the comparison of the results of the two codes.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗