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At least 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Three Dimensional Surface Redefinition Method for Computational Ice Accretion Solvers

Computational tools have been increasing in maturity and are thus commonly used in the engineering design process. Advancements in NASA’s current state of the art computational ice accretion tool are required to tackle the icing challenges of tomorrow. GlennICE, a next generation ice accretion solver, is under development at NASA to tackle these challenges. One of the elements of this migration is transitioning from a quasi-three dimensional strip theory based ice accretion methodology to a fully three dimensional methodology. This requires construction of a method to redefine or extrude a discretized or tessellated surface geometry based on the predicted volumetric ice growth for each tessellated surface triangle. This paper describes the methodology that is employed in the GlennICE software, and assesses the performance of the method in replicating a well definied analytical test case.

Computational↗
NASA NTRS2021

Coupling of the FUN3D Unstructured Flow Solver and the LASTRAC Stability Code to Model Transition

We develop an iterative automated method to predict transition locations in boundary-layer flows by using the FUN3D solver to perform flow simulations and the LASTRAC code for linear stability computations. The coupling of FUN3D and LASTRAC allows for a robust physics-based approach to model boundary-layer transition by analyzing the growth of different instability waves and then using that information to iteratively update the resulting transition location. There is no user involvement during the iterative computations. We apply this automated method to subsonic flow over a flat plate with a sharp leading edge. The final solution has regions of laminar and turbulent flow with a transition onset location that agrees with experiments and stability-based correlations. This iterative automated method is also applied to an NLF(1)-0416 airfoil for conditions with and without a separation bubble. Along with predicting transition locations, we compare the streamwise distributions of surface-pressure and skin-friction coefficients to a transport-equation-based model. We consider a 6:1 prolate spheroid at three angles of attack, namely, five, ten, and fifteen degrees, where mixed-mode transition occurs due to both Tollmien-Schlichting and crossflow instabilities. The skin-friction contours and transition fronts at every angle of attack from our iterative automated method show good agreement with past experimental and computational results in the literature for the 6:1 prolate spheroid.

Transition↗
NASA NTRSDate not supplied

Validation of Actuator Disk, Actuator Line and Sliding Mesh Methods within the LAVA Solver

In this study the implementation of actuator-disk, actuator-line and sliding-mesh methodologies in the Launch Ascent and Vehicle Aerodynamics (LAVA) solver is described and validated against several test-cases. The different models are validated against available numerical as well as experimental data. Both steady and unsteady Reynolds-Averaged Navier-Stokes (RANS) simulations using the Spallart Allmaras (SA) turbulence model are performed for several different configurations representative of aeroscience applications. The first part of the paper is focused on the verification and validation of the implemented propulsor models. The first validation case is a theoretical rotor in hover, compared with the 1D analytical solution derived from momentum theory. The second validation is the Rotor-Airframe Interaction Model of Georgia Institute of Technology (GIT), representing the application of actuator disks to top-mounted rotorcraft vehicles or unmanned aerial vehicles (UAVs). The third case is a representative configuration for tip-mounted rotor-craft vehicles such as NASA’s X57 airplane. The second part of the paper shows the implemented models applied to realistic engineering configurations such as NASA’s X57 airplane and the R4 Advanced Ducted Propellor (ADT). A modification to the actuator line method in order to represent the blade geometry more closely is proposed and comparisons with simulations modeling the blade utilizing a sliding-mesh approach are made.

ARMD↗
NASA NTRSDate not supplied

Wall-Modeled Large Eddy Simulation Method for Unstructured-Grid Navier-Stokes Solvers

This paper reports on the implementation and assessment of a Wall-Modeled Large-Eddy Simulation (WMLES) methodology in an unstructured-grid, node-centered flow solver, FUN3D that is developed and supported at the NASA Langley Research Center. Finite-volume (FV) and finite-element (FE) discretization schemes considered in the study provide formal second-order spatial accuracy. Large-Eddy Simulations (LES) resolve large-scale turbulent-flow features and filter out small-scale effects using the Vreman subgrid-scale model. At solid-wall boundaries, a shear-stress model is employed to provide a proper boundary-flux closure. The nonlinear equations are integrated in time using either an optimized backward difference formula or an implicit multistage Runge-Kutta temporal scheme. The implicit equations at each time step are solved by strong nonlinear iteration schemes. WMLES demonstrations are shown for two high-lift configurations, namely, the McDonnell Douglas 30P30N multielement airfoil and a NASA High-Lift Common Research Model. Results show that the WMLES approaches implemented in the FV and FE discretization methods produce consistent solutions and are capable of capturing key aerodynamic characteristics and flow structures for high-lift configurations at a wide range of angles of attack including maximum-lift conditions. In the 30P30N example, correct trends in the variations of integrated aerodynamic forces and moments, surface pressure distributions, and boundary-layer profiles are captured as the Reynolds number is increased.

CFD; turbulence modeling; High-Lift flow simulatio↗
NASA NTRS2025

Hardware in the Loop Performance of Terrestrial Powered Descent Dual Quaternion Guidance With A Custom First-Order Solver

The Safe & Precise Landing Integrated Capabilities Evolution (SPLICE) program continues to push the development of advanced descent and landing technologies. This paper will focus on the improvements made to the SPLICE Dual Quaternion Guidance (DQG) algorithm, which is a critical software component for generating approach phase and hazard avoidance trajectories. The trajectory performance of SPLICE DQG will be evaluated in preparation for a terrestrial flight test that incorporates a hazard avoidance maneuver. Additionally, the implementation of a customized first order Proportional-Integral Projected Gradient solver will be reviewed, along with preliminary execution results on the SPLICE Descent and Landing Computer (DLC).

SPLICE↗
NASA NTRSDate not supplied

Validation Assessment of Loci/GGFS Gas Granular Flow Solver Predictions of Ejecta from Physics Focused Ground Test

NASA is preparing to return humans to the Moon to establish a sustained Lunar presence through the Artemis program. One area of concern for Lunar landers is the plume surface interaction (PSI) environment that poses several risks during a propulsive landing. Understanding the PSI environment caused by the landers is therefore important to designing successful landing missions. Towards this end, a two-phase, gas granular flow solver, Loci/GGFS, has been developed to predict the cratering and ejecta physics expected during a Lunar landing. The focus of this paper is on a validation assessment of Loci/GGFS predictions of ejecta with monodisperse glass beads (MGB). The validation assessment is performed with respect to the Physics Focused Ground Test 1 (PFGT1) conducted at NASA Marshall Space Flight Center (MSFC) in 2021. It is found that Loci/GGFS predicts similar initial cratering and ejecta features, with predictions of average velocities that are within 25% of experimental values.

Plume Surface Interaction↗
NASA NTRSDate not supplied

Transition Aero-Propulsive Analysis of a Tilt-Wing eVTOL Aircraft Using a Surface-Vorticity Solver

This work uses FlightStream, a surface-vorticity solver, to perform an aero-propulsive analysis on the NASA LA-8 aircraft through the transition flight regime. Aerodynamic force and moment coefficient predictions for forward and transition flight of the airframe without propulsors are compared with wind tunnel data. Powered transition cases are simulated using Conway actuator disks to model the propellers and results are compared with response surface equations derived from wind tunnel data. The approach described in the paper provides mid-fidelity solutions at a reduced computational cost compared to volumetric CFD, which allows for rapid transition flight analyses and optimization in the early design stages. The best prediction results were observed in forward flight and high-speed transition. Mid-transition results were not as close in magnitude but the trends exhibited reasonable agreement with experimental data.

Advanced Air Mobility↗
NASA NTRSDate not supplied

Initial Validation of a Gas-Granular Flow Solver Using a Subscale, Reduced Pressure Plume Surface Interaction Ground Test

With NASA’s goal to land the next humans on the lunar surface in the next few years, it is vitally important to have a better understanding of the plume surface interaction (PSI) between the landing vehicles and the lunar regolith. The Fluid Dynamics Branch at NASA/MSFC has previously used the gas-granular flow solver Loci/GGFS to qualitatively predict crater formation due to PSI effects in a lunar (near vacuum) ambient environment. In this paper, validation of Loci/GGFS crater width and depth predictions in ambient near-lunar conditions are provided using experimental data collected at MSFC during the Physics-Focused Ground Test 1 (PFGT-1) campaign in 2022. To observe sensitivity to soil models, simulations were conducted with both monodisperse glass bead (MGB) and BP-1 lunar regolith simulant soil models in Loci/GGFS. Crater depth and width comparisons are made with PFGT-1 Run 56, which used BP-1 soil. The Loci/GGFS BP-1 soil model performed slightly better with a mean predicted crater depth within 10% of the experiment. Both soil models predicted crater width within 10%. Cratering occurred more quickly with the MGB soil model. Mesh and spatial order sensitivity are also examined for the BP-1 soil model.

Validation↗
NASA NTRSDate not supplied

Wall-Modeled LES of a Swept Wing with Leading-Edge Ice Using LAVA Curvilinear, Unstructured, and Cartesian Solvers

Wall-modeled large-eddy simulation (LES) of a swept wing with leading-edge ice build up is performed using three mesh paradigms and associated flow solvers and compared to experimental results. The study focuses on an 8.9% scale model of the CRM65 swept wing featuring both high-fidelity and smooth leading-edge ice shapes. The assessment is conducted using the Launch, Ascent, and Vehicle Aerodynamics (LAVA) framework using the three actively supported meshing paradigms in LAVA: structured curvilinear overset, unstructured, andCartesian. For the iced configurations, these paradigms use hybrid body-fitted/source-term immersed-boundary, body-fitted, and ghost-cell immersed-boundary strategies, respectively.The unstructured and Cartesian mesh paradigms are particularly attractive for complex ice shapes as they avoid the manual mesh generation effort associated with the curvilinear approach. For the high-fidelity ice shape, good agreement with the experiment can be obtained with all three strategies; however, the curvilinear method is particularly sensitive to the source-term immersed-boundary timescale and span wise mesh resolution, and the Cartesian implementation is sensitive to the choice of numerical flux. For the smooth ice, larger discrepancies are observed across all methods. However, a mesh refinement study guided by flow visualizations leads to an improved comparison with the experiment that is particularly pronounced for the unstructured mesh paradigm.

TTT↗
NASA NTRSDate not supplied

Validation Assessment of Loci/GGFS Gas Granular Flow Solver Predictions of Ejecta From Physics Focused Ground Test

NASA is preparing to return humans to the Moon to establish a sustained Lunar presence through the Artemis program. One area of concern for Lunar landers is the plume surface interaction (PSI) environment that poses several risks during a propulsive landing. Understanding the PSI environment caused by the landers is therefore important to designing successful landing missions. Towards this end, a two-phase, gas granular flow solver, Loci/GGFS, has been developed to predict the cratering and ejecta physics expected during a Lunar landing. The focus of this paper is on a validation assessment of Loci/GGFS predictions of ejecta with monodisperse glass beads (MGB). The validation assessment is performed with respect to the Physics Focused Ground Test 1 (PFGT1) conducted at NASA Marshall Space Flight Center (MSFC) in 2021. It is found that Loci/GGFS predicts similar initial cratering and ejecta features, with predictions of average velocities that are within 25% of experimental values.

Plume Surface Interaction↗
NASA NTRSDate not supplied

Turbo-Design: Open-Source Radial Equilibrium Turbomachinery Solver: Part I - Turbines

Advances in 3D Geometrical Designs and Cooling have played a significant role in improving the efficiency of turbomachinery. However, these advancements must be effectively translated back to the modeler. Machine learning can facilitate this transition. Specifically, machine learning–based loss models can bridge the gap between 3D and 1D designs, enabling modelers not only to predict velocity triangles but also to extract additional geometric features. Currently, the design tools used at NASA have not been updated to support such integration—until now. TurboDesign is an open-source, Python-based framework that replaces TD2 (LEW-11029-1) and AXOD2 (LEW-16323-1), both of which are radial equilibrium solvers for axial turbines. The goal of this update is to enable the integration of machine learning loss models into radial equilibrium equations. Additionally, TurboDesign is designed to support radial machines. This paper presents the governing equations, the assumptions underlying the code, the integration of legacy loss models, an example of machine learning model integration, and a validation comparison with CFD. All code, tutorials, and documentation are available at: https://www.github.com/nasa/turbo-design

Radial Equilibrium↗
DOE OSTI2020

Actinide Mixing Optimization Solver

The Actinide Mixing Optimization Solver (AMOS) is a set of programs written in MATLAB that computes theoretical mixes of different uranium, plutonium, thorium, and other actinide materials given a list of isotopic reference materials. Constraints are applied depending on the desired product and a mixture is computed to meet the specified requirements. The optimal mixture consists of a product that uses the lowest possible number of initial actinide materials and has the lowest cost. AMOS is currently applied to particular reference material requests from the sponsoring agency (NNSA) on behalf of the IAEA.

Baldwin, Aaron Taylor↗
DOE OSTI2022

Novel Solver Algorithms for Nearly Singular Linear Systems Arising in Combustion Modelling

Direct Numerical Simulations of realistic combustion devices are extremely challenging due to the wide separation of scales in the simulation, for example an internal combustion (IC) engine chamber, and the flame thickness of a high-pressure flame. The PeleLMeX solver uses adaptive mesh refinement (AMR) to evolve multi-species reacting flows in the low Mach number limit at the Exascale and relies on an embedded boundary (EB) approach to represent complex geometries. In that framework, the EB geometries often give rise to very small cut-cells along the boundary, which translate into extreme ill-conditioning of the pressure-projection, with eigenvalues that span 15-16 orders of magnitude. In this talk, we focus on the case of a typical IC piston bowl geometry for which we present on a novel approach towards solving these nearly singular linear systems with ILU-based, C-AMG smoothers on massively parallel architectures. In particular, we use scaling and equilibration algorithms to handle the non-normality of the upper triangular factors. This enables us to approximate the highly sequential triangular solve algorithm, embedded in the AMG smoothing-solve phase, with Jacobi iterations. This approximation can be written as a convergent Neumann series whose terms are composed of highly parallel sparse matrix vector multiplications. The result is an algorithm that substantially decreases setup and solve time, compared to state-of-the-art, for these challenging linear systems.

combustion modelling↗
DOE OSTI2022

Implementation of Manifold-Based Combustion Models in a Highly Scalable Low Mach Number Reacting Flow Solver: Preprint

Manifold-based representations of the thermochemistry are often employed in conjunction with large eddy eimulation (LES) to lower the cost of combustion simulations. This work describes steps taken to implement this modeling approach in PeleLM, a scalable and performance-portable low Mach number flow solver. Most significantly, this includes adapting the projection method used by PeleLM to satisfy the mass conservation constraint for use with manifold-based models. The implementation is designed to be general across manifold-based models, including both those that employ traditional tabulation and those that employ neural networks. An initial demonstration for simple test cases is presented and will be used for performance assessment.

high-performance computing↗
DOE OSTI2023

symPACK: A GPU-Capable Fan-Out Sparse Cholesky Solver

Sparse symmetric positive definite systems of equations are ubiquitous in scientific workloads and applications. Parallel sparse Cholesky factorization is the method of choice for solving such linear systems. Therefore, the development of parallel sparse Cholesky codes that can efficiently run on today’s large-scale heterogeneous distributed-memory platforms is of vital importance. Modern supercomputers offer nodes that contain a mix of CPUs and GPUs. To fully utilize the computing power of these nodes, scientific codes must be adapted to offload expensive computations to GPUs. We present symPACK, a GPU-capable parallel sparse Cholesky solver that uses one-sided communication primitives and remote procedure calls provided by the UPC++ library. We also utilize the UPC++ "memory kinds" feature to enable efficient communication of GPU-resident data. We show that on a number of large problems, symPACK outperforms comparable state-of-the-art GPU-capable Cholesky factorization codes by up to 14x on the NERSC Perlmutter supercomputer.

Bellavita, Julian↗
DOE OSTI2023

Recent Advances in PyROS: The Pyomo Solver for Two-Stage Nonconvex Robust Optimization

The slides present recent algorithmic and implementation advances of the two-stage robust optimization (RO) solver PyROS, and a benchmarking study which demonstrates the utility of PyROS for two-stage RO problems. The advances include extensions of the scope of PyROS to models with uncertain variable bounds, improvements to the initializations of the subproblems used by the underlying cutting set algorithm, and extensions of the uncertainty set interfaces. The benchmarking study is performed on a library of over 8,500 instances, with variations in the nonlinearities, degree-of-freedom partitioning, uncertainty sets, and polynomial decision rule approximations. Overall, the results highlight the effectiveness of PyROS for obtaining robust solutions to optimization problems with uncertain equality constraints.

Sherman, Jason↗
DOE OSTI2023

Recent Advances in PyROS: The Pyomo Solver for Two-Stage Nonconvex Robust Optimization

The slides present recent algorithmic and implementation advances of the two-stage robust optimization (RO) solver PyROS, and a benchmarking study which demonstrates the utility of PyROS for two-stage RO problems. The advances include extensions of the scope of PyROS to models with uncertain variable bounds, improvements to the initializations of the subproblems used by the underlying cutting set algorithm, and extensions of the uncertainty set interfaces. The benchmarking study is performed on a library of over 8,500 instances, with variations in the nonlinearities, degree-of-freedom partitioning, uncertainty sets, and polynomial decision rule approximations. Overall, the results highlight the effectiveness of PyROS for obtaining robust solutions to optimization problems with uncertain equality constraints.

Sherman, Jason↗
DOE OSTI2024

Development of Segregated Thermal-Hydraulics Solvers in MOOSE

The simulation of fluid flows is an essential part of the design and analysis of nuclear systems. Algorithms able to simulate flows at different fidelity levels are available in the Multiphysics Object-Oriented Simulation Environment (MOOSE) and MOOSE-based applications such as Pronghorn \cite{novak2018pronghorn}, Pronghorn-Subchannel, RELAP-7, and SAM. Currently, significant effort is being invested in the development of coarse-mesh Computational Fluid Dynamics (CFD) capabilities within MOOSE and Pronghorn for the simulation of Generation IV nuclear reactors. Traditionally, the solution algorithms in MOOSE have relied on Newton or quasi-Newton methods (such as the preconditioned Jacobian-free Newton-Krylov method) where residuals and Jacobians (or approximations thereof) are constructed. Both Newton and quasi-Newton methods require the solution of a linear system at each nonlinear Newton iteration with the Jacobian as the system matrix. The Jacobian contains blocks originating from all variables in the problem (i.e., for thermal-hydraulics at least pressure, velocities, and temperature). Due to the formulation of the problem in a general multiphysics setting on unstructured mesh, creating a good preconditioner for the linear system can be challenging, thus many fluid applications have utilized direct solver-based methods such as LU factorization. However, with increasing system size and complexity in multi-dimensional problems, the direct solution of linear systems becomes computationally expensive both in execution time and and memory. For this reason, recent effort has focused on adapting segregated solution algorithms for CFD problems in MOOSE. These algorithms use fixed-point iteration between segregated systems whose assembly and preconditioning are easier those of the monolithic system. Initial results show that the segregated solution algorithm outperforms the monolithic approach in terms of memory usage and for large 3D problems in terms of CPU time as well.

42 ENGINEERING↗