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At least 469 records · Page 26

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NASA NTRSDate not supplied

Improved Heat Transfer Prediction for High-Speed Flows over Blunt Bodies using Adaptive Mixed-Element Unstructured Grids

Aerothermodynamic prediction is important for the design and analysis of many aerospace vehicles. Computational Fluid Dynamics (CFD) tools used for these predictions commonly rely on structured shock-aligned grids due to the strong shocks exhibited at high speeds. This work details the incorporation of an improved HLLE++ scheme for both perfect gas and thermochemical nonequilibrium flows which robustly captures shock waves on both non-shock-aligned and shock-aligned grids. The HLLE++ scheme reduces the impact of eigenvalue limiting on flow solutions which is required for Roe's scheme for high Mach number flows. An adapted grid approach is also demonstrated using mixed-element unstructured grids to improve heat prediction. Thin prismatic boundary layers are used with tetrahedra in the farfield and for capturing shock waves. Various results are presented for hypersonic flows over blunt bodies including cylinders, spheres, and capsules.

CFD↗

NASA NTRSDate not supplied

Improved Heat Transfer Prediction for High-Speed Flows over Blunt Bodies using Adaptive Mixed-Element Unstructured Grids

CFD↗

DOE OSTI2025

Sockeye Code Validation Against UNIST Heat Pipe - Poster - Internship 2025

Sockeye is an engineering level code being developed under the MOOSE framework for modeling heat pipes. A heat pipe is a sealed tube with a wick structure filled with a working fluid that transfers heat efficiently and passively via phase change of the working fluid. Heat applied to the evaporator end creates a pressure gradient which causes vapor to migrate to the condenser end where the vapor deposits its energy and condenses. Capillary force generated by the wick structure then draws the liquid back to the evaporator. A validation study was performed to compare the Sockeye code against data produced at the Ulsan National Institute of Standards and Technology for a slightly overfilled sodium heat pipe. The heat pipe was operated under natural convection cooling and a decreasing inactive length was observed. The experiment was modeled in Sockeye using the condenser pool model, the front non-condensable gas (NCG) model, and the mixture NCG model separately to reproduce the inactive length phenomenon. Also, a new capability was implemented in MOOSE to allow for conjugate heat transfer from the condenser based on the Churchill-Chu correlation for natural convection. The condenser pool model showed an increasing inactive length, demonstrating that the behavior was likely not caused by a pool of excess liquid. The front NCG model was able to show good agreement with the experiment, but it suffered convergence issues at the front. Finally, the mixture NCG model gave good results when the axial mesh was sufficiently refined. This work culminated in additions to the Sockeye documentation and a contribution to a journal article that will be published later. This poster is a summary of my work which I can take back to my university for presentation.

42 - ENGINEERING↗

NASA NTRS1990

Unsteady transonic Navier-Stokes computations for an oscillating wing using single and multiple zones

Modern jet transports and maneuvering tactical fighters operating in the transonic regime often give rise to time-dependent fluid physics that interact with flexible structural components, e.g., vortical flow, shocks, and separation. Efficient computational fluid dynamic (CFD) methods are required to study such computationally intensive problems. In this work a numerical method is presented to address this problem. Time-dependent, compressible, Navier-Stokes equations are used to simulate unsteady transonic flow about a three-dimensional rigid wing undergoing a forced periodic motion in angle of attack. An efficient, implicit, diagonal algorithm is utilized because of its low operation count per time step compared to other methods that solve systems of block matrix equations. The formal time accuracy is addressed theoretically and demonstrated numerically by comparison of computational results with experimental data. A zonal grid approach, capable of treating complex geometries, is presented and its time accuracy is demonstrated by comparing a zonal computation with a single grid computation and experimental data.

Chaderjian, Neal M.↗

NASA NTRS2019

Generation of a Reduced-Order Model of an Unmanned Combat Air Vehicle Using Indicial Response Functions

Within the NATO STO AVT-251 Task Group, a generic Unmanned Combat Air Vehicle (UCAV) planform was redesigned based on requirements derived from parts of the flight envelope of the defined mission. Because of the lambda-shape planform and associated flow phenomena including shocks and vortices, the aerodynamic design process relies heavily on high-fidelity predictions from computational fluid dynamics (CFD). These simulations enable accurate flight dynamics predictions, allowing for the identification of any potential performance issues early in the design process. Potentially, a complete flight dynamics model can be derived from CFD calculations provided that the underlying reduced order model (ROM) captures the underlying physics contained within the CFD results. This work investigates the creation of a nonlinear ROM using indicial response functions. The response functions are obtained using a grid motion approach that separates the effects of angle of attack and pitch rate. This approach is demonstrated using three different CFD codes from various organizations: ENSOLV at Royal Netherlands Aerospace Centre, USM3D at NASA Langley Research Center, and Kestrel at the United States Air Force Academy. ROM predictions were generated for a manoeuver resembling a low-speed pull-up. The predictions are found to be sensitive to the quality of the steady-state solutions from which step-response calculations were started, as well as the convergence of the step responses themselves. Nevertheless, the indicial response method is shown to provide aerodynamic predictions with acceptable accuracy including transient effects, and as such is a promising method for computationally efficient flight dynamics predictions.

Michel P.C. van Rooij↗

DOE OSTI2020

Model reduction for hypersonic aerodynamics via conservative LSPG projection and hyper-reduction

High-speed aerospace engineering applications rely heavily on computational fluid dynamics (CFD) models for design and analysis due to the expense and difficulty of flight tests and experiments. This reliance on CFD models necessitates performing accurate and reliable uncertainty quantification (UQ) of the CFD models. However, it is very computationally expensive to run CFD for hypersonic flows due to the fine grid resolution required to capture the strong shocks and large gradients that are typically present. Furthermore, UQ approaches are “many-query” problems requiring many runs with a wide range of input parameters. One way to enable computationally expensive models to be used in such many-query problems is to employ projection-based reduced-order models (ROMs) in lieu of the (high-fidelity) full-order model. In particular, the least-squares Petrov–Galerkin (LSPG) ROM (equipped with hyper-reduction) has demonstrated the ability to significantly reduce simulation costs while retaining high levels of accuracy on a range of problems including subsonic CFD applications. This allows computationally inexpensive LSPG ROM simulations to replace the full-order model simulations in UQ studies, which makes this many-query task tractable, even for large-scale CFD models. This work presents the first application of LSPG to a hypersonic CFD application. In particular, we present results for LSPG ROMs of the HIFiRE-1 in a three-dimensional, turbulent Mach 7.1 flow, showcasing the ability of the ROM to significantly reduce computational costs while maintaining high levels of accuracy in computed quantities of interest.

Fluid Dynamics↗

DOE OSTI2025

Learning and discovering multiple solutions using physics-informed neural networks with random initialization and deep ensemble

In this work we explore the capability of physics-informed neural networks (PINNs) to discover multiple solutions. Many real-world phenomena governed by nonlinear differential equations (DEs), such as fluid flow, exhibit multiple solutions under the same conditions, yet capturing this solution multiplicity remains a significant challenge. A key difficulty lies in providing appropriate initial conditions or guesses, as widely used time-marching schemes and Newton’s method are highly sensitive to these choices when solving complex computational problems. While machine learning models, particularly PINNs, have shown promise in solving DEs, their ability to capture multiple solutions remains underexplored. In this work, we propose a simple and practical approach using PINNs to learn and discover multiple solutions. We first demonstrate that PINNs, when combined with random initialization and deep ensemble method—originally developed for uncertainty quantification—can effectively uncover multiple solutions to nonlinear ordinary and partial DEs. Although training large ensembles of PINNs may appear computationally demanding, this can be done efficiently using vectorization techniques supported by modern deep learning frameworks, allowing many networks to be trained simultaneously. Our approach highlights the critical role of initialization in shaping solution diversity, addressing an often-overlooked aspect of machine learning for scientific computing. Furthermore, we propose utilizing PINN-generated solutions as initial conditions or initial guesses for conventional numerical solvers to enhance accuracy and efficiency in capturing multiple solutions. Extensive numerical experiments, including the Allen–Cahn equation and cavity flow, where our approach successfully identifies both stable and unstable solutions, validate the effectiveness of our method. These findings establish a general and efficient framework for addressing solution multiplicity in nonlinear DEs.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

CRN Modeling of Ammonia RQL Combustion using a Partially-Stirred Reactor Approach

Ammonia is a promising alternative to hydrogen with high energy density and favorable storage and transport characteristics. However low flammability and a propensity for high nitrogen oxide (NOx) emissions make direct utilization challenging. Recently, two-stage rich-quench-lean (RQL) combustion strategies have shown promise in achieving low NOx emissions with ammonia. In this approach, the rich stage serves to oxidize a portion of the fuel, while thermally decomposing as much of the remaining ammonia as possible, generating hydrogen. In the second (lean) stage, air is rapidly introduced, burning out the hydrogen and residual ammonia. Two-stage RQL combustion of ammonia has been investigated in the open literature both experimentally and numerically. In general, idealized chemical reactor network (CRN) models predict NOx concentrations below that of 2D/3D computational fluid dynamics models and experiments. The primary drivers of these discrepancies may be largely attributed to finite rate mixing non-adiabatic operation. The typical CRN model is comprised of a perfectly-stirred-reactor (PSR), followed by a plug-flow-reactor (PFR), meant to represent the flame, and post-flame zones, respectively. In the two-stage RQL approach two PSR-PFR networks are arranged sequentially, corresponding to the rich and lean stages, with secondary air injection in between. In the authors’ past work, this arrangement has demonstrated the significant sensitivity of exit NOx to the rich stage equivalence ratio, while the amount of secondary air injection was shown to be less critical. In this paper, the CRN model is extended to (1) include the impacts of heat loss and (2) utilize a partially-stirred-reactor (PaSR) approach to study the impacts of mixing on emissions performance. Varying amounts of heat loss are applied to the rich relaxation zone to understand emissions performance and changes to optimization of equivalence ratio and residence time. Premixed and non-premixed configurations are considered in the rich stage PaSR, with varying degrees of mixing intensity to study the interaction between mixing, transport, and kinetic timescales. Critically, the impact of mixing between hot products and secondary air injection is studied to understand practical injector needs. Results show unburnt ammonia leaving the rich stage as a primary contributor to NOx emissions – driven both by increased heat loss and reduced mixing rates. Furthermore, heat losses have shown to create conditions which are conducive to increased N2O formation in the lean stage. The results of this study will be considered in the context of developing optimized two-stage RQL combustors for ammonia..

advanced gas turbines↗

DOE OSTI2023

Development and evaluation of a skeletal mechanism for EHN additized gasoline mixtures in large Eddy simulations of HCCI combustion

Advanced Low Temperature Combustion modes, such as the Sandia proposed Additive-Mixing Fuel Injection (AMFI), can unlock significant potential to boost fuel conversion efficiency and ultimately improve the energy conversion of internal combustion engines. This is a novel improved combustion process that is enabled by supplying small (<5%) variable amounts of autoignition improver to the fuel to enhance the engine operation and control. Common, diesel-fuel ignition-quality enhancing additive, 2-ethylexyl nitrate (EHN), is doped into gasoline to enable Sandia LTGC + AMFI combustion. This manuscript focuses on the development of a reduced sub-mechanism for EHN chemical kinetics at engine relevant conditions that is implemented into a skeletal mechanism for chemical kinetic studies of gasoline surrogate fuels. The mechanism validation utilized zero-dimensional numerical simulations and comparison to shock tube ignition-delay data of pure and EHN-doped n-heptane. Additional validation is presented with Homogeneous Charge Compression-Ignition (HCCI) engine data of pure and EHN-doped research-grade E10 gasoline. Then, the mechanism was deployed in a 3-D computational fluid dynamics (CFD) using Large Eddy Simulations (LES) to model the HCCI engine experiments of 0.4% vol EHN additized E10 gasoline at several equivalence ratios. Simulations showed a very good performance of the mechanism, and the model accurately reproduced (a) the ignition point, (b) combustion phasing, (c) combustion duration, and (d) the peak of the heat release rates of the engine experiments. The results show that EHN promotes Low-Temperature Heat Release, ultimately driving the gasoline to autoignite at thermodynamic conditions where the fuel would not otherwise ignite. Overall, this work demonstrates a viable reduced chemical-kinetic mechanism for EHN and shows that it can be combined with a skeletal gasoline mechanism for CFD-LES analysis of well-mixed LTGC that matches well with experimental results. The CFD-LES analysis also shows the spatial distribution of EHN-fuel interactions that control the autoignition throughout the combustion chamber.

Guleria, Gaurav↗

NASA NTRSDate not supplied

Effect of anisotropic mesh adaptation on surface pressure predictions for atmospheric entry simulations.

Recently, a metric-based mesh adaptation capability has been developed for the advanced compressible flow solver US3D. Metric-based mesh adaptation is a solution informed mesh adaptation strategy that typically improves the resolution of the mesh along anisotropic flow features, like strong shock waves or shear layers. An anisotropic error indicator is reconstructed based on a provided Computational Fluid Dynamics (CFD) solution which prescribes the locally desired element size and orientation. The benefits of this mesh adaptation strategy is twofold: first, it simplifies the manual meshing labor that typically needs to be carried out by the CFD engineer because the mesh adaptation is informed by the provided solution. Second, the computational cost is kept to a minimum while improving the resolution of the simulation. The aim here is to demonstrate how anisotropic mesh adaptation can be employed to improve the predictions of surface pressure for atmospheric entry vehicles. In this work, we compare CFD simulations that use this newly developed anisotropic mesh adaptation capability for US3D with pressure data that was collected by Mars Entry, Descent, and Landing Instrumentation 2 (MEDLI2) during the atmospheric entry phase of Mars2020.

D. Ekelschot↗

NASA NTRSDate not supplied

Effect of Anisotropic Mesh Adaptation on Surface Pressure Predictions for Atmospheric Entry Simulations

A metric-based mesh adaptation capability has been developed for the advanced compressible flow solver US3D. Metric-based mesh adaptation is a solution informed mesh adaptation strategy that improves the resolution of the mesh along anisotropic flow features, like strong shock waves or shear layers. An anisotropic error indicator is reconstructed based on a provided Computational Fluid Dynamics (CFD) solution which prescribes the locally desired element size and orientation. The benefits of this mesh adaptation strategy is twofold: first, it simplifies the manual meshing labor that typically needs to be carried out by the CFD engineer because the mesh adaptation is informed by the provided solution. Second, the computational cost is kept to a minimum while improving the resolution of the simulation. The aim here is to demonstrate how anisotropic mesh adaptation can be employed to improve the predictions of surface pressure for atmospheric entry vehicles. In this work, we compare CFD simulations that use this newly developed anisotropic mesh adaptation capability for US3D with pressure data that was collected by Mars Entry, Descent, and Landing Instrumentation (MEDLI2) suite.

Dirk Ekelschot↗

NASA NTRS2016

Towards an Entropy Stable Spectral Element Framework for Computational Fluid Dynamics

Entropy stable (SS) discontinuous spectral collocation formulations of any order are developed for the compressible Navier-Stokes equations on hexahedral elements. Recent progress on two complementary efforts is presented. The first effort is a generalization of previous SS spectral collocation work to extend the applicable set of points from tensor product, Legendre-Gauss-Lobatto (LGL) to tensor product Legendre-Gauss (LG) points. The LG and LGL point formulations are compared on a series of test problems. Although being more costly to implement, it is shown that the LG operators are significantly more accurate on comparable grids. Both the LGL and LG operators are of comparable efficiency and robustness, as is demonstrated using test problems for which conventional FEM techniques suffer instability. The second effort generalizes previous SS work to include the possibility of p-refinement at non-conforming interfaces. A generalization of existing entropy stability machinery is developed to accommodate the nuances of fully multi-dimensional summation-by-parts (SBP) operators. The entropy stability of the compressible Euler equations on non-conforming interfaces is demonstrated using the newly developed LG operators and multi-dimensional interface interpolation operators.

Carpenter, Mark H.↗

DOE OSTI2020

A scalable approach of using biomass derived glycerol to synthesize cathode materials for lithium-ion batteries

Glycerol, a main byproduct of biodiesel, was used as the fuel agent in a scalable flame-assisted spray pyrolysis approach to synthesize micron-size cathode materials. Single droplet combustion, particle morphology, and electrochemical performance were examined considering the effects of salt concentration, water addition, and post-annealing time on synthesizing Li(Ni 1/3 Co 1/3 Mn 1/3 )O 2 (NCM111) cathode materials. Single droplet tests showed that a sufficient amount of water in the glycerol-based precursor could delay droplet inflation and ignition. Moreover, using a two-fluid atomization nozzle, spray tests demonstrated that adding water would result in less wrinkled and more uniform particles. Nevertheless, increasing water proportion in the precursor could reduce the reaction heat, resulting in that samples prepared with water addition needed longer post-annealing time to improve their electrochemical performance. Using the precursor without water, the best performed NCM111 cathode material was synthesized with only 2 h of post-annealing. It has a discharge capacity of 163.3 mAh/g at 0.1C and 85.5% capacity retention at 1C after 100 cycles. Furthermore, the current work confirmed the capability of using glycerol as a sustainable fuel agent to synthesize NCM111 cathode materials, and also provided basic conditions for the development of large-scale production in the future.

25 ENERGY STORAGE↗

DOE OSTI2025

Iodine recombination in xenon solvent: Clusters in the gas to liquid-like state transition

Supercritical fluids (SCFs) have attracted significant attention as solvents for chemical reactions due to their unique properties, such as high diffusivity, low viscosity, and tunable solvation properties. These properties profoundly influence reaction kinetics and are often attributed to the formation of molecular clusters within SCFs. To study the effect of supercritical solvent on chemical reactivity and dynamics of reactions, one needs to understand the dynamics of clusters in supercritical fluid. Extensive experiments on the photodissociation and recombination of iodine in supercritical fluids served as a model system for understanding these effects. Experimental studies have been complemented by theoretical and computational investigations, which mostly employ Monte Carlo or empirical molecular dynamics simulations. However, computational studies using non-reactive force fields and ab initio approaches present challenges in capturing reactive processes at larger scales within supercritical fluids. Here, in this work, we developed the ReaxFF parameters by training against quantum mechanics data. ReaxFF reactive force field based molecular dynamics simulations were performed, studying the dynamics of a xenon solvent and cage effect at different thermodynamic conditions for the iodine recombination reaction. We show that the conditions near the critical point are the optimal conditions to study the cage effect. We show that the average lifetime of xenon clusters ranging between 5 and 11 ps is comparable to iodine geminate recombination. Our simulation results of iodine recombination in xenon solvent demonstrate the higher probability of iodine molecule formation in the presence of xenon clusters. Finally, we show that the supercritical condition exhibits the highest recombination rate for iodine atoms.

Cage effect↗

NASA NTRS1979

Transient shutdown analysis of low-temperature thermal diodes

The various thermal diodes available for use in cryogenic systems are described. Two diode types, liquid-trap and liquid-blockage diodes, were considered to be the most attractive, and thermal models were constructed to predict their behavior in the reverse mode. The diodes, which are of similar size and throughput, were also examined experimentally in a parallel test setup under nominally identical conditions. Their characteristics were ascertained in terms of forward-mode and reverse-mode conductances, shutdown times and energies, and recovery to forward-mode operation with ethane as the working fluid in the temperature range 170 K to 220 K. Results show that the liquid-blockage diode is the quicker of the two diodes to shut down from the forward mode (8 min as opposed to 10 min). However, the liquid-blockage diode has a larger reverse-mode conductance which results in a greater overall evaporator temperature rise. The importance of the relative size and heat inputs to the condenser/reservoir configuration of the liquid-blockage diode and the evaporator trap configuration for the liquid-trap diode are demonstrated. Also included are data which show the susceptibility of the diodes to recovery to forward-mode operation. Guidelines for the choice of a particular diode for an actual application are given.

Williams, R. J.↗

NASA NTRS1996

Design of the Heat Receiver for the U.S./Russia Solar Dynamic Power Joint Flight Demonstration

A joint U.S./Russia program is being conducted to develop, fabricate, launch, and operate a solar dynamic demonstration system on Space Station Mir. The goal of the program is to demonstrate and confirm that solar dynamic power systems are viable for future space applications such as the International Space Station Alpha The major components of the system include a heat receiver, a closed Brayton cycle power conversion unit, a power conditioning and control unit, a concentrator, a radiator, a thermal control system, and a Space Shuttle Carrier. This paper discusses the design of the heat receiver component. The receiver comprises a cylindrical cavity, the walls of which are lined with a series of tubes running the length of the cavity. The engine working fluid, a mixture of xenon and helium, is heated by the concentrated sunlight incident on these tubes. The receiver incorporates integral thermal storage, using a eutectic mixture of lithium fluoride and calcium difluoride as the thermal storage solid-to-liquid phase change materiaL This thermal storage is required to enable power production during eclipse. The phase change material is contained in a series of individual containment canisters.

Strumpf, Hal J.↗

DOE OSTI2026

thornado+FLASH-X: A Hybrid Discontinuous Galerkin–Implicit-explicit and Finite-volume Framework for Neutrino-radiation Hydrodynamics in Core-collapse Supernovae

We present neutrino-transport algorithms implemented in the toolkit for high-order neutrino-radiation hydrodynamics (thornado) and their coupling to self-gravitating hydrodynamics within the adaptive mesh refinement–based multiphysics simulation framework FLASH-X. thornado, developed primarily for simulations of core-collapse supernovae (CCSNe), employs a spectral, six-species two-moment formulation with algebraic closure and special-relativistic observer corrections accurate to $\mathcal{O}(v/c)$, and uses discontinuous Galerkin (DG) methods for phase-space discretization combined with implicit-explicit time stepping. A key development is a nonlinear neutrino–matter coupling algorithm based on nested fixed-point iteration with Anderson acceleration, enabling fully implicit treatment of collisional processes, including energy-coupling interactions such as neutrino–electron scattering and pair production. Coupling to finite-volume (FV) hydrodynamics is achieved through a hybrid DG-FV representation of the fluid variables and operator-split evolution within FLASH-X. The implementation is verified using basic transport tests with idealized opacities and relaxation and deleptonization problems with tabulated microphysics. Spherically symmetric CCSN simulations demonstrate accuracy and robustness of the coupled scheme, including close agreement with the CCSN simulation code Chimera. An axisymmetric CCSN simulation further demonstrates the viability of DG-based neutrino transport for multidimensional supernova modeling within FLASH-X. thornado’s neutrino-transport solver is GPU-enabled using OpenMP offloading or OpenACC, and all CCSN applications included in this work use the GPU implementation. Together, these results establish a foundation for future enhancements in physics fidelity, numerical algorithms, and computational performance, for increasingly realistic large-scale CCSN simulations.

Endeve, Eirik [Oak Ridge National Laboratory (ORNL↗

NASA NTRSDate not supplied

Demonstration of Fluid Dynamics for Plant Growing Systems in Varied Gravity Environments Through Scaled Capillary Models

The development of reliable and bioregenerative crop growth production systems is vital for human exploration into deep space. As humans prepare for space travel beyond LEO, scientists need to find a way to provide reliable and adequate water delivery for all stages of the plant's life cycle. Past production systems struggled with this and often led to overwatering in the system. To better understand this issue, NASA's Plant Water Management (PWM) experiments were able to model fluid flow through granular substrates, specifically a clay-based material arcilite, in 0-G. The PWM study can help researchers to predict fluid flow through the systems, however their model only works for an arcilite based system and was unable to account for different stages of plant growth. For future missions, payload requirements to support crop production system will need to be limited, leading to the use of in situ resources. This project aims to validate the PWM experiments as well as incorporate various materials into the design for growth systems. To meet these objectives, a series of terrestrial experiments will be deployed to mimic all gravities. By modifying the material, fluid, and size of the test subjects, the effect of Earth's gravity can be minimized. This project will aid researchers in the design of future crop production systems for surface missions by creating a refined model that can be used at all stages of plant growth and utilize in situ resources.

Plant Biology↗