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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.

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At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Accelerating transients with NekRS: GPU overlapping domain implementation and multi-rate timestepping

The simulation of nuclear transients using Computational Fluid Dynamics (CFD) presents significant computational challenges due to the inherent complexity and the wide separation in temporal scales between various flow physical phenomena. These disparities lead to high computational costs, often making the simulation of transients impractical without advanced techniques. Consequently, multiple research initiatives are being pursued by the NEAMS thermal-hydraulic area, some driven by academic institutions and some by national laboratories. Overall, they are exploring novel methods to make transient simulations more feasible and efficient. This report delves into recent advancements within the CFD code NekRS, specifically those achieved in Fiscal Year 2024 under the CONNECT effort, aimed at improving the performance and feasibility of transient simulations. The first major advancement involves the porting of NekRS to Aurora, one of the Department of Energy’s (DOE) most powerful supercomputers. Additionally, the report discusses the implementation of an overlapping domain capability within NekRS. This novel GPU-accelerated capability allows different spatial regions of the domain to be solved independently, enhancing the code’s efficiency, particularly when running large-scale simulations in complex domains. The scalability of this approach is demonstrated, highlighting its potential to transform how transients are approached in CFD simulations. Lastly, the report focuses on how this overlapping domain capability specifically accelerates transient simulations through multi-rate timestepping. By decoupling different regions and facilitating faster computations, this method offers a promising pathway to making nuclear transient simulations more computationally feasible, addressing one of the critical bottlenecks in the field. Together, these advancements represent a significant leap forward in transient simulation technology, bringing closer the possibility of handling highly complex nuclear scenarios with greater efficiency and accuracy.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1994

Target compressions by working fluids driven with solid liner implosions

Compression by a spherical solid liner of a gold target surrounded by a hydrogen plasma is simulated. Two-dimensional simulations that treat only a subset of the physics included in the one-dimensional code were performed in an attempt to assess multidimensional effects. A one-dimensional numerical code has been developed to study the effects of thermal radiation and conduction. Results of pressure, density, and energy deposited for different initial plasma conditions are presented and discussed. Results from both one- and two-dimensional codes show that the average target density at peak compression is 39-43 g/cu cm, using the SHIVA Star facility at 90 kV discharge.

Chiang, P.-R.↗
DOE OSTI2025

Deconvoluting thermomechanical effects in X-ray diffraction data using machine learning

X-ray diffraction is ideal for probing the sub-surface state during complex or rapid thermomechanical loading of crystalline materials. However, challenges arise as the size of diffraction volumes increases due to spatial broadening and because of the inability to deconvolute the effects of different lattice deformation mechanisms. Here, we present a novel approach that uses combinations of physics-based modeling and machine learning to deconvolve thermal and mechanical elastic strains for diffraction data analysis. The method builds on a previous effort to extract thermal strain distribution information from diffraction data. The new approach is applied to extract the evolution of the thermomechanical state during laser melting of an Inconel 625 wall specimen which produces significant residual stress upon cooling. A combination of heat transfer and fluid flow, elasto-plasticity and X-ray diffraction simulations is used to generate training data for machine-learning (Gaussian process regression, GPR) models that map diffracted intensity distributions to underlying thermomechanical strain fields. First-principles density functional theory is used to determine accurate temperature-dependent thermal expansion and elastic stiffness used for elasto-plasticity modeling. The trained GPR models are found to be capable of deconvoluting the effects of thermal and mechanical strains, in addition to providing information about underlying strain distributions, even from complex diffraction patterns with irregularly shaped peaks.

36 MATERIALS SCIENCE↗
NASA NTRS1990

Coupled effects of conduction in the crystal and thermo-solutal convection in a rectangular inclined enclosure

To date modeling of crystal growth of optoelectronic materials using Physical Vapor Transport has been limited to the study of the fluid phase. To achieve it, the equations of coupled heat, mass and momentum transfer in the gas have to be solved. The first objective of this study is to examine the effect of heat conduction in the crystal on the fluid flow in the neighborhood of the interface. Heat transfer boundary conditions on both interfaces were modified to take into account the additional heat flux between gas and solid. It is proved that heat conduction does not affect the fluid flow. In the presence of gravity, density gradients in the fluid phase generate convection responsible for the problem of a nonplanar growth of the interface. The second objective is to study systematically under one-g the different possible flows in order to solve this problem. Depending on the parameters, a diffusive mode and three convective modes (thermal, solutal and thermo-solutal) are observed. The competition between thermal and solutal convections leads to a mathematical condition which can be used to achieve a planar growth. It is proven that, under the physical conditions chosen, this mathematical condition cannot be thermodynamically satisfied.

Mennetrier, Christophe↗
DOE OSTI2022

SAM-ML: Integrating data-driven closure with nuclear system code SAM for improved modeling capability

Advanced reactors often involve complicated thermal-fluid (T-F) phenomena. Modeling such phenomena with the traditional one-dimensional (1-D) system code is a challenging task. The System Analysis Module (SAM), a modern nuclear system code, has developed a coarse mesh multi-dimensional (multi-D) flow model to capture the spatial effect of T-F phenomena in advanced reactors. As a coarse mesh solver, constitutive relations are required for SAM's multi-D model for unresolved fine-scale physics, such as turbulence. Here this work presents a novel approach that integrates neural networks as data-driven closure for SAM's multi-D flow model. The data-driven closure is trained with fine-resolution data to ensure its accuracy while maintaining a coarse mesh setup to ensure its efficiency and consistency with SAM. We demonstrate the applicability of this SAM-ML capability in an open volume thermal stratification problem, where a neural network model serves as the eddy viscosity closure. A customized interface between the neural network and SAM is developed to ensure flexible and efficient data exchange. The SAM-ML results demonstrate superior performance compared to SAM's built-in zero-equation eddy viscosity closure. The case study shows that although the generalization capability of the data-driven closure still needs to be improved for different transient case or different geometric setup, SAM -ML demonstrates good potential for challenging simulation problems with improved accuracy and computational efficiency.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Finite element modeling of electropolishing of radio frequency dipole Nb crab cavity in hydrofluoric-sulfuric acid electrolyte

The superior performance of niobium superconducting radio frequency (SRF) cavities is achieved through meticulous surface treatment, notably via chemical electropolishing, ensuring exceptionally smooth surfaces. While this technique has been extensively employed for cylindrically symmetric structures, addressing more intricate geometries poses significant challenges in achieving uniform polishing and controlled material removal, especially when moving away from retractable cathodes. This presents a multifaceted electrochemical, thermal, and fluid dynamics conundrum. A prime example is the 197 MHz radio frequency dipole (RFD) crabbing cavity proposed for the Electron Ion Collider (EIC) project, exemplifying such complex structures. Our groundbreaking work integrates the localized oxide thickness variation, considering its impact on current distribution and Joule heating, within the framework of multi-physics modeling using the COMSOL® simulation suite. This approach was applied to a comprehensive model of the RFD cavity, allowing us to investigate optimal external cooling water flow conditions necessary for achieving desirable outcomes. In conclusion, this illustrates the increasing utility of such multi-physics codes to greatly aid in designing solutions to challenging processing requirements for increasingly complex accelerator cavities.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Implementation and verification of a model linearized multi-species collision operator in the COGENT code

We implement the multi-species linearized model collision operator, based on the approach proposed by Kolesnikov, in the full-f continuum gyrokinetic code COGENT. We describe the operator and use it in several COGENT simulations of highly collisional plasmas. We analyze simulation results with the Braginskii fluid model to illustrate that COGENT recovers both friction and thermal forces. Finally, we simulate the neoclassical transport of heavy impurities with COGENT and illustrate agreement with previously published theoretical results.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Non-conformal attractor in boost-invariant plasmas

We study the dissipative evolution of (0+1)-dimensionally expanding media with Bjorken symmetry using the Boltzmann equation for massive particles in relaxation-time approximation. Breaking conformal symmetry by a mass induces a non-zero bulk viscous pressure in the medium. It is shown that even a small mass (in units of the local temperature) drastically modifies the well-known attractor for the shear Reynolds number previously observed in massless systems. For generic nonzero particle mass, neither the shear nor the bulk viscous pressure relax quickly to a non-equilibrium attractor; they approach the hydrodynamic limit only late, at small values of the inverse Reynolds numbers. Only the longitudinal pressure, which is a combination of thermal, shear and bulk viscous pressures, continues to show early approach to a far-off-equilibrium attractor, driven by the rapid longitudinal expansion at early times. Second-order dissipative hydrodynamics based on a gradient expansion around locally isotropic thermal equilibrium fails to reproduce this attractor.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1986

Numerical modeling of physical vapor transport in a vertical cylindrical ampoule, with and without gravity

Numerical modeling has been performed of the fluid dynamics in a prototypical physical vapor transport crystal growing situation. Cases with and without gravity have been computed. Dependence of the flows upon the dimensionless parameters aspect ratio and Peclet, Rayleigh, and Schmidt numbers is demonstrated to a greater extent than in previous works. Most notably, it is shown that the effects of thermally-induced buoyant convection upon the mass flux on the growth interface crucially depend upon the temperature boundary conditions on the sidewall (e.g., whether adiabatic or of a fixed profile, and in the latter case the results depend upon the shape of the profile assumed).

Miller, T. L.↗
DOE OSTI2021

Development of five-moment two-fluid modeling for Z-pinch physics

The Z-pinch m = 0 instability as well as its stabilization by radially sheared axial flow is studied using the nonlinear ideal five-moment twofluid (5M2F) model with an extension of that model to include Braginskii heat and momentum transport. Using the ideal 5M2F model, linear growth rate results are compared with prior work using MHD and Hall MHD. At small normalized wavenumber, 1 < k a < 4 , where a is the effective pinch radius, 5M2F results agree with Hall MHD within 20% in scenarios without radially sheared axial flow. With the sheared flow and focusing on ka = 10/3, agreement with Hall MHD is excellent. In the limit of small ion inertial length, results also match with MHD. A comparison with PIC modeling of shear-free m = 0 stability focuses on a plasma scenario based on recent experimental results. In a scan of mode wavenumber, ideal 5M2F results are qualitatively similar to PIC: the growth rate rises to a peak at a moderate wavenumber and declines at a large wavenumber in contrast to MHD results, which show the saturation of the growth rate with the increasing wavenumber rather than a decline. The peak normalized 5M2F growth rate is &#x3B3; &#x3C4; A = 1.5 , where sA is the Alfven transit time across the pinch. The peak occurs at normalized wavenumber ka = 10. For comparison, PIC results have a peak growth of &#x3B3; &#x3C4; A = 0.77 at ka = 5. Including Braginskiibased closure of the 5M2F model does not qualitatively change the ideal results in this particular case. Nonlinear saturation is studied using the 5M2F model with the dissipative Braginskii-based closure in cases with pinch-edge sheared-flow speed equal to half the Alfven speed. Nonlinear mixing due to the sheared flow yields a quasi-steady state after modest losses of pinch ion inventory and pinch thermal energy, approximately 30% and 10%, respectively. 5M2F modeling captures the essential physics of m = 0 instability and offers a computationally tractable route to high-fidelity modeling of 3D Z-pinch behavior, including m = 1 instability.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Optimization of WAAM Process to Produce AUSC Components with Increased Service Life

Additive manufacturing has the potential to revolutionize industrial hardware and unlock efficiency gains through the fabrication of geometries and architectures not possible by conventional processing. Wire Arc Additive manufacturing (WAAM) process is a class of directed energy deposition process enabling higher build rate and allowing custom wire feedstock allowing spatial variation of microstructure. The larger spot size and lower speed creates a larger melt pool, reducing residual stress and often time creating directional/columnar microstructure for Ni-superalloy. The use of flexible platform provides freedom in deposition strategy, which can accommodate complex substrates, including feature addition onto existing structures, non-flat layers, and repair methods. However, the certification of the final component needs to match the strength requirement. Hence, the quality of the component produced is stringently monitored to avoid buildup of residual stress, cracks, porosity and to reduce detrimental segregated phases commonly observed during alloy solidification. Simulation plays a huge role in predicting the melt pool dimension and can be used to optimize the process parameter. Similar development is also required to perform physics-based modeling of microstructural development in WAAM that can predict the microstructural features during solidification and can be used to optimize the process more effectively. To move toward this goal, Raytheon Technologies Research Center together with Siemens worked to create a set of computational tools to control the process parameters, enable on-line measurements and acquisition with feedback to the optimized process parameters, and eventually track material evolution through each step of the additive process. Computational fluid dynamics is used for accurate prediction and calibration of the thermal field during WAAM process. and phase field models for microstructure evolution as a function of processing parameters to establish a connection between additive parameters and the final microstructure. Here we report cellular automata (CA) model development to predict the dendritic microstructure evolution with surface and bulk nuclei for single track and multiple layers. The CA model was developed to account for secondary element addition and predict segregation, local melting, and latent heat release as well as prediction of Euler angles from orientation information and validated against experiments. This framework was utilized to tailor spatially-varying composition in a part by appropriately controlling the microstructure evolution during the additive process. Functionally graded Haynes 282 alloy with high Cr content at the surface was tested for oxidation and mechanical properties. An advanced physics-based reaction-diffusion model predicting the simultaneous creation of chromium oxide and alumina is developed and validated to extend life expectancy of the WAAM manufactured high temperature part. A machine-learning data-driven framework establishing the process-structure relationship from a dataset of real microstructure images and corresponding process history data has been developed and implemented in the NX Siemens design system. The digital twin configuration along with the tool path generation enabled prediction of WAAM component buildup time and the techno-economic analysis provided a favorable option for all 4 cases with 15-40% cost reduction.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRSDate not supplied

Single and Multi-Node Modeling of Direct, Submerged, and Self-Pressurization of A Cryogenic Propellant Tank Using Nodal Tools

The pressurization of cryogenic propellant tanks will always be an important process so long as cryogenic liquids are being considered as fuel sources or used for other in-space applications. Pressure control of the tank ullage is necessary for managing propellant flowrates to an engine or a receiver tank, and modeling of the process is used to predict the pressurant requirements and the amount of propellant boiloff. Direct ullage pressurization is the more traditional approach to tank pressurization, as the physics are straight-forward, and ample test (flight) data have been collected and analyzed over the past several decades. Submerged injection pressurization is an alternate method for tank pressurization and has been shown to reduce pressurant requirements, subcool the propellant, and reduce the risk of ullage collapse. Additionally, the pressurant gas entering the ullage is usually much colder when using the submerged pressurization approach, resulting in reduced propellant boiloff. These benefits are at the expense of vaporizing a small percentage of the propellent. Both tank pressurization methods are viable options for current and future space missions, and it is important to have the capability of analyzing the tank ullage conditions for both approaches. Our previous work has demonstrated the development of a Generalized Fluid System Simulation Program (GFSSP) model, which contains a thermodynamic equilibrium heat and mass transfer subroutine capable of effectively analyzing both direct and submerged pressurization systems [1-2]. This subroutine has most recently been enhanced to include the non-equilibrium effect of pressurant dissolution into the propellant. To date the ullage has always been represented as a single node, and although the simulated single-node temperatures have good comparison with the volume-averaged ullage temperatures computed from test data, the physics of the thermal stratification in the ullage were never captured, and adjustment factors in the model were required. The purpose of this paper is to introduce the development of a multi-node ullage model using GFSSP and to discuss the improvements of the simulated ullage temperature distribution and its resulting effects on ullage heat transfer processes. Test data from the Cryogenic Propellant Storage and Transfer Engineering Developmental Unit (CPST EDU) was used for model validation. For additional comparison, a Thermal Desktop (TD) model was also developed to analyze the CPST EDU direct ullage pressurization tests using both a single node and multi-node approach. The model includes the direct pressurant line, vent line, fill/drain line, and a TD FloCAD Compartment. The TD FloCAD Compartment is employed to represent the liquid and ullage as single volumes inside the tank, to include a liquid/vapor interface, and to generate network level objects such as lumps (analogous to nodes in GFSSP), paths, and ties between the fluid and thermal elements. An established heat load on the model tank was leveraged from a pre-existing higher-fidelity model correlated to CPST EDU test data.

pressurization↗
NASA NTRS1992

Liquid lubricants for advanced aircraft engines

An overview of liquid lubricants for use in current and projected high performance turbojet engines is discussed. Chemical and physical properties are reviewed with special emphasis placed on the oxidation and thermal stability requirements imposed upon the lubrication system. A brief history is given of the development of turbine engine lubricants which led to the present day synthetic oils with their inherent modification advantages. The status and state of development of some eleven candidate classes of fluids for use in advanced turbine engines are discussed. Published examples of fundamental studies to obtain a better understanding of the chemistry involved in fluid degradation are reviewed. Alternatives to high temperature fluid development are described. The importance of continuing work on improving current high temperature lubricant candidates and encouraging development of new and improved fluid base stocks are discussed.

Loomis, William R.↗
NASA NTRS1993

Liquid lubricants for advanced aircraft engines

An overview of liquid lubricants for use in current and projected high performance turbojet engines is discussed. Chemical and physical properties are reviewed with special emphasis placed on the oxidation and thermal stability requirements imposed upon the lubrication system. A brief history is given of the development of turbine engine lubricants which led to the present day synthetic oils with their inherent modification advantages. The status and state of development of some eleven candidate classes of fluids for use in advanced turbine engines are discussed. Published examples of fundamental studies to obtain a better understanding of the chemistry involved in fluid degradation are reviewed. Alternatives to high temperature fluid development are described. The importance of continuing work on improving current high temperature lubricant candidates and encouraging development of new and improved fluid base stocks are discussed.

Loomis, William R.↗
NASA NTRSDate not supplied

Comparisons of CFD Simulations of Icing Wind Tunnel Clouds with Experiments Conducted at the NASA Propulsions Systems Laboratory

This paper evaluates simulation predictions against experimental test data of icing clouds that were produced during 2018 ice crystal icing physics tests conducted at the NASA Propulsion Systems Laboratory icing wind tunnel. Aero-thermal and cloud parameters are set and known upstream at the tunnel inlet and spray system, but change as the cloud and air thermodynamically interact as the flowing masses reach the tunnel test section. Utilizing the ANSYS Fluent Discrete Phase Model function, 3D computational fluid dynamics (CFD) simulations were performed, capturing the thermodynamic interactions between the test parameters, and providing predictions of the aero thermal and cloud conditions at the tunnel test section. Simulation predictions were compared with test data that were measured at the tunnel exit plane. Evaluations focused on the cloud concentration (total water content), humidity content, and air temperature. CFD simulation predictions showed areas of agreement and disagreement. Simulations showed that cloud concentration profiles at the test section are strongly related to the initial spray nozzle pattern used at the tunnel inlet. Experimental data suggest that greater dispersion of the cloud occurred as the simulated cloud predicted areas of high and low cloud concentration compared to test data profiles. Simulations, however, captured the magnitude and location of the change in humidity content and the change in air temperature due to the presence of the cloud reasonably well, when compared to test data. This result would suggest that while the ANSYS simulation did not fully predict the spreading of the cloud as measured during experiment, it did capture evaporation and the molecular movements of air and vapor relatively well.

CFD↗
NASA NTRSDate not supplied

Comparisons of CFD Simulations of Icing Wind Tunnel Clouds with Experiments Conducted at the NASA Propulsions Systems Laboratory

This paper evaluates simulation predictions against experimental test data of icing clouds that were produced during 2018 ice crystal icing physics tests conducted at the NASA Propulsion Systems Laboratory icing wind tunnel. Aero-thermal and cloud parameters are set and known upstream at the tunnel inlet and spray system, but change as the cloud and air thermodynamically interact as the flowing masses reach the tunnel test section. Utilizing the ANSYS Fluent Discrete Phase Model function, 3D computational fluid dynamics (CFD) simulations were performed, capturing the thermodynamic interactions between the test parameters, and providing predictions of the aero thermal and cloud conditions at the tunnel test section. Simulation predictions were compared with test data that were measured at the tunnel exit plane. Evaluations focused on the cloud concentration (total water content), humidity content, and air temperature. CFD simulation predictions showed areas of agreement and disagreement. Simulations showed that cloud concentration profiles at the test section are strongly related to the initial spray nozzle pattern used at the tunnel inlet. Experimental data suggest that greater dispersion of the cloud occurred as the simulated cloud predicted areas of high and low cloud concentration compared to test data profiles. Simulations, however, captured the magnitude and location of the change in humidity content and the change in air temperature due to the presence of the cloud reasonably well, when compared to test data. This result would suggest that while the ANSYS simulation did not fully predict the spreading of the cloud as measured during experiment, it did capture evaporation and the molecular movements of air and vapor relatively well.

CFD↗
NASA NTRS2019

SINDA/FLUINT and Thermal Desktop Multi-Node Settled and Unsettled Propellant Tank Modeling of Zero Boil Off Test

Cryogenic propellant storage tank self-pressurization involves complex physical phenomena which are usually analytically modelled via complex multidimensional CFD codes. Unfortunately these codes, even when modelling axisymmetric domains, may takes weeks or longer to obtain transient pressure and temperature information for relatively short periods of time (several seconds to several hours). Propellant tank storage end-to-end mission simulations can last a duration of days to weeks to months. Multi-node modelling of propellant tanks is a viable alternative to traditional CFD modelling and presents the advantage of greatly reduced run times on the order of hours and days compared to the weeks or longer for CFD codes. A multi-node model represents the fluid within the storage tank, as well as the storage tank itself, as a fluid-thermal network. This type of setup is not necessarily geometrically based. This can be accomplished using a commercial generalized fluid-thermal network code, such as SINDA/FLUINT (SF). The advantage of using a fluid-thermal network code like SF lies in its extensive ability to model the external environment of the storage tank through the graphical user interface, Thermal Desktop (TD). The total heat load into the tank may be a function of heaters and a complex radiative environment as well. Thermal Desktop may be used to address the detailed radiative environment of the tank as well as building a geometrically accurate depiction of the storage tank itself.

Sakowski, Barbara↗