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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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The electromagnetic effects of conventional dielectrics, anisotropic dielectrics, and metamaterials were modeled in a terahertz-frequency folded-waveguide slow-wave circuit. Results of attempts to utilize these materials to increase efficiency are presented.
The technology of direct electrolysis of molten lunar regolith to produce oxygen and molten metal alloys has progressed greatly in the last few years. The development of long-lasting inert anodes and cathode designs as well as techniques for the removal of molten products from the reactor has been demonstrated. The containment of chemically aggressive oxide and metal melts is very difficult at the operating temperatures ca. 1600 C. Containing the molten oxides in a regolith shell can solve this technical issue and can be achieved by designing a self-heating reactor in which the electrolytic currents generate enough Joule heat to create a molten bath.
In the past, fuel rods have been used in nuclear propulsion applications. A new fuel element concept that reduces weight and increases efficiency uses a stack of grooved discs. Each fuel element is a flat disc with a hole on the interior and grooves across the top. Many grooved ring fuel elements for use in nuclear thermal propulsion systems have been modeled, and a single flow channel for each design has been analyzed. For increased efficiency, a fuel element with a higher surface-area-to-volume ratio is ideal. When grooves are shallower, i.e., they have a lower surface area, the results show that the exit temperature is higher. By coupling the physics of turbulence with those of heat transfer, the effects on the cooler gas flowing through the grooves of the thermally excited solid can be predicted. Parametric studies were done to show how a pressure drop across the axial length of the channels will affect the exit temperatures of the gas. Geometric optimization was done to show the behaviors that result from the manipulation of various parameters. Temperature profiles of the solid and gas showed that more structural optimization is needed to produce the desired results. Keywords: Nuclear Thermal Propulsion, Fuel Element, Heat Transfer, Computational Fluid Dynamics, Coupled Physics Computations, Finite Element Analysis
Ensembles of numerical model forecasts are of interest to operational early warning forecasters as the spread of the ensemble provides an indication of the uncertainty of the alerts, and the mean value is deemed to outperform the forecasts of the individual models. This paper explores two ensembles on a severe weather episode in Spain, aiming to ascertain the relative usefulness of each one. One ensemble uses sensible choices of physical parameterizations (precipitation microphysics, land surface physics, and cumulus physics) while the other follows a perturbed initial conditions approach. The results show that, depending on the parameterizations, large differences can be expected in terms of storm location, spatial structure of the precipitation field, and rain intensity. It is also found that the spread of the perturbed initial conditions ensemble is smaller than the dispersion due to physical parameterizations. This confirms that in severe weather situations operational forecasts should address moist physics deficiencies to realize the full benefits of the ensemble approach, in addition to optimizing initial conditions. The results also provide insights into differences in simulations arising from ensembles of weather models using several combinations of different physical parameterizations.
No abstract available
This presentation gives examples of NASA capability in using commercial tools to solve real world problems in a variety of industries.
Launching powerful space vehicles like the next-generation Space Launch System (SLS) creates extreme pressure waves that could damage the vehicle and the launch environment at NASA’s Kennedy Space Center (KSC). To ensure mission safety, the Ignition Overpressure Protection and Sound Suppression (IOP/SS) water deluge system suppresses the strong acoustic waves by delivering almost a half-million gallons of water to the mobile launcher and flame deflector. To better understand the effectiveness of this system at different operating conditions, the Launch Ascent and Vehicle Analysis (LAVA) code, developed at NASA’s Ames Research Center, is currently being modified and extended to incorporate the complex physics needed to model the IOP/SS system.
No abstract available
Oral only presentation on the development of an MDO problem suite for the community
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Nuclear Electric Propulsion (NEP) is an in-space propulsion technology capable of enabling opposition and conjunction class crewed Mars missions. NEP subsystems include the reactor for heat generation, a power conversion system (PCS), power management and distribution (PMAD), electric propulsion subsystem (EPS), and a primary heat rejection system. Specific mass, or αe (kg / kWe), is a key performance parameter (KPP) of the propulsion system which is directly scalable with the performance and mass estimates for individual components. To inform technology maturation planning, full system and component level parametric modeling is ongoing to explore the design trade space and illustrate the effect of subsystem design choices on the system KPPs. In this study, scaling of high-assay, low-enriched uranium (HALEU) reactor designs is assessed through coupled reactor physics and thermal hydraulics analyses. Scaling analyses evaluate the impact of system performance parameters (power level, interface temperatures) on mass for direct gas cooled, pumped liquid metal, and passively cooled heat pipe reactor concepts. Each concept requires specific geometries and working fluids to reach the performance goals of PCS interface conditions (temperature, pressure, flow rate) and system mass. The reactor assembly includes the active core (fuel, moderator, cladding, working fluid), axial and radial neutron reflectors, control drums, structural support / pressure vessel, and external radiation shielding. Each of these components are parametrically sized based on performance parameters for a megawatt-class power cycle. Results of this scaling analysis increase NEP propulsion system modeling fidelity and ultimately aim to support technology down-selection along with related technology development planning. The reactor and shield αe are a function of several PCS design choices, and reactor scaling with these parameters must be considered to enable an informed decision on reactor geometry and working fluid combination.
Nuclear Electric Propulsion (NEP) is an in-space propulsion technology capable of enabling opposition and conjunction class crewed Mars missions. NEP subsystems include the reactor for heat generation, a power conversion system (PCS), power management and distribution, electric propulsion system, and heat rejection system. Specific mass, or α (kg/kWe), is a key performance parameter (KPP) of the propulsion system which is directly scalable with the performance and mass predictions for each individual component. To inform technology maturation planning activities, full system and component level parametric modeling is ongoing to explore the design trade space and illustrate the effect of subsystem design choices on the system KPPs. In this study, scaling of high-assay, low-enriched uranium reactor designs is assessed through coupled reactor physics and thermal hydraulics analyses. Scaling analyses evaluate the impact of system performance parameters (power level, interface temperatures) on mass for direct gas cooled, pumped liquid metal, and passively-cooled heat pipe reactor concepts. Each concept requires specific geometries, fluids, and power conversion interface conditions (temperature, pressure, flow rate) to meet desired performance and mass. The reactor assembly includes the active core (fuel, moderator, cladding, working fluid), axial and radial neutron reflectors, control drums, structural support / pressure vessel, and external radiation shielding. Each of these components are parametrically sized based on performance parameters for a megawatt-class power cycle. Results of this scaling analysis increase NEP propulsion system modeling fidelity and ultimately aim to support concept down-selection along with related technology development planning. The reactor and shield α are a function of several PCS and heat rejection system design choices, and reactor scaling with these parameters must be considered to enable an informed decision on an optimal reactor geometry and working fluid combination.
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Direct Energy Deposition (DED) is an emerging technology extensively employed in metal Additive Manufacturing (AM). Despite its widespread industrial application, mathematical modeling in this domain remains challenging. This complexity arises from the intricate nature of the modeling approach and the nonlinear behavior of material parameters across a broad temperature range. Consequently, experimentalists often resort to a trial-and-error method to achieve structures with desired properties. However, this approach can be time-consuming and may not always yield parts with the requisite characteristics, highlighting the necessity for mathematical modeling to enhance manufacturing success. This study focuses on thin-walled manufacturing with a single bead thickness, adjusting laser parameters to produce such structures. The laser cladding speed, typical for DED manufacturing, is considered to be on the order of centimeters per second. The various wall thicknesses and heights are explored to discern the general characteristics of walls manufactured via this DED approach. Our modeling approach diverges from the conventional DED modeling based on activation-deactivation of predefined mesh domains, commonly implemented in many finite element codes. Instead, a method is proposed that effectively models layer cladding and melt pool dynamics, enabling predictions of the microstructure in the resulting structures. The formation mechanisms of cellular, dendritic columnar, and stray (equiaxed) grains, which arise from the interplay between nucleation and growth from the surface is analyzed. The study also examines the feasibility of microstructure formation to demonstrate the various thermal characteristics inherent in wall manufacturing. Our results illustrate how different process parameters influence the temperature gradient and cooling rate of the molten pool, subsequently affecting the primary dendrite arm spacing (PDAS). This modeling technique allows for the investigation of diverse thermal conditions, facilitating the prediction of microstructure and residual stresses in the manufactured parts.
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In energy storage materials, strong electrochemical-mechanical coupling and highly anisotropic material properties contribute to the formation and propagation of micro-cracking during charge/discharge cycling, resulting in reduced performance and service life. A coupled electro-chemo-mechanical reproducing kernel particle method (RKPM) formulation is developed, and a patch-test is formulated to certify optimal convergence of the proposed RKPM method for the coupled physics system. With microstructural images supplied by the National Renewable Energy Laboratory (NREL), pixel-based model construction by RKPM is then used to represent the complex material microstructures for modeling the coupled physics of these systems. Further, a neural network-enhanced reproducing kernel particle method (NN-RKPM) [1, 2] is introduced to effectively model 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. Reference: [1] 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, pp 4422-4454, https://doi.org/10.1002/nme.7040, 2022. [2] Baek, J., Chen, J. S., "A Neural Network-Based Enrichment of Reproducing Kernel Approximation for Modeling Brittle Fracture", Computer Methods in Applied Mechanics and Engineering Vol. 410, 116590, 2024.
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