Search NASASearch

SEARCH · Search NASA

Results for “model evaluation”

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

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

1,202 records · Page 26

Dissipative Phase Transition in the Two-Photon Dicke Model

We explore the dissipative phase transition of the two-photon Dicke model, a topic that has garnered significant attention recently. Our analysis reveals that while single-photon loss does not stabilize the intrinsic instability in the model, the inclusion of two-photon loss restores stability, leading to the emergence of superradiant states, which coexist with the normal vacuum states. Using a second-order cumulant expansion for the photons, we derive an analytical description of the system in the thermodynamic limit, which agrees well with the exact calculation results. Additionally, we present the Wigner function for the system, shedding light on the breaking of the 𝑍4 symmetry inherent in the model. These findings offer valuable insights into stabilization mechanisms in open quantum systems and pave the way for exploring complex nonlinear dynamics in two-photon Dicke models.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC

Exposure of Highly Reflective Far-Ultraviolet Coatings to LEO Environment for TRL Advancement for the Habitable Worlds Observatory

Over the past several years, our team at the NASA Goddard Space Flight Center (GSFC), in collaboration with the Jet Propulsion Laboratory (JPL) and the Naval Research Laboratory (NRL), have developed several new protected Al coating technologies with improved Far-Ultraviolet (FUV) reflectance performance and more robust environmental stability. These include Al protected with lithium-based fluoride (LiF) coatings such as hot deposited LiF (eLiF), XeF 2 -passivated LiF coatings (XeLiF), Li 3 AlF 6 overcoats, AlF 3 (plasma passivated), and XeF 2 passivated MgF 2 coatings (XeMgF 2 ). However, despite these developments, relatively little experimental information exists regarding the long-term stability of these coatings after simultaneous exposure to the Low Earth Orbit (LEO) environment. To evaluate their environmental durability and advance their Technology Readiness Level (TRL), representative samples of these coating technologies, Al+XeLiF, Al+eLiF, Al+Li 3 AlF 6 , Al+AlF 3 , Al+XeMgF 2 , and bare Al as reference samples, were flown onboard the International Space Station (ISS) as part of the Materials International Space Station Experiment 20 (MISSE-20). The MISSE platform is operated by Aegis Aerospace for relatively long-duration (e.g. 6 months) external exposure experiments in a space environment. The coatings were deposited on ULE and Zerodur substrates, and witness samples deposited on the same coatings runs, but on glass slides were left on Earth as control. A subset of the flight samples were fitted with MgF 2 windows to reduce direct exposure to atomic oxygen (AO) and charged particles, and still let through UV and other types of radiation on these samples. After approximately 6 months of exposure in the forward-facing (RAM) direction, the samples were returned to Earth and characterized by performing FUV/NUV/VIS/NIR reflectance measurements to quantify degradation, spectroscopic ellipsometry to evaluate coating thickness and optical constants, atomic force microscopy (AFM) to quantify surface roughness evolution during the flight in the ISS. The MgF 2 protective windows were also analyzed through FUV transmission measurements. Comparison with the witness samples left on the ground and with the flown bare Al samples (with just the naturally occurring Al 2 O 3 layer) provided a quantitative assessment of coating thickness variations, optical performance degradation, and morphological changes induced by prolonged exposure to the LEO environment.

Far Ultraviolet (FUV)

Usage-based Lifing of Lithium-Ion Battery with HybridPhysics-Informed Neural Networks

Lithium-ion batteries are commonly used to power unmanned aircraft vehicles (UAVs).The ability to model and forecast the remaining useful life of these batteries enables UAV reliability assurance. Building accurate models for battery state of charge and state of health based on first principles is challenging due to the complex electrochemistry that governs battery operations and computational complexity required to solve them. Therefore, reduced order models are often used due to their ability to capture the overall battery discharge. Un-fortunately, these simplifications lead to residual discrepancy between model predictions and observed data. In this paper, we present a hybrid modeling approach merging reduced-order models and neural networks. In this approach, while most of the input-output relationship is captured by Nernst and Butler-Volmer equations, data-driven kernels reduce the gap between predictions and observations. We validate our approach using data publicly available through the NASA Prognostics Center of Excellence repository. Results showed that our hybrid battery prognosis model can be successfully calibrated, even with a limited number of observations.

Lithium-ion Battery

Investigation of Bipropellant Plume-Induced Contamination Effects on Coverglass Materials

Contamination and degradation of external spacecraft materials by unburned and partially combusted species from bipropellant thruster plumes has long been observed as a key component of the induced space environment. Space shuttle flight experiments and returned flight hardware from the International Space Station (ISS) have both experienced microscopic impact features induced by high-velocity thruster plume droplets. Analytical results have shown that droplet impingement angle relative to a receiving surface plays a key role in the surface damage. Although impacts with normal impingement angles contribute more severely to surface degradation than highly oblique angles, surface effects at higher impingement angles should not be dismissed. Thruster plume-induced materials degradation is a complex phenomenon that depends on a variety of parameters, including but not limited to material type, system temperature and pressure, plume composition, and thruster firing specifications such as number of pulses, pulse duration, and sample distance from the thruster. For space applications, attaining the vacuum pressure and temperature conditions necessary for flight-like plume expansion and exposure conditions is not a trivial task. The German Aerospace Center (Deutsches Zentrum für Luft- und Raumfahrt, DLR) is a facility uniquely capable of simulating such conditions. Test coupons were exposed to bipropellant thruster firings under high vacuum at the DLR facility. Percent area coverage (PAC) and droplet size distributions were evaluated for the uncoated and coated solar array coverglass materials over a range of impingement angles (0̊ to 75̊). A post-test imaging workflow was developed that aimed to quantify changes in sample surface morphology obtained from scanning electron microscopy (SEM) images using the Image Processing and Analysis in Java (ImageJ) tool; an opensource image processing software. The goal was to create a framework through which to evaluate the effect of bipropellant-induced PAC and droplet size distribution on solar array coverglass optical transmission losses. Understanding this relationship is important because optical transmission losses are known to lead to current reduction in solar power generation systems. In addition to the development of surface characterization workflows, valuable lessons learned as they pertain to future investigations and experiments will be discussed. The authors hope that sharing these lessons will facilitate more utilization of DLR’s unique capabilities as well as open the conversation for how best to address experimental characterization of flight-like plume expansion and its impacts on materials surface degradation effects.

Gateway

Numerical Predictions of the Flow and Heat Transfer Characteristics in the Film Boiling Regime During Tube Quenching

Cryogenic fluid management plays a major role in refueling of spacecrafts while in space for NASA’s future human space exploration missions. Due to the low boiling points of cryogens, storage, transport and handling of these fluids becomes difficult and may result in inefficient operation of the space propulsion systems. For refueling applications in space, the cryogenic fluids have to be transported across different locations and hence, the transfer of cryogenic fluids through pipes become critical. The cryogenic chill-down process is characterized by different regimes of flow boiling, viz., film boiling, transition boiling and nucleate boiling. The prediction of these regimes in a single CFD framework available in the literature is challenging and the present work attempts to address this challenge by initially modeling the film boiling regime accurately and to incorporate an user-defined function for transition and nucleate boiling at a later stage. Hence, the aim of the present work is to numerically model and validate the film boiling regime of the chilldown curve for liquid nitrogen experiments available in the literature. The validations are carried out at different inlet mass fluxes to have a robust simulation methodology. A dispersed mixture model is used to predict the vapor-liquid interface dynamics with the phase change phenomena modeled using the Lee model.

line chilldown

SimH 2 : an integrated techno-economic modeling framework for hydrogen pipeline infrastructure and network optimization

Large-scale hydrogen (H 2 ) pipeline transport design and network optimization have seldom been reported due to the lack of a cost model accounting for the relationship between transport cost and hydrogen mass flow rate. Here, this work introduced a system-level cost model for hydrogen pipeline transport at supercritical state and integrated it with an existing CO 2 pipeline network tool, SimCCS, for hydrogen-specific pipeline design and optimization. The Intermountain West (I-West) region of the U.S., historically dependent on fossil fuel-based economies, is chosen to demonstrate the capabilities of our H 2 pipeline cost model and transport network optimization platform called SimH 2 . Two scenarios are examined: one where the pipeline is not allowed to pass through disadvantaged communities and the other where it is permitted. The results highlight that incorporating disadvantaged-community constraints lead to longer pipeline routes and increased transport costs, reflecting the trade-offs involved in equitable infrastructure development. It is demonstrated that the newly developed SimH 2 tool not only enables the efficient design of H 2 transportation pipelines but also optimizes the network by accounting for local terrain and the presence of disadvantaged areas.

08 HYDROGEN

Reduced-order CFD modeling of cryogenic hydrogen isotope extrusion for pellet fueling

This study presents a reduced-order model (ROM) for computational fluid dynamics (CFD) simulations of cryogenic hydrogen isotope extrusions, focusing on protium (H₂) and deuterium (D₂) piston extruders. Using a 2D axisymmetric ROM in ANSYS-Polyflow, significant computational savings were achieved (runtime reduced from 9∼24 h to 3∼5 min), with extrusion force discrepancies between the 2D ROM and 3D models being on the order of 1%. Parametric studies identified optimal cutoff shear rates in the viscosity model (0.01/s for H₂ and 0.001/s for D₂), providing recommendations for future simulations. Finally, a comprehensive comparison of ROM results with experimental data was performed across varying geometries, cryogenic materials, temperatures, extrusion lengths, and piston velocities. Predictions at low extrusion temperatures met the objective of providing quick and efficient solutions with an acceptable extrusion force error of approximately 10% or less, validating the effectiveness of the 2D ROM approach. However, at high temperatures closer to the triple point, extrusion force error grows, which necessitates developing an improved model that accounts for temperature effects, e.g. melting. Nevertheless, the findings still represent a significant improvement in efficiency of CFD modeling of cryogenic hydrogenic extrusion. The ROM framework can also be extended to tritium (T2) and screw extruders, which will ultimately provide a fast and effective tool for optimizing pellet injector design for ITER and future reactor systems.

Fan, Joy [ORNL] (ORCID:0000000229751735)

Reverse Logistics Ev Battery Recycling Agent Base Model

This represents the initial regional tier of the electric vehicle (EV) battery recycling agent base model. Through this model, we can ascertain the number of EV purchases at both the state and regional levels. We employ census data to develop a diverse household profile to inform decisions regarding the acquisition of new or used EVs. The number of EV purchases at the state level will affect the future demand for recycling, reuse, and repurposing of end-of-life EV batteries. Additionally, tax credits, EV rebate programs, and the financial capacity of households will influence the number of EV purchases, thereby further impacting the demand for EV battery recycling.

Alam, Lamia [Idaho National Laboratory (INL), Idah

Conserved Macromolecular Architecture of Poplar Secondary Cell Walls Revealed by ssNMR and Atomistic Modeling

The macromolecular architecture of plant secondary cell walls governs wood's mechanical and biochemical properties, yet its natural intra-species variability remains poorly characterized. Here, we combined 13C solid-state NMR (ssNMR), multivariate statistical analysis, and molecular modeling to profile nanoscale structure across 13 genetically diverse Populus trichocarpa genotypes grown in 13C-enriched atmospheres. SsNMR-derived phenotypes spanning composition, structure, mobility, and inter-polymer proximities reveal a conserved architecture, with a subtle yet coordinated variation organizing into dominant structural and secondary mobility axes. A representative atomistic model captures these features and reproduces experimental metrics. Molecular dynamics simulations support a weak but consistent positive correlation between cellulose abundance and crystalline-like order, with interior cellulose chains enriched in tg (trans-gauche) conformations without expanding crystalline cores. Together, experiment and simulation reveal a genetically buffered, broadly conserved nanoscale architecture across genotypes, where subtle fine-tuning of cellulose bundling and matrix packing balances mechanical performance with biological function.

09 BIOMASS FUELS

Sustainable Triacetic Acid Lactone Production from Sugarcane by Fermentation and Crystallization

Triacetic acid lactone (TAL) has the potential to serve as a bioderived platform chemical for commercial products including sorbic acid and recyclable polydiketoenamine plastics. In this study, we leveraged BioSTEAM to design, simulate, and evaluate (via techno-economic analysis, TEA, and life cycle assessment, LCA) TAL production from sugarcane. We experimentally characterized TAL solubility, calibrated solubility models, and designed a process to separate TAL from fermentation broths by crystallization. The biorefinery could produce TAL at a minimum product selling price (MPSP) of $\$3.73$–5.86·kg –1 (5th–95th percentiles; baseline at $\$4.60$·kg –1 ) and a carbon intensity (CI) of 5.31 [2.60–8.71] kg CO 2 -eq·kg –1 , which could enable financially viable, low-CI production of sorbic acid and polydiketoenamines. To drive down costs and CI, we explored the theoretical fermentation space (titer, yield, productivity combinations), operation scheduling and capacity expansion strategies (e.g., integrated sorghum processing), and potential separation improvements (mitigating TAL loss through pH control). Advancements in key design and technological parameters could further reduce MPSP by 51% to $\$2.26$·kg –1 [$\$1.97$–2.80·kg –1 ] and CI by 43% to 3.05 [1.91–4.15] kg CO 2 -eq·kg –1 . This research highlights the ability of agile TEA-LCA to screen promising designs, navigate sustainability trade-offs, prioritize research needs, and chart quantitative roadmaps to advance bioproducts and biofuels.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Modeling of a Four-Stage Linear Ionization Cooling Channel for a Muon Collider in G4Beamline

A previous study of an eight-stage rectilinear ionization cooling channel in the ICOOL software demonstrated a five-order-of-magnitude reduction in a muon beam’s 6D emittance. In this study, we look to compare the ways ICOOL and Muons, Inc.’s g4Beamline software model ionization cooling by comparing their modeling of the first four stages to this optimized cooling channel constructed in ICOOL. We begin by identifying the parameters used to construct the optimized ionization cooling channel in ICOOL. We then reconstruct this beam in g4Beamline with identical parameter specifications and simulate the cooling of an identical input beam. Finally, we compare the two simulations based on their beam transmission, longitudinal emittance, and transverse emittance along the channel length. Through this process, we demonstrate that G4Beamline accurately reproduces transverse cooling results but predicts systematically different longitudinal emittance evolution while maintaining similar overall cooling performance, reproducing a 97.9% reduction in 6D emittance over four stages.

Keeler, Dominic [Purdue U., West Lafayette] (ORCID

Improvements to RANS Modeling for Aeroheating Predictions on Blunt Bodies

Accurate predictions of aeroheating are critical for designing thermal protection systems for planetary entry vehicles. For larger vehicles, turbulence in the boundary layer can substantially increase convective heating. This turbulence must be accurately modeled to ensure the thermal protection system is sufficient. The majority of hypersonic turbulence model development and validation focuses on boundary layers developing over flat-plates or sharp cones; these cases are substantially different than the boundary layer that develops over the heatshield of a blunt body traveling at hypersonic speeds. Planetary missions often use blunt body geometries, such as the 70-degree sphere-cone favored by Mars missions or the 45-degree sphere-cone planned for the upcoming DAVINCI mission. Due to smaller vehicle size and the lower velocities in the stagnation region, planetary entry vehicles have relatively low Reynolds numbers. Surface curvature and high enthalpy gradients create additional challenges. These difficulties must be addressed to obtain high accuracy needed for the ambitious planetary missions in the upcoming decade. This work focuses on both assessing and improving Reynolds-averaged Navier-Stokes (RANS) turbulence models for blunt-body geometries typical of planetary entry vehicles, with a focus on one-equation and two-equation formulations.

Mars2020

Engineering 2D Square Lattice Hubbard Models in 90° Twisted GeX/SnX (X =S, Se) Moiré Superlattices

Because of the large-period superlattices emerging in moiré two-dimensional (2D) materials, electronic states in such systems exhibit low energy flat bands that can be used to simulate strongly correlated physics in a highly tunable setup. While many investigations have thus far focused on moiré flat bands and emergent correlated electron physics in triangular, honeycomb, and quasi-one-dimensional lattices, tunable moiré realizations of square lattices subject to strong correlations remain elusive. Here, in this work, we propose a feasible scheme to construct moiré square lattice systems by twisting two or more layers of 2D materials in a rectangular lattice by 90°. We demonstrate the concept with twisted GeX/SnX (X =S, Se) moiré superlattices and calculate their electronic structures from first principles. We show that the lowest conduction flat band in these systems can be described by a square lattice Hubbard model with parameters which can be controlled by varying the choice of host materials, number of layers, and external electric fields. In particular, twisted double bilayer GeSe realizes a square lattice Hubbard model with strong frustration due to the next-nearest-neighbor hopping that could host unconventional superconductivity, in close analogy to the Hubbard model for copper-oxygen planes of cuprate high-temperature superconductors. The presented scheme uses 90° twisted 2D materials with rectangular unit cells as a promising platform for realizing the physical phenomena of square lattice Hubbard models, establishing a new route for studying its rich phase diagram of magnetism, charge order, and unconventional superconductivity in a highly tunable setting.

2-dimensional systems

Complex orders and chirality in the classical Kitaev-Γ model

It is well recognized that the low-energy physics of many Kitaev materials is governed by two dominant energy scales, the Ising-type Kitaev coupling 𝐾 and the symmetric off-diagonal Γ coupling. An understanding of the interplay between these two scales is therefore the natural starting point toward a quantitative description that includes subdominant perturbations that are inevitably present in real materials. This study focuses on the classical 𝐾−Γ model on the honeycomb lattice, with a specific emphasis on the region 𝐾< 0 and Γ > 0 , which is the most relevant for the available materials and which remains enigmatic in both quantum and classical limits, despite much effort. We employ large-scale Monte Carlo simulations on specially designed finite-size clusters and unravel the presence of a complex multisublattice magnetic order in a wide region of the phase diagram, whose structure is characterized in detail. We show that this order can be quantified in terms of a coarse-grained scalar-chirality order, featuring a counterrotating modulation on the two spin sublattices. Here, we also provide a comparison to previous studies and discuss the impact of quantum fluctuations on the phase diagram.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND

Reliability Models and Demonstration of a Fault-Tolerant Motor Concept for Vertical Takeoff and Landing Vehicles

This report documents the completion of the Revolutionary Vertical Lift Technology Project Annual Performance Indicator 24-3.2.4.1: “Apply and document reliability prediction for high reliability motor concept.” Two modeling tools were completed for calculation of reliability of fault-tolerant (FT) motors, and key FT operations of a modular FT motor were demonstrated experimentally. The two models are complementary tools for the stakeholder and user community. Both models employ Markov chain theory. The first model is a time-homogeneous Markov chain model, and the second is a time-inhomogeneous Markov-Weibull model. This report’s main sections are as follows: 1.0 Introduction, 2.0 Theory, 3.0 Motor Reliability Models, 4.0 Validation of FT Operation by Hardware Demonstration, and 5.0 Concluding Remarks. Novel contributions to the field include development of a modular FT motor concept for electrified vertical takeoff and landing (eVTOL) application, solution methods to solve the reliability calculations, development of figures of merit, and the introduction of “linked chains” to formulate a building-block approach for time-inhomogeneous Markov-Weibull modeling of motor reliability. Example case studies have been completed, and results are provided and discussed herein. A four-module FT motor concept was developed to a preliminary-design level of detail. This eVTOL FT motor concept was designed for galvanic, magnetic, and thermal isolation of stator winding faults. The reliability of the concept motor was calculated using a time-inhomogeneous Markov chain model. Employing average failure rate as a metric, 570 times greater reliability was achieved as compared to a baseline motor without fault tolerance. A demonstrator motor was built and tested. The testing demonstrated the key features of FT operation and validated the essential premises of the FT motor concepts presented herein. The experiments included successful demonstration of the feasibility of the following four key FT features: (1) terminal open-circuit operation, (2) thermal isolation after fault, (3) terminal short-circuit operation, and (4) internal short-circuit operation. These works indicate that FT modular motor drives offer promise for addressing the daunting reliability gap that electric aircraft propulsor drives are facing relative to the best conventional motor drive technology that is available today.

Electric Motor

Thermodynamically informed priors for uncertainty propagation in first-principles statistical mechanics

Here, this work demonstrates how first-principles statistical mechanics approaches within a Bayesian framework can quantify and propagate uncertainties to downstream thermodynamic calculations. To address the issue of Bayesian prior selection, knowledge of 0 K ground states in the material system of interest is incorporated into the prior. The effectiveness of this framework is shown by creating a phase diagram for the fcc zirconium nitride system, including confidence intervals on order-disorder transition temperatures.

Bayesian methods

Active learning using hybrid surrogate tool life modeling for machining process optimization

Here, this paper describes an active learning approach for part-to-part iterative machining process optimization using a hybrid surrogate tool life model. A probabilistic interpolating tool life model is developed by combining the empirical Taylor-type tool life equation and the model fit error. The probabilistic tool life model is then used to calculate the machining cost per part distribution. The optimal machining parameters are selected using an expected improvement in machining cost per part criterion. The method is validated numerically using experimental results; the results show a median convergence error of 2.2% after three tests over 400 simulations. The method is validated experimentally on two industrial applications for Ti-6Al-4V roughing resulting in a cost per part reduction greater than 23% after two tests. The described method is a robust solution for rapid convergence to optimal machining parameters in an industrial production environment.

Active learning

Rethinking 𝛼−RuCl 3 : Parameters, models, and phase diagram

RuCl 3 was likely the first ever deliberately synthesized ruthenium compound, following the discovery of the 44 Ru element in 1844. For a long time it was known as an oxidation catalyst, with its physical properties being discrepant and confusing, until a decade ago when its allotropic form 𝛼−RuCl 3 rose to exceptional prominence. This “rediscovery” of 𝛼−RuCl 3 has not only reshaped the hunt for a material manifestation of the Kitaev spin liquid, but it has opened the floodgates of theoretical and experimental research in the many unusual phases and excitations that the anisotropic-exchange magnets as a class of compounds have to offer. Given its importance for the field of Kitaev materials, it is astonishing that the low-energy spin model that describes this compound and its possible proximity to the much-desired spin-liquid state is still a subject of significant debate ten years later. In the present study, we argue that the existing key phenomenological observations put strong natural constraints on the effective microscopic spin model of 𝛼−RuCl 3 , and specifically on its spin-orbit-induced anisotropic-exchange parameters that are responsible for the nontrivial physical properties of this material. These constraints allow one to focus on the relevant region of the multidimensional phase diagram of the 𝛼−RuCl 3 model, suggest an intuitive description of it via a different parametrization of the exchange matrix, offer a unifying view on the earlier assessments of its parameters, and bring closer together several approaches to the derivation of anisotropic-exchange models. We explore extended phase diagrams relevant to the 𝛼−RuCl 3 parameter space using quasiclassical, Luttinger-Tisza, exact diagonalization, and density-matrix renormalization-group methods, demonstrating a remarkably close quantitative accord between them on the general structure and hierarchy of the phases, with the zigzag, ferromagnetic, and incommensurate phases that are proximate to each other. As a result, one of the highlights is the detailed agreement on the nature of the incommensurate phases that realize two distinct counterrotating helical states.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND