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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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887 records · Page 3

General Purpose Data-Driven System Monitoring for Space Operations

Modern space propulsion and exploration system designs are becoming increasingly sophisticated and complex. Determining the health state of these systems using traditional methods is becoming more difficult as the number of sensors and component interactions grows. Data-driven monitoring techniques have been developed to address these issues by analyzing system operations data to automatically characterize normal system behavior. The Inductive Monitoring System (IMS) is a data-driven system health monitoring software tool that has been successfully applied to several aerospace applications. IMS uses a data mining technique called clustering to analyze archived system data and characterize normal interactions between parameters. This characterization, or model, of nominal operation is stored in a knowledge base that can be used for real-time system monitoring or for analysis of archived events. Ongoing and developing IMS space operations applications include International Space Station flight control, spacecraft vehicle system health management, launch vehicle ground operations, and fleet supportability. As a common thread of discussion this paper will employ the evolution of the IMS data-driven technique as related to several Integrated Systems Health Management (ISHM) elements. Thematically, the projects listed will be used as case studies. The maturation of IMS via projects where it has been deployed or is currently being integrated to aid in fault detection will be described. The paper will also explain how IMS can be used to complement a suite of other ISHM tools, providing initial fault detection support for diagnosis and recovery

Space Propulsion

Computation of three-dimensional mixed convective boundary layer flow

The paper presents the numerical solution of heat and mass transfer during cross-flow (orthogonal) mixed convection. In this class of flow, a buoyancy-driven transport in the vertical direction and a forced convective flow in the horizontal direction results in a three-dimensional boundary layer structure adjacent to the plate. The rates of heat and mass transfer are determined by a combined influence of the two transport processes. The equations for the conservation of mass, momentum, energy, and species concentration were solved along with appropriate boundary conditions to determine the distributions of velocity components, temperature, and concentration across the thickness of the boundary layer at different locations on the plate. Results were expressed in dimensionless form using Reynolds number, Richardson number for heat transfer, Richardson number for mass transfer, Prandtl number, and Schmidt number as parameters. It was found that the transport is dominated by buoyancy at smaller vertical locations and at larger distances away from the forced convection leading edge. Effects of forced convection appeared to be very strong at smaller horizontal distances from the leading edge. The cross stream forced convection enhanced the rate of heat and mass transfer by a very significant amount.

Prashandt Gadepalli

Semi-Transparent Perovskite Solar Cells in a Stacked Tandem Module: Cooperative Research and Development Final Report, CRADA Number CRD-19-00810

This project seeks to develop device design, materials composition, and processing tools and parameters to fabricate semi-transparent perovskite solar cells and modules for application in stand-alone products or added to other solar cells in a mechanically stacked tandem configuration. This technology presents significant advanced manufacturing challenges and opportunities in getting to scale, including development of perovskite inks, scalable perovskite and heterojunction deposition and annealing processes, heterojunction composition, transparent electrode composition and deposition process, anti-reflection layer composition and deposition process, and cell to module integration processes. Modification 5: The proposed project seeks to develop device design, materials composition, and processing tools and parameters to fabricate semi-transparent perovskite solar cells and modules for application in stand-alone products or added to other solar cells in a mechanically-stacked tandem configuration. This technology presents significant advanced manufacturing challenges and opportunities in getting to scale, including development of perovskite inks, scalable perovskite and heterojunction deposition and annealing processes, heterojunction composition, transparent electrode composition and deposition process, passivation layers including in module scribes, anti-reflection layer composition and deposition process, and cell to module integration processes. Advanced metrology and characterization will be performed on perovskite films, cells and module. Furthermore, we will examine module or materials recycling for circular economy considerations. Modifcation 6: Gigahertz frequency microwave pump-probe spectroscopies are highly sensitive to thin film semiconductor photoconductivity of individual and stacks of layers that comprise perovskite solar cells. As such, these techniques will be used to qualify reproducibility and quality correlations during the manufacturing process. Modification 7: Mechanical adhesion of top contacts within perovskite modules significantly impacts the durability of the module when exposed to accelerated degradation testing. The adhesion between the perovskite/transport layer interface and the transport layer/top contact interface are both very sensitive small changes in processing. ALD processing conditions of the transport layer will be tuned to optimize the mechanical adhesion within the perovskite module stack.

14 SOLAR ENERGY

Analysis of Gas Absorption to A Thin Liquid Film in the Presence of A Zero-Order Chemical Reaction

The paper presents a detailed theoretical analysis of the process of gas absorption to a thin liquid film adjacent to a horizontal rotating disk. The film is formed by the impingement of a controlled liquid jet at the center of the disk and subsequent radial spreading of liquid along the disk. The chemical reaction between the gas and the liquid film can be expressed as a zero-order homogeneous reaction. The process was modeled by establishing equations for the conservation of mass, momentum, and species concentration and solving them analytically. A scaling analysis was used to determine dominant transport processes. Appropriate boundary conditions were used to solve these equations to develop expressions for the local concentration of gas across the thickness of the film and distributions of film height, bulk concentration, and Sherwood number along the radius of the disk. The partial differential equation for species concentration was solved using the separation of variables technique along with the Duhamel's theorem and the final analytical solution was expressed using confluent hypergeometric functions. Tables for eigenvalues and eigenfunctions are presented for a number of reaction rate constants. A parametric study was performed using Reynolds number, Ekman number, and dimensionless reaction rate as parameters. At all radial locations, Sherwood number increased with Reynolds number (flow rate) as well as Ekman number (rate of rotation). The enhancement of mass transfer due to chemical reaction was found to be small when compared to the case of no reaction (pure absorption), but the enhancement factor was very significant when compared to pure absorption in a stagnant liquid film. The zero-order reaction processes considered in the present investigation included the absorption of oxygen in aqueous alkaline solutions of sodiumdithionite and rhodium complex catalyzed carbonylation of methanol. Present analytical results were compared to previous theoretical results for limiting conditions, and were found to have very good agreement.

S Rajagopalan

General Purpose Data-Driven System Monitoring for Space Operations

Modern space propulsion and exploration system designs are becoming increasingly sophisticated and complex. Determining the health state of these systems using traditional methods is becoming more difficult as the number of sensors and component interactions grows. Data-driven monitoring techniques have been developed to address these issues by analyzing system operations data to automatically characterize normal system behavior. The Inductive Monitoring System (IMS) is a data-driven system health monitoring software tool that has been successfully applied to several aerospace applications. IMS uses a data mining technique called clustering to analyze archived system data and characterize normal interactions between parameters. This characterization, or model, of nominal operation is stored in a knowledge base that can be used for real-time system monitoring or for analysis of archived events. Ongoing and developing IMS space operations applications include International Space Station flight control, satellite vehicle system health management, launch vehicle ground operations, and fleet supportability. As a common thread of discussion this paper will employ the evolution of the IMS data-driven technique as related to several Integrated Systems Health Management (ISHM) elements. Thematically, the projects listed will be used as case studies. The maturation of IMS via projects where it has been deployed, or is currently being integrated to aid in fault detection will be described. The paper will also explain how IMS can be used to complement a suite of other ISHM tools, providing initial fault detection support for diagnosis and recovery.

Satellites

Thermally unstable roosts influence winter torpor patterns in a threatened bat species

Abstract Many hibernating bats in thermally stable, subterranean roosts have experienced precipitous declines from white-nose syndrome (WNS). However, some WNS-affected species also use thermally unstable roosts during winter that may impact their torpor patterns and WNS susceptibility. From November to March 2017–19, we used temperature-sensitive transmitters to document winter torpor patterns of tricolored bats (Perimyotis subflavus) using thermally unstable roosts in the upper Coastal Plain of South Carolina. Daily mean roost temperature was 12.9 ± 4.9°C SD in bridges and 11.0 ± 4.6°C in accessible cavities with daily fluctuations of 4.8 ± 2°C in bridges and 4.0 ± 1.9°C in accessible cavities and maximum fluctuations of 13.8 and 10.5°C, respectively. Mean torpor bout duration was 2.7 ± 2.8 days and was negatively related to ambient temperature and positively related to precipitation. Bats maintained non-random arousal patterns focused near dusk and were active on 33.6% of tracked days. Fifty-one percent of arousals contained passive rewarming. Normothermic bout duration, general activity and activity away from the roost were positively related to ambient temperature, and activity away from the roost was negatively related to barometric pressure. Our results suggest ambient weather conditions influence winter torpor patterns of tricolored bats using thermally unstable roosts. Short torpor bout durations and potential nighttime foraging during winter by tricolored bats in thermally unstable roosts contrasts with behaviors of tricolored bats in thermally stable roosts. Therefore, tricolored bat using thermally unstable roosts may be less susceptible to WNS. More broadly, these results highlight the importance of understanding the effect of roost thermal stability on winter torpor patterns and the physiological flexibility of broadly distributed hibernating species.

Biodiversity & Conservation

Multiscale Modeling of Fracture Strength in Fibrous Thermal Protection System Materials

This work presents a multiscale modeling approach to predict the fracture strength of fibrous Thermal Protection System (TPS) materials. The model assumes that system failure is initiated at the joints between individual fibers. We investigated three distinct TPS compositions: amorphous silica, alumina and aluminosilicate fibers. Molecular dynamics (MD) simulations were employed to determine the fracture strength values of these fiber joints for both material systems. These fracture strength values were then integrated into simulations of 3D randomly populated fiber structures, where tensile load transfer occurs through the fiber joints. These microscale properties are upscaled through a renormalization approach [1] to predict macroscale tensile strength of 3D random fiber networks, accounting for joint-dominated failure and effective load-bearing area. The study concludes by demonstrating the resulting strength variation as a function of material composition, fiber density, and morphology. We also show validation of results by comparing them against explicit fiber finite element (FE) modeling [2] where fiber joint fracture is represented by cohesive elements.

Jaehyun Cho

Comparison of Cryogenic Flow Boiling in Liquid Nitrogen and Liquid Hydrogen Chilldown Experiments

This paper presents a comparison between experimental results from recent liquid hydrogen (LH 2 ) transfer line chilldown experiments at high Reynolds (Re) numbers versus liquid nitrogen (LN 2 ) experiments conducted at low Re numbers. Parasitic heat leak, inner wall temperatures, inner wall heat fluxes, and heat transfer coefficients are computed to compare between the two systems. Analysis of temperature traces and flow visualization indicates that the chilldown process evolves much more rapidly at higher Re numbers due to a quick transition from vapor flow to annular liquid flow and near immediate liquid contact along the pipe walls. The lower kinematic viscosity and surface tension of LH 2 , along with reduced parasitic heat leak and higher Re numbers relative to the LN 2 experiments, causes chilldown to proceed almost immediately into the nucleate boiling regime, in comparison to low Re flows where >75% of the chilldown is spent in vapor film boiling.

Cryogenic Heat Transfer Coefficient

Multitask graph neural networks for elastoplastic response prediction in dual-phase polycrystals

Microstructure-sensitive prediction of elastoplastic response remains a recurring bottleneck in multiscale damage and fatigue modeling, where large ensembles of statistically distinct polycrystals are required to quantify variability and extreme-value behavior. In this work, we develop a multitask graph neural network (GNN) surrogate that maps dual-phase ferrite–martensite polycrystal microstructures to Statistical Volume Element (SVE)-level elastoplastic Quantities of Interest (QoIs). Each SVE is represented as a grain-adjacency graph, with node features encoding phase, geometry, and crystallographic orientation, and edge features encoding relative misorientation. A message-passing graph convolution generates node embeddings, which are pooled into a graph representation and passed to a multitask regression head that jointly predicts 10 scalar QoIs and vector-valued stress–strain responses in orthogonal loading directions across multiple martensite volume fractions and SVE sizes. Results show high accuracy for scalar QoIs and strong agreement for full stress–strain trajectories, with population envelopes reproducing both median behavior and finite-SVE variability across compositions and partition scales. A unified model trained on pooled volume-fraction data preserves most within-regime accuracy relative to regime-specific models while also capturing the broader cross-regime variation reflected in the pooled test set. Distributional comparisons further demonstrate that the surrogate preserves heterogeneity under SVE partitioning, enabling statistically consistent block-wise random-field construction for mesoscale analyses. Overall, the proposed grain-graph surrogate provides a practical pathway to accelerate ensemble-based studies of SVE-level constitutive variability in dual-phase polycrystals.

Crystal plasticity

Topological magnons on the ferromagnetic zigzag lattice

Motivated by the experimental identification of magnetic compounds consisting of zigzag chains, we analyze the band structure topology of magnons in ferromagnets on a zigzag lattice. We account for the general lattice geometry by including spatially anisotropic Heisenberg exchange interactions and by Dzyaloshinskii-Moriya interaction on inversion asymmetric bonds. Within the linear spin-wave theory, we find two magnon branches, whose band structure topology (i.e., Chern numbers) we map out in a comprehensive phase diagram. Notably, besides topologically trivial and gapless phases, we identify topologically nontrivial phases that support chiral edge magnons. We show that these edge states are robust against elastic defect scattering.

Subramanian, Skandan [ORNL] (ORCID:000900087255487

Role of Matter Interactions in Superradiant Phenomena

The superradiant phenomenon, usually described by the Dicke model, is a hallmark of strong light-matter interaction. Here, we explore how matter-matter interactions influence this phenomenon by performing ground-state simulations of Dicke-like models with both isotropic and anisotropic interactions. We find that Ising-type interactions produce two qualitatively distinct phase boundaries, one of which gives rise to an antiferromagnetic-normal phase connected to the superradiant regime via a first-order phase transition. Under anisotropic couplings, we uncover a strongly correlated phase where in-plane spin order coexists with superradiance, exhibiting sublinear scaling of the photon occupation per site and power-law decay of spin correlations. Furthermore, superradiance is strengthened by tuning either isotropic or anisotropic interactions, highlighting the role of intrinsic many-body correlations in shaping light-matter quantum phases.

Dicke model

Virtual Growth of SRF Materials

Niobium's native surface oxide affects SRF cavity and superconducting qubit performance, motivating interest in controlling its crystalline structure. We combine a literature-derived machine-learning analysis with temperature-dependent XRD to study crystalline ordering in Nb2O5. Random Forest models, trained on 74 processing conditions from 17 papers and validated by leave-one-group-out cross-validation, predicted broad crystallinity outcomes well (balanced accuracy 0.809), but struggled with specific polymorph identity (0.577). Annealing temperature was the dominant predictor across all targets; oxygen partial pressure showed negligible importance, reflecting narrow literature coverage rather than physical irrelevance. Temperature-dependent XRD on anodized and H2O2-treated Niobium showed structural evolution consistent with the machine learning predictions. Our model and overall approach provide a data-driven framework for identifying and optimizing conditions that promote crystallization in initially amorphous oxides. This framework can guide the selection of growth and post-annealing conditions for Nb surfaces by narrowing the experimental parameter space, thereby reducing trial-and-error efforts in developing oxide structures relevant to SRF applications.

Tilkin, Anthony [Fermilab]

Discrete Rotational Energy for Polyatomic Molecules in Direct Simulation Monte Carlo

The environments experienced by vehicles upon entry into planetary atmospheres generally result in severe aerothermodynamic loading. These flows are characterized by the formation of strong shock waves, behind which high temperatures and non-equilibrium environments are generated, and the accurate prediction of internal energy relaxation and chemical kinetics becomes important. This manuscript focuses on the internal relaxation of the rotational energy of polyatomic molecules. Previous work has described the implementation of a discrete rotational energy model for diatomic molecules (linear rotators). Later, Gimelshein et. al extended this model to include polyatomic molecular internal energies. However, they did not include details on how to generate the particles at equilibrium conditions and centrifugal distortion was not included in their model. The purpose of the present study is to extend the afore-mentioned models to the treatment of discrete rotational energy in polyatomic molecules with the addition of centrifugal distortion. An overview of the background theory needed for the implementation of the model will be given followed by the model itself and verification of the model. For example, sampled versus Boltzmann distributions are compared in Figure 1 for CH3 (oblate rotator – two quantum numbers) and examples of thermal relaxation behavior for linear and non-linear rotators are presented in Figure 2. In addition, comparisons of thermophysical properties will be presented, as well as examples of adiabatic relaxation and application to hypersonic flow.

Rarefied Gas Dynamics

Photon–photon chemical thermodynamics of frequency conversion processes in highly multimode systems

Abstract Frequency generation in highly multimode nonlinear optical systems is inherently a complex process, giving rise to an exceedingly convoluted landscape of evolution dynamics. While predicting and controlling the global conversion efficiencies in such nonlinear environments has long been considered impossible, here, we formally address this challenge even in scenarios involving a very large number of spatial modes. By utilizing fundamental notions from optical statistical mechanics, we develop a universal theoretical framework that effectively treats all frequency components as chemical reactants/products, capable of undergoing optical thermodynamic reactions facilitated by a variety of multi-wave mixing effects. These photon–photon reactions are governed by conservation laws that directly determine the optical temperatures and chemical potentials of the ensued chemical equilibria for each frequency species. In this context, we develop a comprehensive stoichiometric model and formally derive an expression that relates the chemical potentials to the optical stoichiometric coefficients, in a manner akin to atomic/molecular chemical reactions. This advancement unlocks new predictive capabilities that can facilitate the optimization of frequency generation in highly multimode photonic arrangements, surpassing the limitations of conventional schemes that rely exclusively on nonlinear optical dynamics. Notably, we identify a universal regime of Rayleigh–Jeans thermalization where an optical reaction at near-zero optical temperatures can promote the complete and entropically irreversible conversion of light to the fundamental mode at a target frequency. Our theoretical results are corroborated by numerical simulations in settings where second-harmonic generation, sum-frequency generation and four-wave mixing processes can manifest.

Optics

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

Generalized geometric speed limits for quantum observables

Leveraging quantum information geometry, we derive generalized quantum speed limits on the rate of change of the expectation values of observables. These bounds subsume and, for Hilbert space dimension ≥3, tighten existing bounds—in some cases by an arbitrarily large multiplicative constant. Our theoretical results are supported by illustrative examples and an experimental demonstration using a superconducting qutrit. We also derive two upper bounds on the generalized quantum Fisher information in terms of the condition number of the density matrix. One of these bounds applies only to coherent dynamics and depends also on the variance of the Hamiltonian. The other bound depends also on the so-called Wigner-Yanase skew information. These bounds generalize well-known bounds on the symmetric logarithmic derivative quantum Fisher information and are tighter than the existing bounds for sufficiently mixed states (e.g., for sufficiently high temperature thermal states).

open quantum systems & decoherence

Multikilowatt hydrogen-nickel oxide battery system

The potential of the H2-NiO battery for terrestrial applications was assessed. A multicell design approach that differs significantly from the aerospace individual pressure vessel was used. A number of experimental 100-Ah cells were built to evaluate the new design concepts and components. The experimental cells provided the input needed for a multicell battery design. It is found that new multicell H2-NiO battery has a number of potential advantages for aerospace applications such as the manned space station. The advantages are discussed, and a design concept is presented for a multikilowatt battery in a lightweight pressure vessel.

Dunlop, J. D.

Multiple shape coexistence near {sup 118}Sn: First 0+ 3 lifetime measurement

The intruder bands in Sn isotopes, built on the 2p-2h excitation across the Z = 50 proton shell gap, are well-known examples of shape coexistence near the neutron mid-shell region. Spectroscopic signatures for shape coexistence include enhanced E0 transitions between the 0+ band heads. However, the underlying shape coexistence and mixing has been unclear because lifetime information for the excited 0+ states was incomplete in 118Sn. We thus present here the first measurement of the 0+ 3 lifetime in 118Sn using the fast-timing technique following thermal-neutron capture. The observed enhancement in ρ2(E0;0+ 3 → 0+ 2 ) of 150(30) milliunits provides compelling indications for multiple shape coexistence in 118Sn. Additionally, three distinct shapes in 116,118,120Sn naturally emerged in theoretical calculations based on the quantum-number-projected generator coordinate method employing a relativistic energy density functional.

Wu, F.