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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Osmotic and phoretic competition explains chemotaxic assembly and sorting

Microscale objects responding to chemical gradients by migrating toward or away from a preferred species is a simple yet constitutive mechanism by which transport occurs in biological organisms. Synthetic chemotaxis provides key physical descriptions of simplified systems that can be used in biological models, or in the creation of advanced responsive material systems. In this article, we provide a quantitative framework for understanding synthetic chemotaxis of microparticles which involves a competition between phoresis and osmosis. We present separate quantitative measurements of phoresis and osmosis acting on individual taxing particles, finding that phoresis follows the long-predicted v ∼ 1 / r 2 scaling while the osmotic contribution depends on the geometry and details of the system, and must be solved on a case-by-case basis. Through this, we are able to develop a more accurate picture of particle transport at the single particle level. Equipped with this approach, we go on to describe how high concentrations of particles in a symmetric chemical gradient grow close-packed hives that reach a steady-state size tunable through light intensity or particle size. Last, we demonstrate that mixed particles experiencing the same chemical gradient will selectively migrate toward or away depending on the nature of the particle surface, thereby locally sorting out a particular species. We anticipate these results will be important in describing both biological and synthetic chemotaxis in phoretic systems and should bring a wealth of studies that take advantage of competing osmotic flows to illicit unexpected dynamic active behavior.

Science & Technology - Other Topics↗
NASA NTRS2014

High Efficiency Centrifugal Compressor for Rotorcraft Applications

The report "High Efficiency Centrifugal Compressor for Rotorcraft Applications" documents the work conducted at UTRC under the NRA Contract NNC08CB03C, with cost share 2/3 NASA, and 1/3 UTRC, that has been extended to 4.5 years. The purpose of this effort was to identify key technical barriers to advancing the state-of-the-art of small centrifugal compressor stages; to delineate the measurements required to provide insight into the flow physics of the technical barriers; to design, fabricate, install, and test a state-of-the-art research compressor that is representative of the rear stage of an axial-centrifugal aero-engine; and to acquire detailed aerodynamic performance and research quality data to clarify flow physics and to establish detailed data sets for future application. The design activity centered on meeting the goal set outlined in the NASA solicitation-the design target was to increase efficiency at higher work factor, while also reducing the maximum diameter of the stage. To fit within the existing Small Engine Components Test Facility at NASA Glenn Research Center (GRC) and to facilitate component re-use, certain key design parameters were fixed by UTRC, including impeller tip diameter, impeller rotational speed, and impeller inlet hub and shroud radii. This report describes the design effort of the High Efficiency Centrifugal Compressor stage (HECC) and delineation of measurements, fabrication of the compressor, and the initial tests that were performed. A new High-Efficiency Centrifugal Compressor stage with a very challenging reduction in radius ratio was successfully designed, fabricated and installed at GRC. The testing was successful, with no mechanical problems and the running clearances were achieved without impeller rubs. Overall, measured pressure ratio of 4.68, work factor of 0.81, and at design exit corrected flow rate of 3 lbm/s met the target requirements. Polytropic efficiency of 85.5 percent and stall margin of 7.5 percent were measured at design flow rate and speed. The measured efficiency and stall margin were lower than pre-test CFD predictions by 2.4 percentage points (pt) and 4.5 pt, respectively. Initial impressions from the experimental data indicated that the loss in the efficiency and stall margin can be attributed to a design shortfall in the impeller. However, detailed investigation of experimental data and post-test CFD simulations of higher fidelity than pre-test CFD, and in particular the unsteady CFD simulations and the assessment with a wider range of turbulence models, have indicated that the loss in efficiency is most likely due to the impact of unfavorable unsteady impeller/diffuser interactions induced by diffuser vanes, an impeller/diffuser corrected flow-rate mismatch (and associated incidence levels), and, potentially, flow separation in the radial-to-axial bend. An experimental program with a vaneless diffuser is recommended to evaluate this observation. A subsequent redesign of the diffuser (and the radial-to-axial bend) is also recommended. The diffuser needs to be redesigned to eliminate the mismatching of the impeller and the diffuser, targeting a slightly higher flow capacity. Furthermore, diffuser vanes need to be adjusted to align the incidence angles, to optimize the splitter vane location (both radially and circumferentially), and to minimize the unsteady interactions with the impeller. The radial-to-axial bend needs to be redesigned to eliminate, or at least minimize, the flow separation at the inner wall, and its impact on the flow in the diffuser upstream. Lessons were also learned in terms of CFD methodology and the importance of unsteady CFD simulations for centrifugal compressors was highlighted. Inconsistencies in the implementation of a widely used two-equation turbulence model were identified and corrections are recommended. It was also observed that unsteady simulations for centrifugal compressors require significantly longer integration times than what is current practice in industry.

Gorazd Medic↗
DOE OSTI2024

Cross-scale interaction between microturbulence and meso-scale reversed shear Alfvén eigenmodes in DIII-D plasmas

Abstract This paper reports global nonlinear gyrokinetic simulations that couple meso-scale reversed shear Alfvén eigenmodes (RSAEs) driven by energetic particles (EPs) and ion temperature gradient (ITG) microturbulence driven by thermal plasma, using equilibrium and profiles from DIII-D discharge #159243. In simulations focusing only on the ITG, electrostatic ITG drives a huge thermal ion heat transport, which is reduced by a factor of 10 to a level close to the experimental value in electromagnetic simulation due to finite β effect. In the simulations coupling the RSAE and ITG, ITG can scatter the resonant EP nonlinearly trapped by the RSAE and damp the zonal flows generated by the RSAE. The regulation of the RSAE by the ITG greatly reduces the initial saturation amplitude of the RSAE but increases the RSAE amplitude and associated EP transport to experimental levels in the quasi-steady state. The RSAE effects on the ITG, specifically the stronger zonal flows generated by the RSAE and the RSAE frequency modulation of the ITG-induced thermal ion heat transport, in turn, leads to a reduction of the thermal ion heat transport by more than a factor of 2 . For a stronger background ITG, the regulation of the RSAE by the ITG is stronger, while the RSAE effects on the ITG are weaker. This work highlights the importance of cross-scale coupling in the dynamics of the AE turbulence and EP transport.

Physics↗
NASA NTRS2026

Incremental Learning for Passive Microwave Precipitation Retrievals using Advanced Technology Microwave Sounder

Spaceborne passive microwave (PMW) radiometry is central to global precipitation monitoring, yet retrieval uncertainties remain substantial, particularly for cross-track sounders whose variable footprints and channel configurations are optimized for atmospheric temperature and moisture profiling rather than precipitation. Consequently, existing operational products often exhibit angular-dependent biases, limited effective swath utilization, unrealistic rainfall probability distributions, and systematic misclassification of precipitation phase. These limitations are further compounded by the scarcity of globally accurate and representative precipitation observations, as training data from the Dual-frequency Precipitation Radar (DPR) and the Cloud Profiling Radar (CPR) are spatially sparse, lack uniform global coverage, and exhibit heterogeneous error characteristics across precipitation regimes. To address these challenges, this study presents a supervised retrieval algorithm that incrementally trains an ensemble of extreme gradient-boosted decision trees by augmenting base learners with pre-training on reanalysis data and post-training on coincident DPR and CPR observations matched with the Advanced Technology Microwave Sounder (ATMS). By transferring prior information from reanalysis to posterior constraints from radar observations and adopting a sequential detection–estimation strategy for precipitation phase and rate retrieval, the proposed approach yields retrievals across the full ATMS swath that are largely free from persistent deficiencies in current Global Precipitation Measurement (GPM) passive microwave operational products. In particular, the method resolves bimodal artifacts in rainfall retrievals and mitigates systematic high-latitude snowfall biases, including overestimation across the Arctic and underestimation across the Antarctic. Validation against independent Multi-Radar Multi-Sensor (MRMS) data over the Contiguous United States (CONUS) further demonstrates improved performance in precipitation phase detection and rate estimation relative to both reanalysis and current GPM PMW products.

Mahyar Garshasbi↗
NASA NTRS2012

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↗
DOE OSTI2025

Tautomerism induces bending and twisting of biogenic crystals

Understanding and exploiting material flexibility through phenomena such as the bending and twisting of molecular crystals has been a subject of increased interest owing to the number of applications that benefit from these properties, such as optoelectronics, mechanophotonics, soft robotics, and smart sensors. Here, we report the growth of spontaneously bent and twisted ammonium urate crystals induced by the keto–enol tautomerism of the urate molecule. The major tautomer is native to biogenic crystals, whereas the minor tautomer functions as an effective crystal growth modifier to induce naturally bent and twisted ammonium urate crystals. We show that the degree of curvature can be tailored based on the judicious selection of growth conditions. A combination of state-of-the-art microscopy and spectroscopy techniques are used to characterize the origin of bending. Spatially resolved nano-electron diffraction and high-resolution electron microscopy of naturally bent crystals show nearly single crystallinity with local lattice deformations generated by a combination of screw and edge dislocations. These observations are consistent with photoinduced force microscopy and contact resonance atomic force microscopy, which confirmed spatially resolved changes in the intermolecular interactions and the mechanical properties throughout the cross-sectional and axial regions of bent crystals. A mechanism of bending involving the generation of regionally specific dislocations is proposed as an alternative to more commonly reported models. These findings highlight a unique characteristic of tautomeric crystals that may have broader implications for other biogenic materials.

Science & Technology - Other Topics↗
NASA NTRS2009

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↗
DOE OSTI2026

High-resolution modeling of indoor radon exposure with uncertainty quantification in Utah

Indoor radon accounts for 37% of population-level exposure to ionizing radiation in the United States. However, radon metrics are typically reported at coarse spatial scales, potentially obscuring meaningful local variation. We developed a high-resolution modeling framework to estimate indoor radon concentrations across Utah while explicitly quantifying predictive uncertainty. A total of 19,497 residential radon measurements collected between 2006 and 2017 were combined with environmental and housing characteristics and analyzed using a geospatial neural network that accommodates spatial dependence and nonlinear associations. Predictions were generated on a uniform hexagonal grid at 0.73 km2 resolution (H3 level 8). Out-of-sample predictions aggregated to the H3 level 8 grid showed good agreement with observed concentrations (Pearson r=0.64), while household-level predictions exhibited more moderate agreement (r=0.45). The model produced well-calibrated uncertainty estimates, with 24.1% of held-out observations exceeding the predicted 75th-percentile threshold. Maps of predicted radon concentrations and the probability of exceeding the U.S. EPA action level of 148 Bq/m3 (4 pCi/L) revealed substantial fine-scale spatial heterogeneity that was not apparent in conventional coarse-resolution summaries, with greater local variability observed in densely monitored urban counties than in sparsely sampled regions. High-resolution radon models that explicitly quantify uncertainty provide a useful framework for characterizing the spatial distribution of indoor radon and identifying areas of elevated exceedance risk. These findings highlight the value of fine-scale monitoring data and uncertainty-aware modeling approaches for radon exposure assessment, environmental risk characterization, and radon-related health research.

Wu, Yunhan [ORNL] (ORCID:0000000178842994)↗
NASA NTRSDate not supplied

Plume Impingement Software Module for Real-Time Proximity Operations

Successfully executing proximity operations in space, such as docking or in-orbit servicing, requires sophisticated spacecraft design that accounts for induced environments. As a chaser vehicle’s attitude control thrusters fire, they create rarefied plumes that can impact the target vehicle, with the potential to overload components, exceed thermal limits, and spin the target vehicle out of control. High-fidelity simulations of the thruster plume impingement environment require the direct simulation Monte Carlo (DSMC) method, but DSMC is too computationally expensive to simulate proximity operations that involve thousands of thruster firings. For this analysis to be tractable, engineering models of the plume flowfield and impingement events are used to simulate these trajectories [1]. Currently, on-orbit plume impingement environments are modeled through an inefficient open-loop analysis cycle where the vehicle’s flight controller and plume impingement teams iterate on the trajectories until they pass the target vehicle’s plume requirements. As complex on-orbit missions evolve and become more frequent, lengthy design cycles will become operational bottlenecks. To address this gap, this work develops an advanced plume impingement module capable of operating at real-time scale that can be integrated with existing mission planning tools and onboard flight systems. The plume module leverages state-of-the-art plume simulation techniques [2] to deliver fast, physics-based impingement predictions in a software architecture that can be tailored to diverse proximity operations scenarios. A prototype of this plume impingement module is built to demonstrate the feasibility of real-time performance. This prototype completes plume impingement calculations in microseconds per target geometry mesh point. The software serves as a foundational capability for plume-aware trajectory design, operational risk assessment, and future autonomous decision-making systems.

Plume Impingement↗
NASA NTRS2026

The Thermal and Kinematic Sunyaev–Zeldovich Effect in Galaxy Clusters and Filaments Using Multifrequency Temperature Maps of the Cosmic Microwave Background A399–A401 Cluster Pair Case Study

We present a multifrequency and multi-instrument methodology to study the physical properties of galaxy clusters and cosmic filaments using cosmic microwave background observations. Our approach enables simultaneous measurement of both the thermal (tSZ) and kinematic Sunyaev–Zeldovich (kSZ) effects, incorporates relativistic corrections, and models astrophysical foregrounds such as thermal dust emission. We do this by jointly fitting a single physical model across multiple maps from multiple instruments at different frequencies, rather than fitting a model to a single Compton-y map. We demonstrate the success of this method by fitting the A399–A401 galaxy cluster pair and filament system using archival data from the Planck satellite and new, targeted deep data from the Atacama Cosmology Telescope, covering 11 different frequencies over 14 maps from 30 GHz to 545 GHz. Our tSZ results are consistent with previous work using Compton-y maps. We measure the line-of-sight peculiar velocities of the cluster–filament system using the kSZ effect and find statistical uncertainties on individual cluster peculiar velocities of ≲600 km s −1 , which are competitive with current state-of-the-art measurements. Additionally, we measure the optical depth of the filament component with a signal-to-noise of 8.5σ and reveal hints of its morphology. This modular approach is well-suited for application to future instruments across a wide range of millimeter and submillimeter wavebands.

Ajay S Gill↗
DOE OSTI2026

In Situ UV–vis Quantification of Chlorobasicity in Binary Molten Chlorides

Optical basicity measurements provide a basis for determining the relative chlorobasicity of a given molten salt composition. This study uses Bi3+ as a spectroscopic probe to investigate optical basicity across three binary molten chloride systems (LiCl-KCl, MgCl2–KCl, and ZnCl2–KCl) through in situ UV–vis spectroscopy measurements of the 1S0→3P1 transition. LiCl-KCl systems exhibit the highest optical basicity with minimal compositional dependence, while both divalent systems show stronger, yet nonlinear, dependence that is reminiscent of acid–base titration curves. The influence of cation electronegativity and polarizing power (Li+ < Mg2+ < Zn2+) directly reflects the basicity curves, with ZnCl2–KCl displaying the steepest gradients and lowest basicity values. Nonlinear dependencies in divalent systems indicate formation of chloride-bridged network structures with coordination states dictated by the amount of KCl in a salt composition, which was further investigated and validated by molecular dynamics simulations of polymeric structures formed in ZnCl2 and MgCl2-based salts using machine learning force fields. The temperature dependence of chlorobasicity in terms of optical basicity was investigated, and a loose, positive correlation between the two was revealed. These findings establish Bi3+ as a sensitive probe for understanding electronic environments in molten chloride systems and provide insights for predicting the chemical behavior of molten salts for use in high-temperature environments.

Buttice, Kailee [Department of Nuclear Engineering↗
DOE OSTI2023

Host galaxies of ultra-strong Mg ii absorbers at z ∼ 0.7

ABSTRACT We report spectroscopic identification of the host galaxies of 18 ultra-strong Mg ii systems (USMg ii) at 0.6 ≤ z ≤ 0.8. We created the largest sample by merging these with 20 host galaxies from our previous survey within 0.4 ≤ z ≤ 0.6. Using this sample, we confirm that the measured impact parameters ($\rm 6.3\leqslant D[kpc] \leqslant 120$ with a median of 19 kpc) are much larger than expected, and the USMg ii host galaxies do not follow the canonical $\rm {\it W}_{2796}-{\it D}$ anticorrelation. We show that the presence and significance of this anticorrelation may depend on the sample selection. The $\rm {\it W}_{2796}-{\it D}$ anticorrelation seen for the general Mg ii absorbers show a mild evolution at low $\rm W_{2796}$ end over the redshift range 0.4 ≤ z ≤ 1.5 with an increase of the impact parameters. Compared to the host galaxies of normal Mg ii absorbers, USMg ii host galaxies are brighter and more massive for a given impact parameter. While the USMg ii systems preferentially pick star-forming galaxies, they exhibit slightly lower ongoing star-forming rates compared to main sequence galaxies with the same stellar mass, suggesting a transition from star-forming to quiescent states. For a limiting magnitude of mr < 23.6, at least 29 per cent of the USMg ii host galaxies are isolated, and the width of the Mg ii absorption in these cases may originate from gas flows (infall/outflow) in isolated haloes of massive star forming but not starbursting galaxies. We associate more than one galaxy with the absorber in $\ge 21~{{\ \rm per\ cent}}$ cases, where interactions may cause wide velocity spread.

Astronomy & Astrophysics↗
NASA NTRS1964

Performance of Solar Reflectors When Applied to Storage of Cryogenic Propellants in Space

An analysis was performed to determine the effectiveness of solar reflectors in reducing heat transfer through the insulation of cryogenic fuel tanks located in deep space. A solar reflector, as used herein, is defined as a surface having a ratio of absorptance with respect to solar radiation to hemispherical emittance (α/ϵ) less than 1.0. This analysis considers the effect of surface coatings with α/ϵ values varying from 0.1 to 1.0 when applied to the external surfaces of bulk insulation or multifoil insulation. Results were obtained in terms of heat leak to two cryogenic propellants, liquid hydrogen and liquid oxygen, when stored at Mars, Earth, and Mercury orbital distances from the sun. The results show that, with sufficiently good insulation and low heat leaks to the propellant, α/ϵ is a reasonable criterion of merit for these coatings, but that, at larger heat leaks, consideration of ϵ (or α) is necessary. It was observed that selective finishes of α/ϵ = 0.1 on a given amount of bulk insulation material can reduce the heat leak to 40 to 55 percent of the heat leak obtained when gray finishes are considered. Or, for equivalent heat leaks, a reduction in bulk insulation material thickness of about one-half is possible with high-quality selective finishes (α/ϵ = 0.1) compared with flat reflectors. Larger benefits may be achieved from selective finishes painted on foils; the analysis shows that heat leak may be reduced tenfold for surfaces with an α/ϵ of 0.1 compared with gray surfaces. Again, consideration of equivalent heat leaks indicates that the use of approximately 10 times fewer foils of emissivity 0.05 is possible when spectrally selective surfaces are employed. The present state of the art in achieving such surfaces is also briefly reviewed.

Propellant Storage↗
NASA NTRS2026

NASA Hybrid Thermally Efficient Core (HyTEC) Phase 2 Q3’GFY25 to Q2’GFY26 Unlimited Rights Annual Report for CLIN 1 and 2

The HyTEC Phase 2 Project focuses on the development and demonstration of high-power density, small engine core gas turbine engine technologies. The focus of HyTEC on these small engine core technologies will provide direct benefits to the next single-aisle class aircraft in terms of thermal efficiency, as well as integrate with other technologies, through increased hybridization, as they mature to provide substantial continuous fuel burn reductions during the aircraft lifecycle. These advances will strengthen the US position in the commercial aviation engine market and enable cost benefits in commercial aviation. In Government fiscal year 26 the HyTEC Project was closed and contract moved to the Subsonic Vehicle Technologies and Tools Project. GE Aerospace is executing two major work plans as part of the HyTEC Phase 2 contract. The first is Contract Line-Item Number (CLIN) 001 and its objective is to mature High Pressure Turbine (HPT) aerodynamics technology to TRL 5 through multiple rigs so that it may be incorporated into a complete TRL 6 evaluation and unlock learnings for the engine core demonstration as applicable. CLIN 002, the second work plan, is to design, procure and test a cost shared portion of technologies on the TRL6 Compact Core test vehicle. The compact core demonstrated through HyTEC Phase 2 along with the HPT rig TRL advancement directly matures the technologies being developed as part of the CFM RISE demonstrator program which is targeting a more than 20% fuel burn reduction at the engine level versus today’s state of the art. The RISE program’s objective is to advance both the novel Open Fan architecture, compact core technologies and advanced systems such as hybrid electric needed to achieve the desired fuel burn reduction to TRL6 ahead of a new product introduction in the single-aisle class aircraft in the 2030s timeframe.

gas turbine engine↗
NASA NTRSDate not supplied

Evaluation of Low-Energy Hydrogen Separation Method Using Metal-Organic Frameworks (MOFs) for Closed-Loop ECLSS Air Revitalization (CLEAR)

The State-of-the-Art (SOA) air revitalization architecture onboard the International Space Station (ISS) recovered approximately 50% of the oxygen (O 2 ) from metabolic carbon dioxide (CO 2 ) via the Sabatier process from 2011 to 2017. O 2 recovery is currently constrained by the limited availability of reactant hydrogen (H 2 ) preventing complete conversion of CO 2 to H 2 O. Increasing O 2 recovery within Closed-Loop ECLSS is essential to reducing resupply mass for long-duration manned missions; specifically focusing on water (H 2 O) which supplies H 2 for Sabatier via water electrolysis. Past ground test endeavors at Marshall Space Flight Center (MSFC) have attempted to recover H 2 from Sabatier-produced CH 4 using technologies such as carbon vapor deposition (CVD) and plasma pyrolysis. The byproducts of these technologies can act as a catalyst poison or reactor deadload to the Sabatier reactor. Hydrogen separation techniques must be utilized to maintain the Sabatier catalyst during gas recycling and must be scalable, non-energy intensive, and safe to operate in a habitation setting. Research indicated that metal-organic frameworks (MOFs) could meet these criteria and were tested for their capability to capture the various carbon-based gaseous products of CVD and plasma pyrolysis such as acetylene (C 2 H 2 ), ethylene (C 2 H 4 ), ethane (C 2 H 6 ), and carbon monoxide (CO) which would purify the hydrogen gas stream passing through the MOF. A sub-scale adsorption column was developed by Marshall Space Flight Center to test three MOF candidates against a synthetic gas mixture comprised of process-relevant carbonous gases and hydrogen to evaluate the separation capability of the MOFs. The results of the hydrogen separation capability, isothermal desorption capability, and demonstrated cyclic reuse of the MOF are presented in this paper.

Kagen Crawford↗
NASA NTRSDate not supplied

Physics-Guided Deep Learning for Complex System Health Management and Decision Making

The landscape of complex engineered systems is rapidly evolving, from smart manufacturing facilities to next-generation transportation vehicles. As these systems become increasingly sophisticated and interconnected, the need for advanced health management systems grows ever more critical. These systems must go beyond simple monitoring, actively predicting potential failures before they occur. This paradigm shift from fixed maintenance schedules to condition-based predictions is key to optimizing system performance, enhancing safety, and paving the way for autonomous decision-making across various industries. Whether in industrial processes, energy systems, or advanced transportation, the ability to anticipate and prevent failures is becoming a cornerstone of operational excellence. To accurately predict the future health of any complex system, knowledge of its current health state and future operational conditions is essential. Recent advancements in data-driven algorithms have generated growing interest in artificial intelligence for industrial applications. However, the limitations of pure data-driven methods, particularly in industries where data acquisition is costly and limited, have become apparent. This has led to a focus on blending physics with data-driven algorithms, mitigating the drawbacks of both approaches while emphasizing their respective advantages. This research proposes a novel framework for integrating physics-based performance models with deep learning algorithms for the prognostics of complex safety-critical systems. In this approach, physics-based models serve as a blueprint, capturing fundamental system behaviors, while deep learning algorithms, leveraging real-world sensor data, fill in gaps and identify subtle patterns indicative of potential problems. This hybrid methodology, utilizing techniques such as Physics-Informed Neural Networks (PINNs), offers a powerful solution for predicting system health. By fusing domain knowledge with data-driven insights, this approach promises more accurate, adaptable, and reliable models for health prediction. The resulting framework is versatile, applicable across various sectors including aerospace, manufacturing, and energy systems, ultimately contributing to safer, more efficient operations in our increasingly complex technological landscape.

Diagnostics↗
DOE OSTI2026

Compatibility of Type 304H Stainless Steel in Static Molten FLiBe for Inertial Confinement Fusion Reactors: Role of Impurities and Redox Control

Molten fluoride salts, such as FLiBe (LiF-BeF2), are promising candidates for tritium breeding and heat transfer in fusion reactors, but corrosion of structural materials remains a major challenge. This study investigates the corrosion behavior of austenitic stainless steel 304H in purified and NiF2-containing FLiBe at 500°C and 600°C, focusing on the effects of impurities and redox control. Exposure to purified FLiBe resulted in the concurrent depletion of Cr, Mn, and Fe, with corrosion at 500 °C dominated by the combined oxide formation and elemental dissolution, while at 600°C elemental depletion was predominant. The addition of a controlled NiF2 impurity significantly accelerated corrosion at both temperatures, demonstrating the sensitivity of 304H to the salt redox state. Beryllium additions were effective in mitigating corrosion for both baseline and NiF2-containing FLiBe; minimal depletion of Cr, Mn, and Fe occurred with Be additions as low as 2.5 mg (147 wppm), and no NiBe intermetallics formed at 5 mg (294 wppm), indicating that small Be inventories can provide substantial protection without deleterious phase formation. Thermodynamic equilibrium and coupled thermodynamic-kinetic analyses at the salt-alloy interface suggested low corrosion rates in systems with limited hydrogen fluoride (HF) generation, highlighting the importance of salt redox control. Estimates for a Be addition rate were calculated for the HYLIFE-II fusion reactor that can mitigate corrosion-induced degradation, assuming complete conversion of tritium to tritium fluoride (TF). Overall, 304H shows reasonable compatibility with FLiBe under optimized redox conditions. These results provide quantitative guidance for material selection and salt management in fusion blanket and heat exchanger systems and motivate validation under flowing, nonisothermal, and irradiated conditions.

Pillai, Rishi [ORNL] (ORCID:0000000243688197)↗
DOE OSTI2025

AUTOIGNITION DELAY TIMES FOR REFORMATE GAS MIXTURES FROM METHANE GAS ENGINES

Methane slip is a prominent issue in natural gas reciprocating engines that are used in transportation and marine applications. The incomplete combustion that results in methane slip can be resolved with the introduction of hydrogen within the combustion mixture to improve methane oxidation and further enable combustion within the engine crevices where methane has previously remained unreacted. Steam methane reforming (SMR) is a common method used to produce hydrogen and can be used to design an onboard device to reduce methane slip from reciprocating engines. The development of this reformer device requires the validation of high-fidelity chemical kinetic models at the low temperatures of the crevice volumes of these engines. In this work, auto-ignition data is obtained using a shock tube at lean (φ—0.714 or λ—1.4) and stoichiometric (φ, λ = 1) equivalence ratios spanning a temperature range of 1042–1234 K at the 80-bar operating pressure of the test engine. Blends of methane, hydrogen, and reformate products from the SMR reaction are shock-heated in synthetic air, with the ignition delay time measured using an OH* chemiluminescence detector at 310 nm and a CH* detector at 430 nm. The experimental results are compared to several state-of-the-art chemical kinetic mechanisms from the literature. In general, most of the mechanisms show very good agreement with experiments at higher temperatures, with simulation results showing little deviation from experiments at lower temperatures. A sensitivity analysis was conducted, and the results reveal that the reaction H2 + CH3O2 = H + CH3O2H has a very significant role in determining low-temperature ignition delay times (IDTs) of SMR mixtures. These findings provide valuable insights into the chemical kinetics governing methane reformate combustion and contribute to the optimization of onboard reformer designs aimed at mitigating methane slip in natural gas-fueled engines.

Fraze, Matthew↗