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1,162 records · Page 46

2005 NASA Seal/Secondary Air System Workshop

The 2005 NASA Seal/Secondary Air System workshop covered the following topics: (i) Overview of NASA’s new Exploration Initiative program aimed at exploring the Moon, Mars, and beyond; (ii) Overview of the NASA-sponsored Propulsion 21 Project; (iii) Overview of NASA Glenn’s seal project aimed at developing advanced seals for NASA’s turbomachinery, space, and reentry vehicle needs; (iv) Reviews of NASA prime contractor, vendor, and university advanced sealing concepts including tip clearance control, test results, experimental facilities, and numerical predictions; and (v) Reviews of material development programs relevant to advanced seals development. Turbine engine studies have shown that reducing high-pressure turbine (HPT) blade tip clearances will reduce fuel burn, lower emissions, retain exhaust gas temperature margin, and increase range. Several organizations presented development efforts aimed at developing faster clearance control systems and associated technology to meet future engine needs. The workshop also covered several programs NASA is funding to develop technologies for the Exploration Initiative and advanced reusable space vehicle technologies. NASA plans on developing an advanced docking and berthing system that would permit any vehicle to dock to any on-orbit station or vehicle. Seal technical challenges (including space environments, temperature variation, and seal-on-seal operation) as well as plans to develop the necessary “androgynous” seal technologies were reviewed. Researchers also reviewed tests completed for the shuttle main landing gear door seals.

Hypersonic

Behavior of HfB2-SiC Materials in Simulated Re-Entry Environments

The objectives of this research are to: 1) Investigate the oxidation/ablation behavior of HfB2/SiC materials in simulated re-entry environments; 2) Use the arc jet test results to define appropriate use environments for these materials for use in vehicle design. The parameters to be investigated include: surface temperature, stagnation pressure, duration, number of cycles, and thermal stresses.

Don Ellerby

Thermal Analysis on Large Format Lithium-Ion Batteries in Thermal Runaway

Lithium-ion (Li-ion) batteries can deliver electrical power across a large range of applications, and large format versions of these batteries are common in aerospace for their low mass and energy dense properties. Li-ion cells usage has increased as they are more power dense than fuel cells and have overall higher performance over lead-acid/NiCd batteries. However, Li-ion cells can experience Thermal Runaway (TR) via electro-chemical, mechanical, or thermal abuse. TR is a phenomenon where the stored energy in a cell is rapidly released along with vented gases and other effluents. A cell is generally determined to be in TR if its internal heat generation has surpassed its ability to dissipate that heat. If a Li-ion cell enters TR, propagation within the battery may occur. Propagation is the chain reaction that can occur to nearby cells due to a cell that has entered TR initially. Understanding a battery’s susceptiveness to propagation is necessary to evaluate risks associated with TR phenomenon. To determine if a battery is designed in a sufficient manner to prevent battery propagation if single cell TR occurs, testing and thermal analysis of the battery must be conducted. The presentation for TFAWS 2026 will cover considerations for battery TR thermal analysis, such as: testing methods, influences on the cells, failure mechanisms, and TR parameters. This presentation will include a walkthrough of an example battery TR thermal analysis, and the results thereof.

Lithium Ion Batteries

Mechanochemically responsive polymer enables shockwave visualization

Abstract Understanding the physical and chemical response of materials to impulsive deformation is crucial for applications ranging from soft robotic locomotion to space exploration to seismology. However, investigating material properties at extreme strain rates remains challenging due to temporal and spatial resolution limitations. Combining high-strain-rate testing with mechanochemistry encodes the molecular-level deformation within the material itself, thus enabling the direct quantification of the material response. Here, we demonstrate a mechanophore-functionalized block copolymer that self-reports energy dissipation mechanisms, such as bond rupture and acoustic wave dissipation, in response to high-strain-rate impacts. A microprojectile accelerated towards the polymer permanently deforms the material at a shallow depth. At intersonic velocities, the polymer reports significant subsurface energy absorption due to shockwave attenuation, a mechanism traditionally considered negligible compared to plasticity and not well explored in polymers. The acoustic wave velocity of the material is directly recovered from the mechanochemically-activated subsurface volume recorded in the material, which is validated by simulations, theory, and acoustic measurements. This integration of mechanochemistry with microballistic testing enables characterization of high-strain-rate mechanical properties and elucidates important insights applicable to nanomaterials, particle-reinforced composites, and biocompatible polymers.

Science & Technology - Other Topics

EMU Battery/module Service Tool Characterization Study

The power tool which will be used to replace the attitude control system in the SMM spacecraft is being modified to operate from a self contained battery. The extravehicular mobility unit (EMU) battery, a silver zinc battery, was tested for the power tool application. The results obtained during show the EMU battery is capable of operating the power tool within the pulse current range of 2.0 to 15.0 amperes and battery temperature range of -10 to 40 degrees Celsius.

Palandati, C. F.

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

Conditional diffusion machine-learning framework for mapping valence electron distribution from convergent beam electron diffraction

Quantitative convergent beam electron diffraction (CBED) enables determination of aspherical valence electron distributions through refinement of low-order structure factors, which are highly sensitive to chemical bonding and charge density variations. However, conventional quantitative CBED (QCBED) requires solving a highly nonlinear inverse problem with many coupled parameters, and computationally intensive dynamical diffraction calculations, making it time-consuming and difficult to apply to complex systems. More broadly, reconstructing charge density and orbital electron distribution from diffraction data has long been a central challenge in both x-ray and electron crystallography. Here, in this study, we introduce an artificial-intelligence (AI)-based framework that replaces traditional refinement with a data-driven inverse solver. Using a large synthetic CBED dataset generated by Bloch-wave simulations, we train a conditional diffusion model to directly infer crystal structural parameters and multipole density formalism parameters, and hence valence electron distributions, from CBED patterns alone. By learning from forward simulations across realistic parameter space, the model effectively solves the inverse problem. Compared with direct regression approaches, the diffusion-based framework provides posterior parameter distributions for rigorous uncertainty quantification while preserving quantitative fidelity and reducing analysis time by orders of magnitude. By eliminating the need for external single-crystal x-ray diffraction data and complex nonlinear refinement, this approach enables practical, high-throughput, and in situ quantitative CBED, enabling real-time mapping of valence electron distributions and their correlation with functional responses in quantum and energy materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND

Geosynchronous Performance of a Lithium-titanium Disulfide Battery

An ambient temperature rechargeable Lithium-Titanium disulfide (Li-TiS2) five cell battery has completed the first orbital year of accelerated synchronous orbit testing. A novel charge/discharge, state of charge (SOC) control scheme is utilized, together with taper current charge backup to overcome deleterious effects associated with high end of charge and low end of discharge voltages. It is indicated that 10 orbital years of simulated synchronous operation may be achieved. Preliminary findings associated with cell matching and battery performance are identified.

Otzinger, B.

Insights into the thermo-hydraulic properties of compacted MX80 bentonite during hydration under elevated temperature

In high-level radioactive waste geological repositories, compacted bentonite undergoes coupled thermo-hydraulic processes due to heat released from a central waste canister and groundwater imbibition from the surrounding host rock. An understanding of these processes is essential for long-term simulations of radionuclide migration and canister corrosion, which requires an understanding of temperature effects on the coupled thermo-hydraulic properties governing these processes. In this study, a tank-scale radial infiltration test was used to investigate water imbibition processes in compacted bentonite under a central heater temperature of 200 °C that simulates high thermal gradients in a repository. Interpretation of this test focuses on evaluation of the liquid water wetting front during hydration and the interpretation of the temperature-dependent transient soil water retention curve (SWRC), thermal conductivity function (TCF), and hydraulic conductivity function (HCF). The SWRC during imbibition follows a temperature-dependent wetting path. Temperature effects on the hydraulic conductivity of bentonite in saturated conditions had the greatest effect on the shape of the HCF, with minimal temperature effects at higher suctions. The transient thermal conductivity data matched well with a new TCF linked with the SWRC shape. Although the bentonite layer was restrained, local deformations during hydration may have affected the shapes of the TCF and HCF.

Engineering

Transient Studies of G-Induced Capillary Dryout and Rewet

A transient, one-dimensional numerical code is developed to model the liquid motion in an axial groove with square cross section. Axial variation in liquid level, shear stress and heat transfer between the groove wall and the liquid, evaporation and transient body forces are accounted for in the model. Dryout and rewet of the groove are allowed; the front location is determined numerically using conservation of mass and linear extrapolation. Several numerical test results are presented and discussed.

M K Reagan

A Cryogenic Seven-Element HEMT Front End for DSS 13

A cryogenically cooled Ka-band (33.6-GHz), seven-element front-end array for the DSN was built and tested. This system uses seven high electron mobility transistor (HEMT) low-noise amplifiers cooled by a two-stage closed-cycle refrigerator. All system components from the polarizers to the output isolators are cooled to a physical temperature between 18 and 35 K. The noise temperatures of the individual elements range from 64 to 84 K over a 2.75-GHz bandwidth.

J Bowen

Engineering the Interface: Advanced Surface Technologies for Lunar Dust Management and Equipment Longevity

Through the Artemis program, NASA intends to develop a sustainable human foothold on the Moon, ultimately paving the way for crewed exploration of Mars. The Moon's hostile environment poses numerous obstacles, including exposure to radiation, temperature extremes, micrometeoroid threats, and particularly the persistent problem of lunar dust. Lunar dust impacts nearly every aspect of surface operations through adhesion and abrasion mechanisms, with contamination from anthropogenic activities (landing, rovers) far outweighing natural phenomena. Multiple adhesion pathways contribute to surface contamination in the lunar environment, including van der Waals forces, electrostatic forces, chemical reaction, and magnetic forces from elemental iron deposits. Sharp asperities from micrometeoroid bombardment and atmospheric absence increase interaction potential and enable mechanical interlocking. Low cohesion between dust particles exacerbates these challenges, as minimal interaction potential between dust and nearby surfaces overcomes particle cohesion, causing contamination. Lunar dust adhesion mitigation technologies can be categorized as either active, requiring external energy, or passive, relying on intrinsic material properties. Ultrasonic and electrodynamic technologies have been developed to the highest technology readiness level for active approaches. Passive strategies primarily focus on surface chemistry and topography modifications. At NASA Langley Research Center, approaches include surface migration agents to reduce surface energy, topographical modification using laser ablation patterning, and tailored surface conductivity to reduce intrinsic adhesion force. Performance has been evaluated using custom-built ultrasonic and centrifuge instruments. Plume-surface interactions from lunar landers can propel micrometer-sized particles at velocities up to 1000 m s-1.8 These particles pose risks to landers, habitats and infrastructure, leading to erosion, degradation, and reduced component lifespan. A panel recovered from Surveyor III was determined to have been severely abraded because of lunar dust displaced from the Apollo 12 lunar module that landed 160 m away. The performance of metallic surfaces has been evaluated via high velocity single particle impact using the laser-induced project impact test (LIPIT) facility at the University of Utah. Peridynamics modeling, a form of continuum mechanics that uses a nonlocal approach enabling greater simulation capabilities of crack initiation and fracture, has also been utilized to gain greater insight into material response during impact events. Lunar dust contamination challenges extend to power generation systems and moving equipment. Cables, rotation stages, and other mechanisms may experience limited range of motion and reduced lifetime due to dust infiltration. NASA Langley Research Center has evaluated traditional aerospace alloys, softgoods, wear resistant ceramics, and several polymer and polymer composite materials. Test methods have included traditional techniques like Taber abrasion testing, as well as designed test configurations developed in the DUSTE (dust, ultraviolet radiation, and space thermal environmental) chamber that reproduce mechanism functions in operational environment. Beyond laboratory experiments, several flight experiments have been conducted. Materials were exposed to the low Earth orbit environment on the Materials International Space Station Experiment (MISSE) and to the lunar surface environment through the Aegis Aerospace Regolith Adherence Characterization (RAC) payload and the Honeybee Robotics PlanetVac payload. Determining lunar dust's impact on surface exploration and habitation requires comprehensive experimental and computational capabilities combined with lessons learned from initial lunar activities. Identifying the greatest environmental challenges and developing mitigation technologies provides the clearest path toward successfully, expeditiously, and efficaciously completing NASA's mission. This presentation will discuss ongoing efforts at NASA Langley Research Center and collaborator contributions to these critical objectives.

Surface Engineering

CFD Simulation of the Dosing Behavior within the Atomic Layer Deposition Feeding System

The effective operation of atomic layer deposition (ALD) feeding system is the premise of realizing specific ALD processes. In the present work, a detailed computational fluid dynamics (CFD) model of the feeding system has been developed and validated, which accounts for the roles of ALD valves and manifolds. A numerical simulation of the compressible fluid flow and heat/mass transfer within the feeding system was conducted. The dosing amounts and the spatiotemporal distributions of the precursors can be accurately predicted using the CFD model, as validated by experimental results. Different precursors, operating conditions, and structures of the feeding system were simulated and analyzed to examine the operating flexibility of the feeding system. The simulation results can be adopted as the upstream boundary conditions for simulations of the ALD process in the reaction chamber. The substrate-scale simulation indicates that the effect of the feeding system on the film deposition is highly related to the surface kinetics of ALD. The present work can serve as a guide for the development and optimization of different ALD-based processes via proper operation and even the design of the feeding system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Flame stabilization in DME spray flames under engine-relevant conditions characterized by OH* chemiluminescence and formaldehyde laser-induced fluorescence

The transient and quasi-steady flame structures of Dimethyl Ether (DME) fuel sprays, produced by a single-hole injector (Spray D), were investigated using Planar Laser-Induced Fluorescence (PLIF) and chemiluminescence imaging in a constant-volume chamber under Engine Combustion Network (ECN) Spray A conditions (900 K ambient temperature, 60 bar ambient pressure, 1500 bar injection pressure, and 22.8 kg/m 3 ambient density). Low-temperature chemical reaction zones were visualized using formaldehyde (CH 2 O) PLIF with 355 nm excitation, while high-temperature flame regions were captured via chemiluminescence imaging of excited-state hydroxyl radicals (OH*). Both transient and quasi-steady flame structures clearly show the transition from CH 2 O to OH*, highlighting the progression from low- to high-temperature combustion, while the position of the flame is displaced for DME compared to reference hydrocarbon n-dodecane. Homogeneous reactor calculations with detailed chemistry and using adiabatic mixing for initial temperature show that CH 2 O peaks are significantly higher for DME at the same equivalence ratio, with a higher heat-release during the cool-flame regime with respect to the fuel heating value. Thus, the cool-flame dynamic as a precursor to high-temperature combustion and flame stabilization exhibit distinct behavior for DME relative to conventional hydrocarbons, and these phenomena are effectively resolved through the soot-free nature of DME and the high-speed, time-resolved diagnostics.

CH2O laser-induced fluorescence

Model-based, in-situ, non-destructive qualification and certification of parts made by autonomous additive manufacturing

To address the significant productivity challenges associated with the qualification and certification (Q&C) tasks of additively manufactured (AM) parts, which have traditionally relied on rigorous post‐build inspection and testing, we propose an integrated framework that combines model‐based qualification and certification (MBQ&C) with autonomous additive manufacturing (AAM). MBQ&C employs high‐fidelity predictive models, developed within the Integrated Computational Materials Engineering (ICME) paradigm, to simulate process–structure–property–performance relationships for assessing a part’s fitness for use. Since predictive models are commonly machine learning (ML)-based or reduced-order surrogates of validated physics models, they run efficiently, enabling timely inference. In parallel, the self-driving AAM utilises ML-based adaptive, closed‐loop control strategies to avoid, mitigate, or repair defects and anomalies during fabrication, thereby increasing the likelihood of producing acceptable parts. A key feature of the combined AAM-MBQ&C framework is that predictive models explicitly incorporate defects or anomalies that persist after the build, using instance-specific data captured via in-situ sensing. This customisation enables a build‐specific assessment of fitness for use, rather than relying on nominal or generic parameters. Such individualised evaluation provides a robust basis for Q&C-related acceptance decisions relating to each build. Additionally, the rapid solution capabilities of ML or reduced-order models enable the determination of a part’s suitability for service shortly after build completion. As the framework matures, it has the potential to substantially reduce reliance on conventional point‐design approaches—such as time‐consuming post‐build computed tomography scanning and costly destructive testing. Thus, the AAM-MBQ&C framework represents a transformative, scalable strategy for quality assurance of AM components, as parts produced within a stable, validated, and certified envelope can be certified with reduced testing. Key benefits include: (1) significant gains in Q&C productivity through efficient, model-centric assessment; (2) performance-based classification of defects into critical and non-critical categories; (3) the ability to predict potential deviations in the performance of parts affected by real-time, adaptive process control interventions relative to those produced under a certified process, and (4) the enabling of virtual Q&C for service environments that are difficult, hazardous, or impractical to access or reproduce experimentally. Collectively, these capabilities strengthen the business case for AM, particularly for high‐consequence and mission‐critical applications. Finally, although this work focuses on powder-based AM, the proposed techniques could be extended to AM processes employing alternative feedstock forms.

Gunasegaram, Dayalan

Advanced Space Power PEM Fuel Cell Systems

A model showing mass and heat transfer in proton exchange membrane (PEM) single cells is presented. For space applications, stack operation requiring combined water and thermal management is needed. Advanced hardware designs able to combine these two techniques are available. Test results are shown for membrane materials which can operate with sufficiently fast diffusive water transport to sustain current densities of 300 ma per square centimeter. Higher power density levels are predicted to require active water removal.

PEM

Data Mining for ISHM of Liquid Rocket Propulsion Status Update

This document consists of presentation slides that review the current status of data mining to support the work with the Integrated Systems Health Management (ISHM) for the systems associated with Liquid Rocket Propulsion. The aim of this project is to have test stand data from Rocketdyne to design algorithms that will aid in the early detection of impending failures during operation. These methods will be extended and improved for future platforms (i.e., CEV/CLV).

Ashok Srivastava

Spin‐Polarized Interfaces Redirect CO 2 Reduction From CO to Formate

Achieving high product selectivity in electrocatalytic carbon dioxide reduction (CO 2 RR) remains a critical challenge due to competition between multiple proton-coupled electron-transfer pathways on catalyst surfaces. Meanwhile, chirality-induced spin selectivity (CISS), which enables spin-polarized electron transport through chiral interfaces, has recently emerged as a promising strategy to modulate interfacial electrochemical reactions. Although the CISS effect has been shown to enhance selectivity and efficiency in the spin-sensitive oxygen evolution reaction (OER), its role in regulating CO 2 RR pathways and in stabilizing intermediates remains largely unexplored. Here, chiral molecules (R- and S-1,1′-bi-2-naphthyl-2,2′-diyl hydrogen phosphate, BNP) were integrated with SnO 2 to construct chiral-modified catalysts (R-BNP/SnO 2 and S-BNP/SnO 2 ). Compared with bare SnO 2 and racemic BNP-modified SnO 2 (Rac-BNP/SnO 2 ), the chiral catalysts exhibited a pronounced shift in product selectivity from CO toward formate production. Importantly, in-situ attenuated total reflectance surface-enhanced infrared absorption spectroscopy (ATR-SEIRAS) reveals that the chiral interface selectively stabilizes the O-bound *OCHO intermediate associated with the formate pathway and modulates interfacial water structure and hydrogen-bonding dynamics. These findings demonstrate that spin-polarized interfacial electron transfer can regulate CO 2 RR pathway selectivity by modulating the stabilization of key intermediates. More broadly, this work establishes chiral spin-selective interfaces as a new strategy for regulating competitive electrocatalytic reaction pathways.

14 SOLAR ENERGY