Development of a low temperature battery for space probe applications third quarterly report, 24 dec. 1964 - 23 mar. 1965
Test of electrochemical cell and local action mechanisms of wet cell battery for space probe applications
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Test of electrochemical cell and local action mechanisms of wet cell battery for space probe applications
Hand operated shear removes a battery case without disturbing the internal components which are to be tested. It consists of three tool-steel elements, the cutter blade, and a hand lever that provides the mechanical advantage required to cut steel.
In this work, we will discuss observations from images acquired from a time-resolved, high-speed self-aligned focusing Schlieren campaign that was performed at the CW-22 facility at NASA Glenn Research Center to understand the dynamic behavior of thick trailing-edge high-pressure turbine blades simulating a ceramic matrix composite (CMC) construction at high inlet turbulence conditions. For the CMC-9 blade, which has a trailing edge thickness of 9% of the axial chord, we identified a regime where an excessive total pressure loss (loss anomaly) is observed only for a narrow range of Reynolds numbers at a fixed exit Mach number of 0.74. The loss anomaly is qualitatively explained by our images, which were taken at 10 distinct blade Reynolds numbers spanning a factor of 6. The images show a significant increase in energy related to the oscillations due to transonic vortex shedding at the Reynolds numbers related to the high loss conditions. This increased energy leads to the formation of strong acoustic waves that turn into shock waves at the highest loss conditions. From our observations stemming from Spectral POD analysis of the high-speed images, we see the acoustic waves produced by the trailing edge vortex shedding exist in all conditions tested; but the shedding frequency has a very slight trend upwards as the Reynolds number is increased, varying about 6% in the range tested. Considering this variation of shedding frequency as a function of Reynolds number, which is well-established for other bluff-body flows, we stipulate there may be a potential feedback mechanism involving an acoustic information transfer path across neighboring blades that may explain why only a narrow range of Reynolds numbers displays strong, shock-forming vortex shedding. We consider a few feedback paths and examine the timing based on the mean flow field from a high-resolution LES simulation. It appears that all feedback mechanisms are viable, presenting an integer number of delay cycles with respect to disturbances generated at the trailing edge. Most noteworthy, however, is the acoustic/shock-boundary layer interaction mechanism at the blade geometric throat. Based on our analysis, this mechanism likely plays an important role in realistic, curved turbine blade passages.
The design of synthetic soft matter capable of emulating the complex behaviors of living organisms, such as sensing and adapting to their environment, remains an important challenge in developing biomimetic materials. Functionalized hydrogels are ideal candidates for such materials since they are highly responsive to their environment and can be operated in water. In this work, we investigate a hybrid bonding hydrogel composed of peptide amphiphile supramolecular nanofibers covalently attached to a photoresponsive network, in which high-aspect-ratio ferromagnetic nanowires are aligned along the length of the sample, designed to swim under oscillating magnetic fields. This hybrid hydrogel swimmer can autonomously swim toward a light source by utilizing photoinduced interactions between supramolecular and covalent networks reminiscent of phototactic swimming in living systems. Using a combination of experimental techniques and a continuum model incorporating photochemistry, magnetoelasticity, and hydrodynamics, we explain the swimming mechanism and predict phototactic behavior. Our work highlights the potential role of hybrid bonding polymers, which leverage the interplay between supramolecular assemblies and covalent networks. We demonstrate how these polymers can be tailored to react dynamically to their environment, paving the way for developing intelligent and autonomous robotic systems.
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.
Abstract The operation of low‐temperature electrochemical energy conversion systems (fuel cells, electrolyzers) at high pH values is of perennial interest due to the possibility of moving away from expensive platinum group metal catalysts and reducing cost. Historically, the anion exchange membranes (AEMs) and ionomers have been hampered by performance (ionic conductivity, mechanical strength) and chemical stability issues. In this context, select developments over the past decade in alternate AEM chemistries, water management methods, and production of membrane electrode assemblies (MEAs) that have enabled a significant leap in performance of alkaline fuel cells are examined. These developments are linked to performance improvements in alkaline H 2 /O 2 fuel cells and also consider developments in alkaline fuel cells using nitrogen‐containing fuels (ammonia, hydrazine), carbon‐containing fuels (alcohols, glycols), and boron‐containing fuels (sodium borohydride, ammonia borane). Finally, current challenges and bottlenecks are identified, and potential solutions are proposed.
The following topics are presented in viewgraph format: Cosmic Background Explorer (COBE) mission background; battery background and specifications; cell history; battery mechanical/structural design; battery test data; and flowcharts of the various battery approval procedures.
Through this collaborative effort, a new 3D printing platform for ceramics called laser-induced slip casting (LIS) was explored and developed for improving the processing and manufacture of silicon carbide (SiC), a high temperature ceramic material. This method prints layers of ceramic slips/slurries with subsequent selective-laser heating to dry each layer to build a 3D structure. The completed and dried part is then sintered. This manufacturing process is inherently lower cost than alternative ceramic printing methods such as binder jet technology or stereolithography when it comes to the feedstock material but is more expensive than robocasting or direct ink writing. However, it has the potential to make more controlled parts with less defects compared to robocasting. The largest cost is the heating source for the printer. With this technique, there is potential to make large ceramic parts in a near-net shape. Further, there is no known commercial manufacturing of 3D printed ceramics that creates a large range of different high-density ceramics at large scale. The goals and outcomes for the development of the new printing technology were: 1) assessing the technology with alumina by characterizing coupons, 2) printing and sintering of silicon carbide (SiC), and 3) characterization and properties testing of materials printed and a scale-up of SiC part(s). Through this collaborative project, it was sought to provide the best solution to achieving highly dense and near-net shaped ceramic parts at large scale and reduced cost. The goal was to produce high density sintered materials for applications in defense, energy generating systems, armor, and wear parts using 3D printing methods. Variables including powder particle sizes, dispersant molecular weights (MWs), binders, printing parameters, and post processing were explored as well as the characterization of the physical properties (add specifics here).
This work presents an overview of a hyperspectral microwave-photonic spectrometer and demonstrates the system end-to-end noise equivalent delta temperature (NEDT) performance. The system aims at augmenting the remote sensing capability from space, with a focus on the Earth’s planetary boundary layer (PBL) thermal microwave (MW) spectral region (0-200 GHz). Combining a Photonic Integrated Circuit (PIC) channelizer and an application-specific integrated circuit (ASIC) spectrometer, the PIC & ASIC (PICASIC) module is capable of processing 40 GHz spectra at hyperspectral (4 MHz) resolution. The photonic technology is agnostic to the spectral region and multiple photonic modules can cover the entire 200 GHz spectrum. Measured results of the end-to-end system NEDT agree with predicted values confirming that the NEDT is primarily dominated by the noise figure of the MW front-end, with the optical link adding no significant noise. The data also demonstrate that a single module enables simultaneous super- and hyper-spectral resolution channel analysis across a 40 GHz range.
Carbon capture from industrial point sources is an essential component of the global effort to mitigate climate risks. However, traditional approaches require significant energy input—often provided, counterproductively, by fossil fuel combustion. Using sunlight directly as the energy source would significantly improve the energy efficiency of carbon capture processes. Herein, we report the first fully visible-light-driven CO 2 separation system, in which carbon capture is achieved via the photoenolization/addition reaction of inexpensive 2-methylbenzophenone with CO 2 , and CO 2 release is realized through an intramolecular photodecarboxylation reaction. Finally, this system operates isothermally, works with natural sunlight, and facilitates CO 2 removal from natural gas flue emissions, providing a blueprint for other non-thermal chemical separations.
DC brush motors have several qualities which make them very attractive for space flight applications. Their mechanical commutation is simple and lightweight, requiring no external sensing and control in order to function properly. They are extremely efficient in converting electrical energy into mechanical energy. Efficiencies over 80% are not uncommon, resulting in high power throughput to weight ratios. However, the inherent unreliability and short life of sliding electrical contacts, especially in vacuum, have driven previous programs to utilize complex brushless DC or the less efficient stepper motors. The Mars Surveyor Program (MSP'98) and the Shuttle Radar Topography Mission (SRTM) have developed a reliable "long life" brush type DC motor for operation in low temperature, low pressure CO2 and N2, utilizing silver-graphite brushes. The original intent was to utilize this same motor for SRTM's space operation, but the results thus far have been unsatisfactory in vacuum. This paper describes the design, test, and results of this development.
The Habitable Worlds Observatory (HWO) is NASA’s next large space telescope, selected by the 2020 Decadal Survey in Astronomy and Astrophysics to search for and characterize habitable exoplanets while enabling a broad range of transformative astrophysics. In August 2024, the HWO Technology Maturation Project Office (TMPO) was formed to begin exploring the HWO science, technology, and mission architectures toward a Mission Concept Review (MCR) at the end of the decade. A primary deliverable of this effort is this technology development plan that identifies critical technologies that enable the mission, defines a process for assessing the readiness of those technologies, and outlines a strategy for developing those technologies to a Technology Readiness Level (TRL) of 5 before the MCR. This document covers technologies organized along three “tracks”: Coronagraph System technologies, Ultra-stable Telescope System technologies, and High-sensitivity Ultraviolet and Visible Instrumentation technologies. Additional emerging and enhancing technologies are also discussed.
Addressing sustainable energy storage remains crucial for transitioning to renewable sources. While Li‐ion batteries have made significant contributions, enhancing their capacity through alternative materials remains a key challenge. Micro‐sized silicon is a promising anode material due to its tenfold higher theoretical capacity compared to conventional graphite. However, its substantial volumetric expansion during cycling impedes practical application due to mechanical failure and rapid capacity fading. A novel approach is proposed to mitigate this issue by incorporating trace amounts of aluminum into the micro‐sized silicon electrode using ball milling. Density functional theory (DFT) is employed to establish a theoretical framework elucidating how grain boundary sliding, a key mechanism involved in preventing mechanical failure is facilitated by the presence of trace aluminum at grain boundaries. This, in turn, reduces stress accumulation within the material, reducing the likelihood of failure. To validate the theoretical predictions, capacity retention experiments are conducted on undoped and Al‐doped micro‐sized silicon samples. In conclusion, the results demonstrate significantly reduced capacity fading in the doped sample, corroborating the theoretical framework and showcasing the potential of aluminum doping for improved Li‐ion battery performance.
Perfluorosulfonic acid (PFSA) membranes are critical components in proton exchange membrane fuel cells, where performance depends on balancing ionic conductivity, mechanical durability, and chemical stability. This study characterizes a composite membrane (NC700) featuring PFSA-impregnated expanded polytetrafluoroethylene (ePTFE) reinforcement and cerium-based radical scavengers, benchmarked against unreinforced NR211. Complementary techniques, including electron microscopy, X-ray scattering, infrared spectroscopy, thermogravimetric analysis, and dynamic mechanical analysis, identify the structural and compositional strategies employed in NC700. Water sorption isotherms reveal lower water uptake for NC700 across all conditions, attributed to reinforcement and cerium incorporation. Reinforcement reduces in-plane swelling from 11% to 2.1% at 90% RH, confirming strong swelling anisotropy, while maintaining mechanical properties at elevated temperatures. While the ionic conductivity of NC700 is approximately 10% lower than that of NR211, the reduced thickness yields a 40% decrease in calculated area-specific resistance, suggesting the composite architecture can favorably shift the conductivity-stability trade-off. The composite structure also reduces gas permeability, indicating potential for improved separator function alongside favorable transport properties. Systematic deconvolution of reinforcement and additive contributions shows that conductivity losses from cerium incorporation are largely offset by gains from the lower equivalent-weight polymer, providing quantitative relationships that may guide composite membrane design for fuel cells and other electrochemical applications.
Bayesian optimization (BO) can accelerate materials discovery by guiding expensive experiments toward the most promising processing conditions. We systematically compare five BO surrogate and framework combinations (Gaussian processes in Ax, Gaussian processes and Monte-Carlo neural networks in BayBE, random forests in Lolopy, and tree-structured Parzen (TPE) estimators in Hyperopt) on three benchmarks that mimic common materials design tasks (a discrete solid-electrolyte composition space, a hybrid discrete/continuous laminate-composite design problem solved with micromechanics modeling, and the continuous Ishigami analytic function which is a standard optimization benchmark). Each BO surrogate is paired with posterior mean, probability of improvement, and expected improvement acquisition functions and run for 100 trials from randomized initial samples with uniform random search providing a control. Across five random seeds per setting, BayBE’s Gaussian-process surrogate with expected improvement consistently reached ≥95 % of the known optimum in the fewest evaluations, while Lolopy’s random forest matched or exceeded GP performance on purely categorical or mixed spaces at a higher computational cost. Posterior mean alone often stagnated at local optima, underscoring the need for exploration, whereas probability and expected improvement balanced exploration and exploitation leading to better optimization in fewer trials. Execution times ranged from milliseconds for TPE to minutes for neural-network and random-forest surrogates. These results establish baseline expectations for BO in automated materials laboratories and highlight expected improvement with Gaussian processes as a reliable first choice, with random forests offering a strong alternative when categorical variables dominate. The benchmark suite and code are released to facilitate future surrogate, acquisition, and constraint-handling research in data-driven materials optimization.
The Gear Test Assembly (GTA) is an experimental test apparatus built and installed in the Mechanisms and Engineering Test Loop (METL) at Argonne National Laboratory (ANL). While designed to accommodate a variety of components intended for use in advanced compact in-vessel transfer machine, the focus of GTA been the testing of large radial spur gears. The performance of the components used in GTA motivates the choices made in the design, components, and material choices for the forthcoming METL test articles; the Gripper Test Assembly (GrTA), and the Bearing Test Assembly (BTA). To date, GTA has completed nine experimental testing campaigns and achieved over 21 million revolutions under prototypic sodium fast reactor loads and operating conditions. This report provides an overview and results for the two most recent experiments Campaign #8 and Campaign #9. `Campaign #8 was the first campaign to make use of a set of nickel alloy radial spur gears, made from Hastelloy C-22HS, and combined with heat-treated tapered roller bearings. The bearings and torque profile used allowed Campaign #8 to be directly compared with Campaign #1 where Inconel 718 gears were used instead. Campaign #8 attained 1,058,880 shaft revolutions within 23% of the 1,314,855 revolutions achieved in Campaign #1. These results demonstrate that the heat-treated tapered roller bearings show consistent increased lifetimes, approximately three times longer than for non heat-treated taper rollers, and that the particular material of the gear does not play a substantial role in performance. Similar to Campaign #7 where bearing failure resulted in fragmentation and transport of bearing material into the gear teeth led to tooth damage in the Inconel gears, a similar process led to the damage of the Hastelloy gears. Subsequent NDE analysis showed that the damage was only limited to the tooth surface and does not extend into the gear interiors. Based on the NDE reports, the Hastelloy gears can be reconditioned and put back into service for future campaigns as was done for the Inconel gears. Reconditioned Inconel 718 gears damaged in Campaign #7 were returned to service in Campaign #9 and paired with non heat-treated tapered roller bearings. In Campaign #9 a novel set of operating conditions were implemented whereby the gears and bearings were cycled between hot, submerged refueling conditions where fuel handling operations occurred and cold, dry, and inert conditions where the sodium was drained and the vessel was allowed to cool simulating long, ex-vessel storage of the fuel handling machine. A total of eight of these operating cycles were achieved before a bearing failure occurred after the accumulation of 475,692 shaft revolutions were achieved. During Campaign #9, one of the drive motors was damaged and over the course of a 240 day standby period, the entire GTA drive system was upgraded from a 480VAC system to a 240VAC system that provided the opportunity to consolidate wall-space in the METL facility and provide more space for additional test articles being installed in the coming year. The over 475,000 shaft revolutions achieved in Campaign #9 eclipses the previous record for lifetime of non heat-treated tapered roller bearings held by Campaign #3 of 392,000 shaft revolutions. Further analysis and future campaigns hope to shed light on the cause of this approximately 17% increase in lifetime.
Nuclear Safety is a review journal that covers significant developments in the field of nuclear safety. Its scope includes the analysis and control of hazards associated with nuclear energy, operations involving fissionable materials, and the products of nuclear fission and their effects on the environment. Primary emphasis is on safety in reactor design, construction, and operation; however, the safety aspects of the entire fuel cycle, including fuel fabrication, spent-fuel processing, nuclear waste disposal, handling of radioisotopes, and environmental effects of these operations, are also treated. Table of Contents for this issue follows. GENERAL SAFETY CONSIDERATIONS: 325 Safety of Framatome Advanced Nuclear Steam Supply Systems Designs by J. A. Charles and D. Lange, 333 Book Review of Nuclear Accidents: Intervention Levels for the Protection of the Public by H. B. Piper; ACCIDENT ANALYSIS: 335 Living PRA Computer Systems by S. C. Dinsmore and H.-P. Balfanz, 343 Summary of ICAP Assessments of RELAP5/MOD2 by W. E. Driskell and R. G. Hanson; CONTROL AND INSTRUMENTATION: 352 Thermal Performance Monitoring System at Maanshan Nuclear Power Plant by H.-J. Chao, Y.-P. Lin, G.-H. Jou, L.-Y. Liao, and Y.-B. Chen; DESIGN FEATURES: 358 Warning Systems for Nuclear Power Plant Emergencies by J. H. Sorensen and D. S. Mileti; WASTE AND SPENT FUEL MANAGEMENT: 371 Activities Related to Waste Management Compiled by E G. Silver; OPERATING EXPERIENCES: 382 Steam Generator Tube Performance: Experience with Water-Cooled Nuclear Power Reactors During 1985 by O. S. Tatone and R. L. Tapping, 400 Systems Interaction Analyses: Concepts and Techniques (Part II) by M. D. Muhlheim and G. A. Murphy, 413 Reactor Shutdown Experience Compiled by J. W. Cletcher, 416 Operating U.S. Power Reactors Compiled by E G. Silver; RECENT DEVELOPMENTS: 440 General Administrative Activities Compiled by E G. Silver, 460 Reports, Standards, and Safety Guides by D. S. Queener, 466 Status of Power-Reactor Licensing Activities Compiled by E G. Silver, 470 Proposed Rule Changes as of Mar. 31, 1989; ANNOUNCEMENTS: 334 Proceedings Published, 351 CEC Seminar on Methods and Codes for Assessing the Off-Site Consequences of Nuclear Accidents, 357 Short Course on Multiphase Flow and Heat Transfer: Bases and Applications in A: The Nuclear Power Industry B: The Process Industries, 357 International Conference on Probabilistic Safety Assessment and Management, 478 International Topical Meeting on the Safety, Status, and Future of Non-Commercial Reactors and Irradiation Facilities, 475 The Authors.
This article describes the data analysis based on the image frames received at the Solid State Imaging (SSI) camera of the Galileo Optical Experiment (GOPEX) demonstration conducted between December 9 and 16, 1992. Laser uplink was successfully established between the ground and the Galileo spacecraft during its second Earth-gravity-assist phase in December 1992. SSI camera frames were acquired which contained images of detected laser pulses transmitted from the Table Mountain Facility (TMF), Wrightwood, California, and the Starfire Optical Range (SOR), Albuquerque, New Mex/co. Laser pulse data were processed using standard image-processing techniques at the Multimission Image Processing Laboratory (MIPL) for preliminary pulse identification and to produce public re/ease images. Subsequent image analysis corrected for background noise to measure received pulse intensities. Data were plotted to obtain histograms on a dmly basis and were then compared with theoretical results derived from applicable weak-turbulence and strong-turbulence considerations. This article describes processing steps and compares the theories with the experimented results. Quantitative agreement was found in both turbulence regimes, and better agreement would have been found, given more received laser pulses. Future experiments should consider methods to reliably measure low-intensity pulses, and through experimented planning to geometrically locate pulse positions with greater certainty.