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Chalcogenide is a proven phase change material used in re-writeable CDs and DVDs. This material changes phases, reversibly and quickly, between an amorphous state that is dull in appearance and electrically high in resistance, and a polycrystalline state that is highly reflective and low in resistance. The application of this commercially proven technology to create dense, high-speed, non-volatile semiconductor memories is discussed.
The cyclic oxidation test results for some 1000 high temperature commercial and experimental alloys have been collected in an EXCEL database. This database represents over thirty years of research at NASA Glenn Research Center in Cleveland, Ohio. The data is in the form of a series of runs of specific weight change versus time values for a set of samples tested at a given temperature, cycle time, and exposure time. Included on each run is a set of embedded plots of the critical data. The nature of the data is discussed along with analysis of the cyclic oxidation process. In addition examples are given as to how a set of results can be analyzed. The data is assembled on a read-only compact disk which is available on request from Materials Durability Branch, NASA Glenn Research Center, Cleveland, Ohio.
This report compiles a list of commercial and developmental niobium-based alloys developed during the Space Age (late 1950s through mid-1970s) for extreme-temperature applications, including rocket engine thrust chambers, hypersonic re-entry thermal protection systems, and space fission reactor loops. Niobium (Nb) was widely pursued because it provided the lowest density (~8.6 g/cc) among the primary refractory metals, a high melting temperature (~2470°C), exceptional low-temperature ductility, good formability, and compatibility with liquid alkali metals. An evaluation of physical metallurgy mechanisms, focusing on solid-solution strengthening via heavy refractory solutes (W, Mo, Ta), dual-purpose reactive solutes (Hf, Zr, Ti), and dispersion strengthening using carbides, nitrides, and oxides is presented. Additionally, the report compares Western and Soviet Union metallurgical approaches, explaining how supply chain factors and manufacturing infrastructure influenced element selection, interstitial chemistry, and alloy identification/naming conventions. Cataloging these historical alloy chemical compositions serves as a foundational reference for modern alloy additive manufacturing, thermodynamic CALPHAD modeling, and machine-learning discovery pipelines for next-generation extreme-environment niobium-based alloys.
Batteries are used in a wide variety of applications. In recent years, they have become popular as a source of power for electric vehicles such as cars, unmanned aerial vehicles, and commericial passenger aircraft. In such application domains, it becomes crucial to both monitor battery health and performance and to predict end of discharge (EOD) and end of useful life (EOL) events. To implement such technologies, it is crucial to understand how batteries work and to capture that knowledge in the form of models that can be used by monitoring, diagnosis, and prognosis algorithms. In this work, we develop electrochemistry-based models of lithium-ion batteries that capture the significant electrochemical processes, are computationally efficient, capture the effects of aging, and are of suitable accuracy for reliable EOD prediction in a variety of usage profiles. This paper reports on the progress of such a model, with results demonstrating the model validity and accurate EOD predictions.
This chapter will provide a thorough end-to-end description of the process for evaluation of three different data-driven algorithms for anomaly detection to select the best candidate for deployment as part of a suite of IVHM (Integrated Vehicle Health Management) technologies. These algorithms were deemed to be sufficiently mature enough to be considered viable candidates for deployment in support of the maiden launch of Ares I-X, the successor to the Space Shuttle for NASA's Constellation program. Data-driven algorithms are just one of three different types being deployed [3],[5]. The other two types of algorithms being deployed include a "rule-based" expert system, and a "model-based" system. Within these two categories, the deployable candidates have already been selected based upon qualitative factors such as flight heritage. For the rile-based system, SHINE (Spacecraft High-speed Inference Engine) has been selected for deployment, which is a component of BEAM (Beacon-based Exception Analysis for Multimissions) [4], a patented technology developed at NASA's JPL (Jet Propulsion Laboratory) and serves to aid in the management and identification of operational modes. For the "model-based" system, a commercially available package developed by QSI (Qualtech Systems, Inc.), TEAMS (Testability Engineering and Maintenance System) [1] has been selected for deployment to aid in diagnosis. In the context of this particular deployment, distinctions among the use of the terms "data-driven," "rule-based," and "model-based," call found in [5]. Although there are three different categories of algorithms that have been selected for deployment, our main focus in this chapter will be on the evaluation of three candidates for data-driven anomaly detection. These algorithms will be evaluated upon their capability for robustly detecting incipient faults or failures in the ground-based phase of pre-launch space shuttle operations, rather than based oil heritage as performed in previous studies [5]. Robust detection will allow for the achievement of pre-specified minimum false alarm and/or missed detection rates in the selection of alert thresholds. All algorithms will also be optimized with respect to all of these same criteria. Our study relies upon the use of Shuttle data to act as was a proxy for and in preparation for application to Ares I-X data, which uses a very similar hardware platform for the subsystems that are being targeted (TVC - Thrust Vector Control subsystem for the SRB (Solid Rocket Booster)).
NASA’s Small Spacecraft & Distributed Systems (SSDS) within the Research and Technology Mission Directorate (RTMD) expands U.S. capability to execute unique missions through targeted investment, rapid development, and flight demonstration of small spacecraft technologies applicable to exploration, science and the commercial space sector. SSDS strategically invests in technology development and on-orbit demonstrations executed across NASA, other government agencies, industry, and academia. The program’s University SmallSat Technology Partnerships initiative awards academic researchers with the opportunity to collaborate with NASA to mature innovative technology. Capabilities aligned with RTMD’s technology shortfalls and interests - power, processing, propulsion, sensors, communications, autonomous navigation, architectures, and advanced applications like artificial intelligence (AI), machine learning, and edge computing - are prioritized in SSDS investments. These investments enable distributed, autonomous, and cooperative small spacecraft systems that support swarm missions extending beyond low Earth orbit into cislunar and deep space. This paper highlights representative SSDS flight demonstrations that mature these capabilities to enable a future operational infrastructure needed to support sustained exploration of the Moon and beyond. SSDS’s investment strategy emphasizes rapid development and on-orbit demonstration to validate spacecraft technologies required for swarms and distributed mission architectures. The Starling swarm technology demonstration mission exemplifies this approach by advancing distributed spacecraft autonomy, cooperative operations, and space situational awareness. Extended flight testing and ongoing studies of next generation swarm configurations and on-orbit space traffic monitoring and management continue to inform future swarm designs. DiskSat’s four-spacecraft demonstration mission represents SSDS’s strategic vision to expand the design space for future small spacecraft through its commitment to advance novel platform concepts that can impact how science is performed on orbit. Continuing to invest in future platforms, the notional PY12 concept is a 12-spacecraft swarm hosting neuromorphic processors and is envisioned as an on-orbit testbed for AI, edge computing, and positioning, navigation and timing technologies. SSDS also invests in single-spacecraft technology demonstrations that underpin the success of future swarm missions and accelerate the availability of validated technologies across the small spacecraft ecosystem. Examples of such demonstrations include Pathfinder Technology Demonstrator-3 (PTD-3), which performed high-rate optical communications; PTD-R, which demonstrated a camera capable of simultaneous ultraviolet and short-wave infrared optical sensing; and CAPSTONE, the Cislunar Autonomous Positioning System Technology and Operations Navigation Experiment, which validated autonomous navigation in cislunar space. Collectively, SSDS-funded demonstrations advance capabilities across swarms and illustrate a coordinated investment strategy to mature high-impact technologies required for autonomous, distributed, and cooperative small spacecraft systems for low Earth orbit, cislunar, and deep space applications. Technology demonstrations strengthen SSDS partnerships with industry, academia, and other government agencies, and promote small spacecraft community adoption of capabilities required to close technical gaps for swarm missions.
Integrating CO2 utilization and renewable energy delivery/storage, the rechargeable Li–CO2 battery has been considered as a promising candidate for next-generation secondary batteries. However, high-performance catalyst(s) for efficient formation and decomposition of the discharge product, Li2CO3, are an imperative part of a Li–CO2 battery. The development of flexible Li–CO2 batteries extends their applications into compliant and wearable devices/systems, but at the same time imposes a big challenge for battery fabrication and lifetime enhancement. In this study, a rechargeable quasi-solidus flexible Li–CO2 battery was designed and fabricated using highly active N,S-doped carbon nanotubes (N,S-doped CNTs) as the cathode catalyst, and a smart polymer gel as the flexible electrolyte. This newly-developed flexible Li–CO2 battery exhibited a capacity as high as 23560 mAh g−1 based on the catalyst mass and an ultra-long lifetime of up to 538 cycles with excellent mechanical flexibility. This work provides a platform for the design and development of high-performance flexible Li–CO2 batteries from low-cost, earth-abundant, carbon-based multifunctional cathode catalysts.
Lithium-ion batteries are commonly used to power unmanned aircraft vehicles (UAVs).The ability to model and forecast the remaining useful life of these batteries enables UAV reliability assurance. Building accurate models for battery state of charge and state of health based on first principles is challenging due to the complex electrochemistry that governs battery operations and computational complexity required to solve them. Therefore, reduced order models are often used due to their ability to capture the overall battery discharge. Un-fortunately, these simplifications lead to residual discrepancy between model predictions and observed data. In this paper, we present a hybrid modeling approach merging reduced-order models and neural networks. In this approach, while most of the input-output relationship is captured by Nernst and Butler-Volmer equations, data-driven kernels reduce the gap between predictions and observations. We validate our approach using data publicly available through the NASA Prognostics Center of Excellence repository. Results showed that our hybrid battery prognosis model can be successfully calibrated, even with a limited number of observations.
A Rocket Based Combined Cycle (RBCC) engine system is designed to combine the high thrust to weight ratio of a rocket along with the high specific impulse of a ramjet in a single, integrated propulsion system. This integrated, combined cycle propulsion system is designed to provide higher vehicle performance than that achievable with a separate rocket and ramjet. The RBCC engine system studied in the current program is the Aerojet strutjet engine concept, which is being developed jointly by a government-industry team as part of the Air Force HyTech program pre-PRDA activity. The strutjet is an ejector-ramjet engine in which small rocket chambers are embedded into the trailing edges of the inlet compression struts. The engine operates as an ejector-ramjet from takeoff to slightly above Mach 3. Above Mach 3 the engine operates as a ramjet and transitions to a scramjet at high Mach numbers. For space launch applications the rockets would be re-ignited at a Mach number or altitude beyond which air-breathing propulsion alone becomes impractical. The focus of the present study is to develop and demonstrate a strutjet flowpath using hydrocarbon fuel at up to Mach 7 conditions.
Two widely used family of algorithms, pressure-based and density-based methods, have been developed for computational fluid dynamics (CFD) problems over the years. Pressure-based methods (such as SIMPLE and PISO) use a Poisson-like equation for updating pressure instead of the continuity equation, while density-based methods use the continuity equation to update density (an equation of state is used to provide density in pressure based schemes and pressure in density based schemes). Pressure-based methods were developed originally for incompressible flows at low Reynolds numbers and were then extended to high Reynolds numbers and compressible applications. On the other hand, density based methods were originally developed for transonic flows and have been extended down to low Mach numbers through the use of preconditioning techniques. We compare these two very different approaches to solving the Navier-Stokes equations in order to gain an understanding of their similarities and differences. Specifically, we consider the PISO scheme as a representative pressure-based method and contrast it with a recently developed preconditioning scheme. We also compare the relative performance of the PISO algorithm with a Euler implicit algorithm that is employed to solve the preconditioned equations by means of a vector stability analysis.
Fiber-based materials are extensively used to protect spacecraft during entry. Insulative fibers, often in a fiber network or woven, provide rigidity, strength, and control of material anisotropy and density. Woven thermal protection materials, such as ADEPT (Adaptable, Deployable Entry and Placement Technology), 3D-MAT (3-Dimensional Multifunctional Ablative Thermal Protection), and 3MDCP (3D Woven Mid-Density Carbon Phenolic), enable missions with stronger and denser materials for entry profiles with high shear and heat flux. Vulnerabilities to woven thermal protection materials include manufacturing-induced material property variation, and impact from micrometeoroids. Simulating woven materials under these conditions require models that can resolve hierarchal structures, thermomechanical behavior, and failure. To address this, we simulate weave thermal conduction and mechanical deformation. We simulate the full weave with a coarse-grained yarn model is presented. The model combines a validated, high-resolution single 3MDCP yarn model and phenolic resin model. Instead of modeling every fiber, each yarn ply with order 10, instead of order 1000, fibers. The discrete element bonded particle model (DEM-BPM) of fibers captures the thermal and mechanical behavior within and between fibers. We study the proportion of heat transfer and stress via the contact network, fiber bonds, and overall weave geometry.
Two global-chemistry models for oxidative deposition of jet fuels are evaluated by integrating them into a Computational Fluid Dynamics with Chemistry (CFDC) code. A previously developed two-step global-chemistry model was found to be insufficient to describe the thermal-oxidation and -deposition rates associated with a Jet-A fuel. A new global-chemistry model has been developed systematically based on observations from flowing and static experiments. The global-autoxidation reaction is modified such that the reaction rate becomes zeroth-order with respect to the dissolved oxygen concentration. The generation of deposit-forming precursor is coupled with the autoxidation reaction by introducing a radical species ROO. A formulation for the sticking probability has also been developed. Deposition profiles are well represented by this new model under a variety of temperature and flow conditions. The model correctly predicts the changes in magnitude and spatial location of the deposition peak due to changes in flow. The CFDC model, which is designed for flowing systems, has been extended to static experiments. The model incorporates a non-depleting species F(sub s) representing all non-oxygen compounds responsible for deposition. Static experiments were found to provide a useful and inexpensive method for estimating the concentration of F(sub s) in the fuel.
The exchange of models is one of the most serious problems currently encountered in the practice of spacecraft thermal analysis. Essentially, the problem originates in the diversity of computing environments that are used across different sites, and the consequent proliferation of native tool formats. Furthermore, increasing pressure to reduce the development's life cycle time has originated a growing interest in the so-called spacecraft concurrent engineering. In this context, the realization of the interdependencies between different disciplines and the proper communication between them become critical issues. The use of a neutral format represents a step forward in addressing these problems. Such a means of communication is adopted by consensus. A neutral format is not directly tied to any specific tool and it is kept under stringent change control. Currently, most of the groups promoting exchange formats are contributing with their experience to STEP, the Standard for Exchange of Product Model Data, which is being developed under the auspices of the International Standards Organization (ISO 10303). This paper presents the different efforts made in Europe to provide the spacecraft thermal analysis community with a Thermal Neutral Format (TNF) based on STEP. Following an introduction with some background information, the paper presents the characteristics of the STEP standard. Later, the first efforts to produce a STEP Spacecraft Thermal Application Protocol are described. Finally, the paper presents the currently harmonized European activities that follow up and extend earlier work on the area.
This presentation discusses the manufacturing and scale-up of natural fiber composites for aerospace applications, conducted within NASA’s Convergent Aeronautics Solutions portfolio to advance aircraft capabilities and efficiency. The effort focused on the development and demonstration of two proof-of concept articles, an electric vertical takeoff and landing (eVTOL) propeller skin and a C-channel subcomponent. Best practices and guidance on addressing key challenges with bio-based composite materials and manufacturing are provided.
The endurance life and the friction coefficient of ceramic-bonded calcium fluoride (CaF2) coatings on nickel-base alloys were determined at temperatures from 75° to 1900° F. The specimen configuration consisted of a hemispherical rider (3/16-in. rad.) sliding against the flat surface of a rotating disk. Increasing the ambient temperature (up to 1500° F) or the sliding velocity generally reduced the friction coefficient and improved coating life. Base-metal selection was critical above 1500° F. For instance, cast Inconel sliding against coated Inconel X was lubricated effectively to 1500° F, but at 1600° F severe blistering of the coatings occurred. However, good lubrication and adherence were obtained for René 41 sliding against coated René 41 at temperatures up to 1900° F; no blisters developed, coating wear life was fairly good, and the rider wear rate was significantly lower than for the unlubricated metals . Friction coefficients were 0.12 at 1500° F, 0.15 at 1700° F, and 0.17 at 1800° and 1900° F. Because of its ready availability, Inconel X appears to be the preferred substrate alloy for applications in which the temperature does not exceed 1500° F. René 41 would have to be used in applications involving higher temperatures. Improved coating life was derived by either preoxidizing the substrate metals prior to the coating application or by applying a very thin (<0.0002 in.) burnished and sintered overlay to the surface of the coating. Preoxidation did not affect the friction coefficient. The overlay generally resulted i n a higher friction coefficient than that obtained without the overlay. The combination of both modifications resulted in longer coating life and in friction coefficients intermediate between those obtained with either modification alone.
Microbial monitoring onboard the International Space Station (ISS) is essential for assessing the efficiency of the Environmental Control and Life Support Systems (ECLSS) and providing insight into potential risk to both crew and spacecraft. Historically, this monitoring required the need to culture organisms onboard, return these cultures to Earth, and then complete the identifications, a process that would take months. Over the past decade, and through numerous payloads, advances in molecular biology have enabled in-flight microbial identifications using nanopore sequencing. The swab-to-sequencer method resulting from these efforts was transitioned from research to operations for microbial monitoring under the Crew Health Care Systems (CHeCS) BioMole. Collectively, these accomplishments have propelled the swab-to-sequencer method to be selected as the Microbial Surface Monitor (MSM) for Gateway, as well as a payload on Artemis IV. However, the lack of cold stowage availability for Artemis requires modifications to the entire method due to the thermal instability of the reagents required for sample preparation. To achieve this, new development, optimization, and validations were undertaken. Key considerations included enzyme concentration, buffer compatibility, and equal or enhanced sensitivity and specificity. At each step, thorough side-by-side comparisons with the current ISS method were performed. The development of a robust shelf-stable method will ensure continued sequencing-based microbial monitoring for Artemis and beyond, providing data in near real-time, enhancing risk response time, and yielding clear insight into the microbiome of spacecraft.
Recently there is a growing interest in the aviation sector to reduce air and noise pollution. Electrochemical energy storage devices such as batteries coupled with a distributed electric propulsion system can reduce noise concerns as well as emissions and allow the concept of Urban Air Mobility to come to fruition. The battery performance needs to improve considerably compared from current state-of-art Li-ion battery (about 200Wh/Kg) to realize all-electric passenger jet for short flights (up to 690 miles). NASA is exploring lithium-oxygen battery chemistry to power hybrid (battery powered electrical system) and all-electric aircraft for short distance and long-distance flights. Li-O2 is one of the advanced Li-ion technologies that promise to provide specific energy of more than 750Wh/Kg. For this presentation, we present our work on improving power density of Li-O2 batteries through the use of multiphysics simulations. Next, a path is outlined to port these model to simulate performance for a new battery chemistry for space application, Li-CO2. Li-CO2 uses carbon dioxide as the active material instead of oxygen. Although this technology is in its early development, the offers two benefits: it can be used as a CO2 scrubber, as oxygen is one of the by-products on charging, and as a backup or a standalone battery for various Mars or Venus missions, where the carbon dioxide content in the atmosphere is high and need battery to operate at higher temperatures.
A particle simulation model is developed to study the charge-exchange grid erosion in ion thrusters for both ground-based and space-based operations. Because the neutral gas downstream from the accelerator grid is different for space and ground operation conditions, the charge-exchange erosion processes are also different. Based on an assumption of now electric potential hill downstream from the ion thruster, the calculations show that the accelerator grid erosion rate for space-based operating conditions should be significantly less than experimentally observed erosion rates from the ground-based tests conducted at NASA Lewis Research Center (LeRC) and NASA Jet Propulsion Laboratory (JPL). To resolve this erosion issue completely, we believe that it is necessary to accurately measure the entire electric potential field downstream from the thruster.