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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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NASA NTRS2014

Assessing the Effect of Spaceflight on the Propensity for Astronauts to Develop Disk Herniation

BACKGROUND: A previous study [1] reported that the instantaneous risk of developing a Herniated Nucleus Pulposus (HNP) was higher in astronauts who had flown at least one mission, as compared with those in the corps who had not yet flown. However, the study only analyzed time to HNP after the first mission (if any) and did not account for the possible effects of multiple missions. While many HNP's occurred well into astronauts' careers or in some cases years after retirement, the higher incidence of HNPs relatively soon after completion of space missions appears to indicate that spaceflight may lead to an increased risk of HNP. The purpose of this study was to support the Human System Risk Board assessment of back pain, evaluate the risk of injury due to dynamic loads, and update the previous dataset which contained events up to December 31, 2006. METHODS: Data was queried from the electronic medical record and provided by the Lifetime Surveillance of Astronaut Health. The data included all 330 United States astronauts from 1959 through February 2014. Cases were confirmed by Magnetic Resonance Imaging, Computerized Tomography, Myelography, operative findings, or through clinical confirmation with a neurologist or neurosurgeon. In this analysis, astronauts who had an HNP at selection into the corps or had an HNP diagnosis prior to their first flight were excluded. The statistical challenges in using the available data to separate effects of spaceflight from those associated with general astronaut training and lifestyle on propensity to develop HNPs are many. The primary outcome is reported date of first HNP (if any), which at best is only an approximation to the actual time of occurrence. To properly analyze this data with a survival analysis model, one must also know the "exposure" time - i.e. how long each astronaut has been at risk for developing an HNP. If an HNP is reported soon after a mission, is it mission caused or general? If the former, exposure time should be counted from the time of landing (assuming the risk of HNP occurring during a mission is zero). If the latter, exposure time should be counted from the time of selection; however we can't directly know which one to use. In our analysis we take both of these possibilities into account with a competing risks model, wherein two distinct stochastic processes are going on: TG = time to HNP (general) and TS = time to HNP (spaceflight). Under this type of model, whichever of these occurs first is what we observe; in other words we don't observe TG or TS, only min(TG, TS). Here, we parameterized the model in terms of separate Weibull hazard functions for each process and estimated all parameters using maximum likelihood. In addition, we allowed for a "cured fraction" - i.e. the possibility that some astronauts may never develop an HNP. RESULTS: Results will include a depiction of the competing hazard functions as well as a probability curve for the relative likelihood that an HNP reported at a given time after a mission is actually mission caused. Other factors, such as dwell time in microgravity and vehicle landing environment will be explored. An overall assessment as to whether spaceflight truly exacerbates HNP risk will be made.

Feiveson, A. H.↗
NASA NTRS2010

Estimation and Control for Autonomous Coring from a Rover Manipulator

A system consisting of a set of estimators and autonomous behaviors has been developed which allows robust coring from a low-mass rover platform, while accommodating for moderate rover slip. A redundant set of sensors, including a force-torque sensor, visual odometry, and accelerometers are used to monitor discrete critical and operational modes, as well as to estimate continuous drill parameters during the coring process. A set of critical failure modes pertinent to shallow coring from a mobile platform is defined, and autonomous behaviors associated with each critical mode are used to maintain nominal coring conditions. Autonomous shallow coring is demonstrated from a low-mass rover using a rotary-percussive coring tool mounted on a 5 degree-of-freedom (DOF) arm. A new architecture of using an arm-stabilized, rotary percussive tool with the robotic arm used to provide the drill z-axis linear feed is validated. Particular attention to hole start using this architecture is addressed. An end-to-end coring sequence is demonstrated, where the rover autonomously detects and then recovers from a series of slip events that exceeded 9 cm total displacement.

Hudson, Nicolas↗
NASA NTRS2016

3D Printing in Zero G Technology Demonstration Mission: Summary of On-Orbit Operations, Material Testing, and Future Work

Human space exploration to date has been limited to low Earth orbit and the moon. The International Space Station (ISS), an orbiting laboratory 200 miles above the earth, provides a unique and incredible opportunity for researchers to prove out the technologies that will enable humans to safely live and work in space for longer periods of time and venture farther into the solar system. The ability to manufacture parts in-space rather than launch them from earth represents a fundamental shift in the current risk and logistics paradigm for human spaceflight. In particularly, additive manufacturing (or 3D printing) techniques can potentially be deployed in the space environment to enhance crew safety (by providing an on-demand part replacement capability) and decrease launch mass by reducing the number of spare components that must be launched for missions where cargo resupply is not a near-term option. In September 2014, NASA launched the 3D Printing in Zero G technology demonstration mission to the ISS to explore the potential of additive manufacturing for in-space applications and demonstrate the capability to manufacture parts and tools on-orbit. The printer for this mission was designed and operated by the company Made In Space under a NASA SBIR (Small Business Innovation Research) phase III contract. The overarching objectives of the 3D print mission were to use ISS as a testbed to further maturation of enhancing technologies needed for long duration human exploration missions, introduce new materials and methods to fabricate structure in space, enable cost-effective manufacturing for structures and mechanisms made in low-unit production, and enable physical components to be manufactured in space on long duration missions if necessary. The 3D print unit for fused deposition modeling (FDM) of acrylonitrile butadiene styrene (ABS) was integrated into the ISS Microgravity Science Glovebox (MSG) in November 2014 and phase I printing operations took place from November through December of that year. Phase I flight operations yielded 14 unique parts (21 total specimens) that could be directly compared against ground-based prints of identical geometry manufactured using the printer prior to its launch to ISS. The 3DP unit functioned safely and produced specimens necessary to advance the understanding of the critical design and operational parameters for the FDM process as affected by the microgravity environment. From the standpoint of operations, 3DP demonstrated the ability to remove parts from the build-tray on-orbit, teleoperate the printer from the ground, perform critical maintenance functions within defined human factors limits, produce a functional tool that could be evaluated for form/fit/function, and uplink a new part file from the ground and produce it on the printer. The flight parts arrived at NASA Marshall Space Flight Center in Huntsville, Alabama in April 2015, where they underwent months of testing in the materials and processes laboratory. Ground and flight prints completed the following phases of testing: photographic/visual inspection, mass and density evaluation, structured light scanning, XRay and CT, mechanical testing, optical microscopy, scanning electron microscopy, and chemical analysis. This presentation will discuss the results of this testing as well as phase II operations for the printer, which took place in June and July of 2016. Lessons learned from the tech demo and their impacts on the design and development of the second generation 3D printer for ISS, the Additive Manufacturing Facility (AMF) by Made In Space will also be presented. In addition, progress in other elements of NASA's In Space Manufacturing (ISM) initiative such as the on-demand ISM utilization catalog, in-space Recycler ISS Technology Demonstration development, launch packaging recycling, in-space printable electronics, development of higher strength polymeric materials for 3D printing and Additive Construction by Mobile Emplacement (ACME) will also be addressed.

Prater, Tracie↗
NASA NTRSDate not supplied

Additive Manufactured Ultra-Fine Lattice Structures for Propulsion Catalysts

Traditional mono-propulsion catalysts consist of coated ceramic or graphite foams that possess anisotropic mechanical and fluid properties limiting design, cost, availability, and operational use. Ultra-fine lattice structures are repeating unit cells with ligament thickness as small as 100 μm produced via Additive manufacture (AM). These lattice structures have the potential to replace coated foams used in a mono-propellant system catalysts. AM ultra-fine lattice structures are designed to mimic the operational intent of coated foams but with improved design flexibility, compressive strength, and flow behavior printed from into a single part directly from the preferred platinum metal alloy. The investigation objective was to conduct feasibility studies of AM ultra-fine lattice structures capable of replacing coated foams with superior functionality. NASA MSFC identified desired lattice characteristics and created designs while EOS developed optimized laser powder bed fusion AM parameters to manufacture Ti6Al4V and tungsten specimens. Optimized designs, computational tools, AM parameters, and post-process methods were developed. Specimens underwent x-ray micro-focus CT, metallographic inspection, compression testing, and flow testing. Results demonstrate that AM ultra-fine lattices improved geometric and performance repeatability with the potential for significantly increased availability while decreasing cost and lead time.

Omar R Mireles↗
NASA NTRS2020

Additive Manufactured Ultra-Fine Lattice Structures for Propulsion Catalysts

Traditional mono-propulsion catalysts consist of coated ceramic or graphite foams that possess anisotropic mechanical and fluid properties limiting design, cost, availability, and operational use. Ultra-fine lattice structures are repeating unit cells with ligament thickness as small as 100 μm produced via Additive manufacture (AM). These lattice structures have the potential to replace coated foams used in a mono-propellant system catalysts. AM ultrafine lattice structures are designed to mimic the operational intent of coated foams but with improved design flexibility, compressive strength, and flow behavior printed from into a single part directly from the preferred platinum metal alloy. The investigation objective was to conduct feasibility studies of AM ultra-fine lattice structures capable of replacing coated foams with superior functionality. NASA MSFC identified desired lattice characteristics and created designs while EOS developed optimized laser powder bed fusion AM parameters to manufacture Ti6Al4V and tungsten specimens. Optimized designs, computational tools, AM parameters, and post-process methods were developed. Specimens underwent x-ray microfocus CT, metallographic inspection, compression testing, and flow testing. Results demonstrate that AM ultra-fine lattices improved geometric and performance repeatability with the potential for significantly increased availability while decreasing cost and lead time.

Omar R Mireles↗
NASA NTRSDate not supplied

Additive Manufacture of Ultra-Fine Lattice Structures of Green Propulsion Catalysts

Traditional mono-propulsion catalysts consist of coated ceramic or graphite foams that possess anisotropic mechanical and fluid properties limiting design, cost, availability, and operational use. Ultra-fine lattice structures are repeating unit cells with ligament thickness as small as 100 μm produced via Additive manufacture (AM). These lattice structures have the potential to replace coated foams used in a mono-propellant system catalysts. AM ultrafine lattice structures are designed to mimic the operational intent of coated foams but with improved design flexibility, compressive strength, and flow behavior printed from into a single part directly from the preferred platinum metal alloy. The investigation objective was to conduct feasibility studies of AM ultra-fine lattice structures capable of replacing coated foams with superior functionality. NASA MSFC identified desired lattice characteristics and created designs while EOS developed optimized laser powder bed fusion AM parameters to manufacture Ti6Al4V and tungsten specimens. Optimized designs, computational tools, AM parameters, and post-process methods were developed. Specimens underwent x-ray microfocus CT, metallographic inspection, compression testing, and flow testing. Results demonstrate that AM ultra-fine lattices improved geometric and performance repeatability with the potential for significantly increased availability while decreasing cost and lead time.

Omar Mireles↗
NASA NTRS2020

GeneLab

GeneLab collects and enables analysis of spaceflight and ground-based spaceflight simulation genomic data, RNA and protein expression, and metabolic profiles. It interfaces with other existing databases containing spaceflight omic data. The 2011 National Research Council (NRC) Decadal Survey on NASA Life and Physical Sciences called for increased opportunities for multi-investigator spaceflight opportunities and greater use of genomic approaches to meet the needs of NASA researchers. To address these recommendations of the NRC Decadal Survey, the Space Life and Physical Sciences Research and Applications Division of NASA's Human Exploration and Operations Mission Directorate has initiated a transition to an Open Science architecture to increase research opportunities, and has developed the GeneLab Platform based on highly leveraged and integrated bioinformatics analytics. GeneLab is an interactive, open-access resource where scientists can upload, download, store, search, share, transfer, and analyze omics data from spaceflight and corresponding analogue experiments. Users can explore GeneLab datasets in the Data Repository, analyze data using the Analysis Platform, visualize high-order data and create collaborative projects using the Collaborative Workspace. Our primary goal is to maximize the utilization of the valuable biological research conducted aboard the International Space Station (ISS) by collecting genomic, transcriptomic, proteomic, and metabolomics data known as “omics”. By providing a portal linking processed data to flight parameters, GeneLab enables exploration of the molecular network responses of terrestrial biology to the space environment. This allows researchers to understand the complex responses of biological systems to the space environment. This technology development activity was transferred from the Human Exploration and Operations Mission Directorate to the Science Mission Directorate Division of Biological and Physical Sciences (BPS) in October 2020.

GeneLab↗
NASA NTRS2022

Design of Materials with Alchemite

Machine learning models that establish the relationships between materials processing and properties can enable inverse design of materials through active learning. Alchemite is a commercial software that can perform inverse materials design on sparse data. Here we evaluate Alchemite’s performance on a dataset of shape memory alloys and a dataset of heat exchangers compared to baseline random forest models. Alchemite had higher accuracy when making predictions on sparse data and was more accurate or nearly as accurate as random forests on complete datasets while also quantifying uncertainty. The software was also used to suggest processing steps and design parameters to optimize properties and performance; however, physical validation of the suggested design parameters was beyond the scope of this work. Several useful design insights were gained about the impact of the design parameters on properties and performance including the importance of dopant choice and amount for shape memory alloys and the importance of height and weight on the thermal resistance of heat exchangers.

Machine learning↗
NASA NTRSDate not supplied

Linear Regression Model for Predictive Service Provider Selection

The increasing number of satellites in orbit has led to a growing reliance on third-party service providers for data transfer between Earth and space. Traditional approaches to managing satellite communications require human intervention, which becomes more burdensome with the escalating number of satellites. This research addresses the need for an efficient and automated system to optimize service provider selection for NASA space communication. Previous research has utilized human-operated approaches for service provider management. Our study fills a gap by developing a cognitive algorithm that automates and optimizes the selection process based on various parameters, such as data volume, priority, quality of service and cost. This novel solution reduces user burden, facilitates service management, and contributes to the development of cognitive spaceflight missions, ultimately supporting NASA’s research into Cognitive Communications technology. The algorithm design consists of three major steps: modeling data, developing a Link Selection Algorithm (LSA) based on a grading system, and applying machine learning using linear regression. The LSA evaluates providers based on user-defined constraints, considering factors such as delivery time, cost, and quality of service. We define a suitability metric which allows our algorithm to make a recommendation to a user regarding which commercial service providers to select. The addition of Linear Regression predicts the future suitability value. Our main findings demonstrate that the resulting algorithm can autonomously manage connections between satellites and providers, maximizing communication channel efficiency. This research has significant implications, as it not only addresses a pressing issue in satellite communication management but also advances the field of cognitive spaceflight missions.

Linear regression↗
NASA NTRS1972

Wing optimization for space shuttle orbiter vehicles

The results were presented of a parametric study performed to determine the optimum wing geometry for a proposed space shuttle orbiter. The results of the study establish the minimum weight wing for a series of wing-fuselage combinations subject to constraints on aerodynamic heating, wing trailing edge sweep, and wing over-hang. The study consists of a generalized design evaluation which has the flexibility of arbitrarily varying those wing parameters which influence the vehicle system design and its performance. The study is structured to allow inputs of aerodynamic, weight, aerothermal, structural and material data in a general form so that the influence of these parameters on the design optimization process can be isolated and identified. This procedure displays the sensitivity of the system design of variations in wing geometry. The parameters of interest are varied in a prescribed fashion on a selected fuselage and the effect on the total vehicle weight is determined. The primary variables investigated are: wing loading, aspect ratio, leading edge sweep, thickness ratio, and taper ratio.

Surber, T. E.↗
NASA NTRS1974

Failure criteria for viscoelastic materials

Research projects concerned with developing a theory of fracture of materials are discussed. The effects of the geometry of the structure and the loads acting on the structure as they influence the failure process are analyzed. The effects of the viscoelastic deformation characteristics of the bulk elastomer on failure behavior are examined. Additional material parameters which control the fracture process are identified.

Knauss, W. G.↗
NASA NTRS1993

Comparison of cloud microphysical parameters derived from surface and satellite measurements during FIRE phase 2

Cloud microphysical properties are an important component in climate model parameterizations of water transport, cloud radiative exchange, and latent heat processes. Estimation of effective cloud particle size, liquid or ice water content, and optical depth from satellite-based instrumentation is needed to develop a climatology of cloud microphysical properties and to better understand and model cloud processes in atmospheric circulation. These parameters are estimated from two different surface data sets taken at Coffeyville, Kansas, during the First ISCCP Regional Experiment (FIRE) Phase-2 Intensive Field Observation (IFO) period (November 13 - December 7, 1991). Satellite data can also provide information about optical depth and effective particle size. This paper explores the combination of the FIRE-2 surface and satellite data to determine each of the cloud microphysical properties.

Young, David F.↗
NASA NTRS2000

Coherence Measurements for Excited to Excited State Transitions in Barium

Experimental studies concerning elastic and inelastic electron scattering by coherently ensembles of Ba (...6s6p (sub 1)P(sub 1)) atoms with various degrees of alignment will be described. An in-plane, linearly-polarized laser beam was utilized to prepare these target ensembles and the electron scattering signal as a function of polarization angle was measured for several laser geometries at fixed impact energies and scattering angles. From these measurements, we derived cross sections and electron-impact coherence parameters associated with the electron scattering process which is time reverse of the actual experimentally studied process. This interpretation of the experiment is based on the theory of Macek and Herte. The experimental results were also interpreted in terms of cross sections and collision parameters associated with the actual experimental processes. Results obtained so far will be presented and plans for further studies will be discussed.

Trajmar, S.↗
NASA NTRS1992

Activated transport in AMTEC electrodes

Transport of alkali, metal atoms through porous cathodes of alkali metal thermal-to-electric converter (AMTEC) cells is responsible for significant reducible losses in the electrical performance of these cells. Experimental evidence for activated transport of metal atoms at grain surfaces and boundaries within some AMTEC electrodes has been derived from temperature dependent studies as well as from analysis of the detailed frequency dependence of ac impedance results for other electrodes, including thin, mature molybdenum electrodes which exhibit transport dominated by free molecular flow of sodium gas at low frequencies or dc conditions. Activated surface transport will almost always exist in parallel with free molecular flow transport, and the process of alkali atom adsorption/desorption from the electrode surface will invariably be part of the transport process, and possibly a dominant part in some cases. The temperature dependence of the diffusion coefficient of the alkali metal through the electrode in several cases provides an activation energy and preexponential, but at least two activated processes may be operative, and the activation parameters should be expected to depend on the alkali metal activity gradient that the electrode experiences. In the case of Pt/W/Mn electrodes operated for 2500 hours, limiting currents varied with electrode thickness, and the activation parameters could be assigned primarily to the surface/grain boundary diffusion process.

Williams, R. M.↗
NASA NTRS1995

A simulation to study the feasibility of improving the temporal resolution of LAGEOS geodynamic solutions by using a sequential process noise filter

A key drawback to estimating geodetic and geodynamic parameters over time based on satellite laser ranging (SLR) observations is the inability to accurately model all the forces acting on the satellite. Errors associated with the observations and the measurement model can detract from the estimates as well. These 'model errors' corrupt the solutions obtained from the satellite orbit determination process. Dynamical models for satellite motion utilize known geophysical parameters to mathematically detail the forces acting on the satellite. However, these parameters, while estimated as constants, vary over time. These temporal variations must be accounted for in some fashion to maintain meaningful solutions. The primary goal of this study is to analyze the feasibility of using a sequential process noise filter for estimating geodynamic parameters over time from the Laser Geodynamics Satellite (LAGEOS) SLR data. This evaluation is achieved by first simulating a sequence of realistic LAGEOS laser ranging observations. These observations are generated using models with known temporal variations in several geodynamic parameters (along track drag and the J(sub 2), J(sub 3), J(sub 4), and J(sub 5) geopotential coefficients). A standard (non-stochastic) filter and a stochastic process noise filter are then utilized to estimate the model parameters from the simulated observations. The standard non-stochastic filter estimates these parameters as constants over consecutive fixed time intervals. Thus, the resulting solutions contain constant estimates of parameters that vary in time which limits the temporal resolution and accuracy of the solution. The stochastic process noise filter estimates these parameters as correlated process noise variables. As a result, the stochastic process noise filter has the potential to estimate the temporal variations more accurately since the constraint of estimating the parameters as constants is eliminated. A comparison of the temporal resolution of solutions obtained from standard sequential filtering methods and process noise sequential filtering methods shows that the accuracy is significantly improved using process noise. The results show that the positional accuracy of the orbit is improved as well. The temporal resolution of the resulting solutions are detailed, and conclusions drawn about the results. Benefits and drawbacks of using process noise filtering in this type of scenario are also identified.

Hartman, Brian Davis↗
NASA NTRS2009

Self-Supervised Learning of Terrain Traversability from Proprioceptive Sensors

Robust and reliable autonomous navigation in unstructured, off-road terrain is a critical element in making unmanned ground vehicles a reality. Existing approaches tend to rely on evaluating the traversability of terrain based on fixed parameters obtained via testing in specific environments. This results in a system that handles the terrain well that it trained in, but is unable to process terrain outside its test parameters. An adaptive system does not take the place of training, but supplements it. Whereas training imprints certain environments, an adaptive system would imprint terrain elements and the interactions amongst them, and allow the vehicle to build a map of local elements using proprioceptive sensors. Such sensors can include velocity, wheel slippage, bumper hits, and accelerometers. Data obtained by the sensors can be compared to observations from ranging sensors such as cameras and LADAR (laser detection and ranging) in order to adapt to any kind of terrain. In this way, it could sample its surroundings not only to create a map of clear space, but also of what kind of space it is and its composition. By having a set of building blocks consisting of terrain features, a vehicle can adapt to terrain that it has never seen before, and thus be robust to a changing environment. New observations could be added to its library, enabling it to infer terrain types that it wasn't trained on. This would be very useful in alien environments, where many of the physical features are known, but some are not. For example, a seemingly flat, hard plain could actually be soft sand, and the vehicle would sense the sand and avoid it automatically.

Bajracharya, Max↗
NASA NTRS1999

Loss tolerant speech decoder for telecommunications

A method and device for extrapolating past signal-history data for insertion into missing data segments in order to conceal digital speech frame errors. The extrapolation method uses past-signal history that is stored in a buffer. The method is implemented with a device that utilizes a finite-impulse response (FIR) multi-layer feed-forward artificial neural network that is trained by back-propagation for one-step extrapolation of speech compression algorithm (SCA) parameters. Once a speech connection has been established, the speech compression algorithm device begins sending encoded speech frames. As the speech frames are received, they are decoded and converted back into speech signal voltages. During the normal decoding process, pre-processing of the required SCA parameters will occur and the results stored in the past-history buffer. If a speech frame is detected to be lost or in error, then extrapolation modules are executed and replacement SCA parameters are generated and sent as the parameters required by the SCA. In this way, the information transfer to the SCA is transparent, and the SCA processing continues as usual. The listener will not normally notice that a speech frame has been lost because of the smooth transition between the last-received, lost, and next-received speech frames.

Prieto, Jr., Jaime L.↗
NASA NTRS2024

Independent Scientific Review of Biological Assumptions and Planned Ultraviolet Treatment for Mars Sample Return Backward Planetary Protection

The Backward Planetary Protection Study Team (“the Study Team”), assembled by the Office of the Chief Scientist (OCS) at the request of the Office of Planetary Protection (OPP), has conducted numerous detailed discussions on the potential use of an active ultraviolet (UV) approach for minimizing or eliminating biological contamination of the exterior of the planned Orbiting Sample container (OS) of the Mars Sample Return (MSR) mission. This review of the backward planetary protection (BPP) considerations for the MSR mission focused on two key parameters that are opportunities for further process development to support implementation of planetary protection practices in meeting mission requirements. These parameters include: 1) Sub-cellular biological assumptions – should Mars missions consider self-replicating organisms only or do they need to consider non-self-replicating entities without a cellular organization such as viruses, prions, etc. and macromolecules capable of genetic information transfer, as well? 2) UV biocidal impact – what is the UV fluence in the Mars atmosphere and its associated potential biocidal credit? The assembled subject matter experts (SMEs) in the Study Team are listed in Appendix A, with a brief description of each member’s relevant expertise.

Mamta Patel Nagaraja↗