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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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At least 289 records · Page 16

Effect of Internal Clearance on Load Distribution and Life of Radially Loaded Ball and Roller Bearings

The effect of internal clearance on radially loaded deepgroove ball and cylindrical roller bearing load distribution and fatigue life was determined for four clearance groups defined in the bearing standards. The analysis was extended to negative clearance (interference) conditions to produce a curve of life factor versus internal clearance. Rolling-element loads can be optimized and bearing life maximized for a small negative operating clearance. Life declines gradually with positive clearance and rapidly with increasing negative clearance. Relationships were found between bearing life and internal clearance as a function of ball or roller diameter, adjusted for load. Results are presented as life factors for radially loaded bearings independent of bearing size or applied load. In addition, a modified Stribeck Equation is presented that relates the maximum rolling-element load to internal bearing clearance.

Oswald, Fred B.↗

Uncertainty Quantification in Remaining Useful Life of Aerospace Components using State Space Models and Inverse FORM

This paper investigates the use of the inverse first-order reliability method (inverse- FORM) to quantify the uncertainty in the remaining useful life (RUL) of aerospace components. The prediction of remaining useful life is an integral part of system health prognosis, and directly helps in online health monitoring and decision-making. However, the prediction of remaining useful life is affected by several sources of uncertainty, and therefore it is necessary to quantify the uncertainty in the remaining useful life prediction. While system parameter uncertainty and physical variability can be easily included in inverse-FORM, this paper extends the methodology to include: (1) future loading uncertainty, (2) process noise; and (3) uncertainty in the state estimate. The inverse-FORM method has been used in this paper to (1) quickly obtain probability bounds on the remaining useful life prediction; and (2) calculate the entire probability distribution of remaining useful life prediction, and the results are verified against Monte Carlo sampling. The proposed methodology is illustrated using a numerical example.

Sankararaman, Shankar↗

Real-Time Aircraft Engine-Life Monitoring

This project developed an inservice life-monitoring system capable of predicting the remaining component and system life of aircraft engines. The embedded system provides real-time, inflight monitoring of the engine's thrust, exhaust gas temperature, efficiency, and the speed and time of operation. Based upon this data, the life-estimation algorithm calculates the remaining life of the engine components and uses this data to predict the remaining life of the engine. The calculations are based on the statistical life distribution of the engine components and their relationship to load, speed, temperature, and time.

Klein, Richard↗

Comparison of Models for Ball Bearing Dynamic Capacity and Life

Generalized formulations for dynamic capacity and life of ball bearings, based on the models introduced by Lundberg and Palmgren and Zaretsky, have been developed and implemented in the bearing dynamics computer code, ADORE. Unlike the original Lundberg-Palmgren dynamic capacity equation, where the elastic properties are part of the life constant, the generalized formulations permit variation of elastic properties of the interacting materials. The newly updated Lundberg-Palmgren model allows prediction of life as a function of elastic properties. For elastic properties similar to those of AISI 52100 bearing steel, both the original and updated Lundberg-Palmgren models provide identical results. A comparison between the Lundberg-Palmgren and the Zaretsky models shows that at relatively light loads the Zaretsky model predicts a much higher life than the Lundberg-Palmgren model. As the load increases, the Zaretsky model provides a much faster drop off in life. This is because the Zaretsky model is much more sensitive to load than the Lundberg-Palmgren model. The generalized implementation where all model parameters can be varied provides an effective tool for future model validation and enhancement in bearing life prediction capabilities.

Rolling-element Fatigue↗

NASA Advanced Explorations Systems: Advancements in Life Support Systems

The NASA Advanced Exploration Systems (AES) Life Support Systems (LSS) project strives to develop reliable, energy-efficient, and low-mass spacecraft systems to provide environmental control and life support systems (ECLSS) critical to enabling long duration human missions beyond low Earth orbit (LEO). Highly reliable, closed-loop life support systems are among the capabilities required for the longer duration human space exploration missions assessed by NASA's Habitability Architecture Team (HAT). The LSS project is focused on four areas: architecture and systems engineering for life support systems, environmental monitoring, air revitalization, and wastewater processing and water management. Starting with the international space station (ISS) LSS systems as a point of departure (where applicable), the mission of the LSS project is three-fold: 1. Address discrete LSS technology gaps 2. Improve the reliability of LSS systems 3. Advance LSS systems towards integrated testing on the ISS. This paper summarized the work being done in the four areas listed above to meet these objectives. Details will be given on the following focus areas: Systems Engineering and Architecture- With so many complex systems comprising life support in space, it is important to understand the overall system requirements to define life support system architectures for different space mission classes, ensure that all the components integrate well together and verify that testing is as representative of destination environments as possible. Environmental Monitoring- In an enclosed spacecraft that is constantly operating complex machinery for its own basic functionality as well as science experiments and technology demonstrations, it's possible for the environment to become compromised. While current environmental monitors aboard the ISS will alert crew members and mission control if there is an emergency, long-duration environmental monitoring cannot be done in-orbit as current methodologies rely largely on sending environmental samples back to Earth. The LSS project is developing onboard analysis capabilities that will replace the need to return air and water samples from space for ground analysis. Air Revitalization- The air revitalization task is comprised of work in carbon dioxide removal, oxygen generation and recovery and trace contamination and particulate control. The CO2 Removal and associated air drying development efforts under the LSS project are focused both on improving the current SOA technology on the ISS and assessing and examining the viability of other sorbents and technologies available in academia and industry. The Oxygen Generation and Recovery technology development area encompasses several sub-tasks in an effort to supply O2 to the crew at the required conditions, to recover O2 from metabolic CO2, and to recycle recovered O2 back to the cabin environment. Current state-of-the-art oxygen generation systems aboard space station are capable of generating or recovering approximately 40% of required oxygen; for exploration missions this percentage needs to be greatly increased. A spacecraft cabin trace contaminant and particulate control system serves to keep the environment below the spacecraft maximum allowable concentration (SMAC) for chemicals and particulates. Both passive (filters) and active (scrubbers) methods contribute to the overall TC & PC design. Work in the area of trace contamination and particulate control under the LSS project is focused on making improvements to the SOA TC & PC systems on ISS to improve performance and reduce consumables. Wastewater Processing and Water Management- A major goal of the LSS project is the development of water recovery systems to support long duration human exploration beyond LEO. Current space station wastewater processing and water management systems distill urine and wastewater to recover water from urine and humidity condensate in the spacecraft at a approximately 74% recovery rate. For longer, farther missions into deep space, that recovery rate must be greatly increased so that astronauts can journey for months without resupply cargo ships from Earth.

Shull, Sarah A.↗

The Use of Returned Martian Samples to Evaluate the Possibility of Extant Life on Mars

The formal life-related objective of the M-2020 sample-collecting rover is to seek the signs of ancient life. The rover will not enter ''special regions'' on Mars where Earth life may replicate or extant Martian life forms are likely to exist. Therefore, returned samples will not specifically be chosen for the purpose of discovering extant life unless something unexpected is encountered in the field. Regardless, the astrobiological community is highly interested investigating whether or not there is extant life in/on these samples.

Source record↗

Future of the Search for Life: Workshop Report

The 2-week, virtual Future of the Search for Life science and engineering workshop brought together more than 100 scientists, engineers, and technologists in March and April 2022 to provide their expert opinion on the interconnections between life-detection science and technology. Participants identified the advances in measurement and sampling technologies they believed to be necessary to perform in situ searches for life elsewhere in our Solar System, 20 years or more in the future. Among suggested measurements for these searches, those pertaining to three potential indicators of life termed “dynamic disequilibrium,” “catalysis,” and “informational polymers” were identified as particularly promising avenues for further exploration. For these three indicators, small breakout groups of participants identified measurement needs and knowledge gaps, along with corresponding constraints on sample handling (acquisition and processing) approaches for a variety of environments on Enceladus, Europa, Mars, and Titan. Despite the diversity of these environments, sample processing approaches all tend to be more complex than those that have been implemented on missions or envisioned for mission concepts to date. The approaches considered by workshop breakout groups progress from nondestructive to destructive measurement techniques, and most involve the need for fluid (especially liquid) sample processing. Sample processing needs were identified as technology gaps. These gaps include technology and associated sampling strategies that allow the preservation of the thermal, mechanical, and chemical integrity of the samples upon acquisition; and to optimize the sample information obtained by operating suites of instruments on common samples. Crucially, the interplay between science-driven life-detection strategies and their technological implementation highlights the need for an unprecedented level of payload integration and extensive collaboration between scientists and engineers, starting from concept formulation through mission deployment of life-detection instruments and sample processing systems.

Marc Neveu↗

Bioregenerative life support: not a picnic

If humans are to live permanently in space, regenerative life support systems are an enabling technology and must replace the picnic approach of taking all supplies required for each mission. These systems are classified by technologies as either physical/chemical or bioregenerative. Both of these system-types can recycle water, remove carbon dioxide, produce oxygen, and recover essential elements from waste products. Bioregenerative can also produce food, thus, making it essential if humans are to exist in space independent of earth. A solely bioregenerative life support system includes plants as a biomass production module and microbial organisms in bioreactors as a resource recovery module. In the Advanced Life Support Program, bioregenerative life support systems are being investigated through a research and technology development project which includes large scale testing as part of the Breadboard Project and human tests conducted in the soon to be constructed BioPlex facility. Research and technology development efforts are directed toward optimizing biomass productivity in controlled chambers by developing light weight, energy efficient, and automated systems; recycling liquid and solid wastes; baselining the operation of bioreactors; determining system microbial stability; assessing chemical contamination; and building models required for long term system operations. The program will include space flight studies in the near future to determine if these life support technologies will function in microgravity. When a bioregenerative system is finally incorporated into a mission, the conversion from a picnic and resupply mentality to permanent recycling and independence from earth will be complete.

NASA Center KSC↗

An Accelerated Life Testing Dataset for Lithium-Ion Batteries With Constant and Variable Loading Conditions

The dataset repository is organized into three main folders, each containing one group of life cycled battery packs. Within each folder individual battery packs own their dedicated csv file for continuous data logging, which are named with their respective battery pack number. The folders are named: - regular_alt_batteries: Containing one csv file for each battery pack cycled at the same load level or load range throughout lifetime - recommissioned_batteries: Containing one csv file for each battery pack cycled at different load levels at varying life stages - second_life_batteries: Containing one csv file for each second life battery pack cycled at constant current througout the second life

Li-ion Battery↗

Don't Trust a Management Metric, Especially in Life Support

Goodhart's law states that metrics do not work. Metrics become distorted when used and they deflect effort away from more important goals. These well-known and unavoidable problems occurred when the closure and system mass metrics were used to manage life support research. The intent of life support research should be to develop flyable, operable, reliable systems, not merely to increase life support system closure or to reduce its total mass. It would be better to design life support systems to meet the anticipated mission requirements and user needs. Substituting the metrics of closure and total mass for these goals seems to have led life support research to solve the wrong problems.

life support↗

The Icebreaker Mission to Search for Life on Mars

The search for evidence of life on Mars is the ultimate motivation for its scientific exploration. The results from the Phoenix mission indicate that the high N. latitude ice-rich regolith at low elevations is likely to be a recently habitable place on Mars [Stoker et al., 2010]. The near-surface ice likely provided adequate water activity during periods of high obliquity, 3 to 10 Myr ago. Carbon dioxide and nitrogen are present in the atmosphere, and nitrates may be present in the soil. Together with iron in basaltic rocks and perchlorate in the soil they provide carbon and energy sources, and oxidative power to drive metabolism. Furthermore, the presence of organics is possible, as thermally reactive perchlorate would have prevented their detection by Viking and Phoenix. The Mars Icebreaker Life mission [McKay et al., 2013] focuses on the following science goals: (1) Search for biomolecular evidence of life; (2) Search for organic matter from either exogeneous or endogeneous sources using methods that are not effected by the presence of perchlorate; (3) Characterize oxidative species that produced reactivity of soils seen by Viking; and 4) Assess the habitability of the ice bearing soils. The Icebreaker Life payload (Figure 1) includes a 1-m rotary percussive drill that brings cuttings samples to the surface where they are delivered to three instruments (Fig. 1), the Signs of Life Detector (SOLID) [Parro et al., 2011] for biomolecular analysis, Laser Desorption Mass Spectrometer (LDMS) [??? 2015]) for broad spectrum organic analysis, and Wet Chemistry Laboratory (WCL) [Hecht et al., 2009] for detecting soluble species of nutrients and reactive oxidants. The Icebreaker payload fits on the Phoenix spacecraft and can land at the well-characterized Phoe-nix landing site in 2020 in a Discovery-class mission.

Carbon dioxide and nitrogen↗

The Search for Life in the Universe

Each recent report of liquid water existing elsewhere in the solar system has reverberated through the international press and excited the imagination of humankind. We have come to realize that where there is liquid water on Earth, virtually no matter what the physical conditions, there is life. Dr. Lynn Rothschild, an evolutionary biologist known for her work on life in extreme environments and a founder of the field of astrobiology, tells us about intriguing new data. The prevalence of potential abodes for life in our solar system and beyond, the survival of microbes in the space environment, modeling of the potential for transfer of life between celestial bodies, and advances in synthetic biology suggest that life could be more common than previously thought. Are we truly "alone"?

Life in the Universe↗

Algorithmic Classification of Raman Spectra Biosignatures: Improving Life Detection Confidence

“Agnostic” biosignatures – indicators of life (or the absence of life), independent of a particular biochemistry – are increasingly considered a high standard for life detection. The Ladder of Life Detection (2018) called for investigating how combinations of independent and different potential biosignatures affect confidence. To address this gap, statistical classification of elemental abundances, isotopic fractionation, and reflectance spectroscopy (VNIR) has been implemented. Raman spectroscopy, highly desirable due to its wide availability, has the potential to improve this predictive power. This work implemented biosignature classification algorithms on Raman data alone, in preparation for combination with the other data types. Raman spectroscopy data was collected from published databases and papers as part of a manually curated dataset of “indicative” and “non-indicative of life” samples. These currently include 61 non-indicative samples (meteorites, magnetite); 3 indicative living samples (bacteria); 20 indicative non-living samples (chalk, bone); and 12 indicative mixed (with non-indicative material) samples (soil, microbial mats). Laboratory work is ongoing to characterize additional samples, particularly a greater breadth of mixed systems. Spectra were interpolated, filtered with the Savitzsky-Golay filter, and de-noised. For a preliminary examination, agnostic features were manually extracted including mean intensity, number of peaks, and mean peak width. Different peak prominences and filtering polynomials were used to refine features. Classification algorithms were implemented: k-nearest neighbors (KNN), logistic regression (LR), linear support vector machines (SVM), random forest (RF), Gaussian naïve bayes (GNB). Lastly, Monte Carlo simulations on 1,000 50%-train-test-splits were used to validate classification performance and feature significance. The preliminary feature set achieved its highest AUC of 0.52 with LR, with no strongly discriminatory features. Work to improve feature extraction, such as through deep learning with back propagation, is planned. In future work, the Raman data will be combined with the other data types, and potentially new data types such as enantiomeric excess. This project was partially supported through the NASA Ames Project EXcellence (APEX) incubator program.

Astrobiology↗

Microbial Life in Space

Outer space is a harsh environment harbouring multiple forms of stress like cosmic radiation, space vacuum, extreme temperature and pressure, UV radiations, and altered gravity. Earth’s atmosphere has several layers that expose microbial and terrestrial life to harsh external environments. In order to study the limits of survival of microbial life in extremes, it is imperative to study the response of micro-organisms to space-related stress. The present chapter summarizes the various balloon and flight experiments performed to investigate the presence and response of microbial life in space. Studying the microbiome in the ISS is important as pathogenic bacteria can present a major risk to astronaut health in a closed environment. Hence, studying occurrence, ecology, diversity, response, and adaptations of microbial life in space is crucial to understanding the limits of organismic survival in inhospitable conditions. Studying microbial life in space also helps predict the plausible survival and endurance of microbial travel between planets, crucial to lithopanspermia theories and planetary protection.

space↗

NASA's Advanced Life Support Systems Human-Rated Test Facility

Future NASA missions to explore the solar system will be long-duration missions, requiring human life support systems which must operate with very high reliability over long periods of time. Such systems must be highly regenerative, requiring minimum resupply, to enable the crews to be largely self-sufficient. These regenerative life support systems will use a combination of higher plants, microorganisms, and physicochemical processes to recycle air and water, produce food, and process wastes. A key step in the development of these systems is establishment of a human-rated test facility specifically tailored to evaluation of closed, regenerative life supports systems--one in which long-duration, large-scale testing involving human test crews can be performed. Construction of such a facility, the Advanced Life Support Program's (ALS) Human-Rated Test Facility (HRTF), has begun at NASA's Johnson Space Center, and definition of systems and development of initial outfitting concepts for the facility are underway. This paper will provide an overview of the HRTF project plan, an explanation of baseline configurations, and descriptive illustrations of facility outfitting concepts.

NASA Discipline Number 61-10↗

Johnson Space Center's Regenerative Life Support Systems Test Bed

The Regenerative Life Support Systems (RLSS) Test Bed at NASA's Johnson Space Center is an atmospherically closed, controlled environment facility for human testing of regenerative life support systems using higher plants in conjunction with physicochemical life support systems. The facility supports NASA's Advanced Life Support (ALS) Program. The facility is comprised of two large scale plant growth chambers, each with approximately 11 m2 growing area. The root zone in each chamber is configurable for hydroponic or solid media plant culture systems. One of the two chambers, the Variable Pressure Growth Chamber (VPGC), is capable of operating at lower atmospheric pressures to evaluate a range of environments that may be used in a planetary surface habitat; the other chamber, the Ambient Pressure Growth Chamber (APGC) operates at ambient atmospheric pressure. The air lock of the VPGC is currently being outfitted for short duration (1 to 15 day) human habitation at ambient pressures. Testing with and without human subjects will focus on 1) integration of biological and physicochemical air and water revitalization systems; 2) effect of atmospheric pressure on system performance; 3) planetary resource utilization for ALS systems, in which solid substrates (simulated planetary soils or manufactured soils) are used in selected crop growth studies; 4) environmental microbiology and toxicology; 5) monitoring and control strategies; and 6) plant growth systems design. Included are descriptions of the overall design of the test facility, including discussions of the atmospheric conditioning, thermal control, lighting, and nutrient delivery systems.

NASA Discipline Number 61-10↗

Evaluation of methods for determining hardware projected life

An investigation of existing methods of predicting hardware life is summarized by reviewing programs having long life requirements, current research efforts on long life problems, and technical papers reporting work on life predicting techniques. The results indicate that there are no accurate quantitative means to predict hardware life for system level hardware. The effectiveness of test programs and the cause of hardware failures is considered.

Source record↗

Generation of Finite Life Distributional Goodman Diagrams for Reliability Prediction

The methodology of developing finite life distributional Goodman diagrams and surfaces is described for presenting allowable combinations of alternating stress and mean stress to the design engineer. The combined stress condition is that of an alternating bending stress and a constant shear stress. The finite life Goodman diagrams and surfaces are created from strength distributions developed at various ratios of alternating to mean stress at particular cycle life values. The conclusions indicate that the Von Mises-Hencky ellipse, for cycle life values above 1000 cycles, is an adequate model of the finite life Goodman diagram. In addition, suggestions are made which reduce the number of experimental data points required in a fatigue data acquisition program.

Kececioglu, D.↗