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At least 1,045 records · Page 58

Evolving Reliability and Maintainability Allocations for NASA Ground Systems

This paper describes the methodology and value of modifying allocations to reliability and maintainability requirements for the NASA Ground Systems Development and Operations (GSDO) programs subsystems. As systems progressed through their design life cycle and hardware data became available, it became necessary to reexamine the previously derived allocations. This iterative process provided an opportunity for the reliability engineering team to reevaluate allocations as systems moved beyond their conceptual and preliminary design phases. These new allocations are based on updated designs and maintainability characteristics of the components. It was found that trade-offs in reliability and maintainability were essential to ensuring the integrity of the reliability and maintainability analysis. This paper discusses the results of reliability and maintainability reallocations made for the GSDO subsystems as the program nears the end of its design phase.

reliability↗

A Comparative Study of Some Dynamic Stall Models

Three semi-empirical aerodynamic stall models are compared with respect to their lift and moment hysteresis loop prediction, limit cycle behavior, easy implementation, and feasibility in developing the parameters required for stall flutter prediction of advanced turbines. For the comparison of aeroelastic response prediction including stall, a typical section model and a plate structural model are considered. The response analysis includes both plunging and pitching motions of the blades. In model A, a correction to the angle of attack is applied when the angle of attack exceeds the static stall angle. In model B, a synthesis procedure is used for angles of attack above static stall angles and the time history effects are accounted through the Wagner function. In both models the life and moment coefficients for angle of attack below stall are obtained from tabular data for a given Mach number and angle of attack. In model C, referred to an the ONERA model, the life and moment coefficients are given in the form of two differential equations, one for angles below stall, and the other for angles above stall. The parameters of those equations are nonlinear functions of the angle of attack.

Reddy, T. S. R.↗

A modified ATI technique for nowcasting convective rain volumes over areas

This paper explores the applicability of the area-time-integral (ATI) technique for the estimation of the growth portion only of a convective storm (while the rain volume is computed using the entire life history of the event) and for nowcasting the total rain volume of a convective system at the stage of its maximum development. For these purposes, the ATIs were computed from the digital radar data (for 1981-1982) from the North Dakota Cloud Modification Project, using the maximum echo area (ATIA) no less than 25 dBz, the maximum reflectivity, and the maximum echo height as the end of the growth portion of the convective event. Linear regression analysis demonstrated that correlations between total rain volume or the maximum rain volume versus ATIA were the strongest. The uncertainties obtained were comparable to the uncertainties which typically occur in rain volume estimates obtained from radar data employing Z-R conversion followed by space and time integration. This demonstrates that the total rain volume of a storm can be nowcasted at its maximum stage of development.

Makarau, Amos↗

Lower bound on reliability for Weibull distribution when shape parameter is not estimated accurately

The mathematical relationships between the shape parameter Beta and estimates of reliability and a life limit lower bound for the two parameter Weibull distribution are investigated. It is shown that under rather general conditions, both the reliability lower bound and the allowable life limit lower bound (often called a tolerance limit) have unique global minimums over a range of Beta. Hence lower bound solutions can be obtained without assuming or estimating Beta. The existence and uniqueness of these lower bounds are proven. Some real data examples are given to show how these lower bounds can be easily established and to demonstrate their practicality. The method developed here has proven to be extremely useful when using the Weibull distribution in analysis of no-failure or few-failures data. The results are applicable not only in the aerospace industry but anywhere that system reliabilities are high.

Huang, Zhaofeng↗

Lower bound on reliability for Weibull distribution when shape parameter is not estimated accurately

The mathematical relationships between the shape parameter Beta and estimates of reliability and a life limit lower bound for the two parameter Weibull distribution are investigated. It is shown that under rather general conditions, both the reliability lower bound and the allowable life limit lower bound (often called a tolerance limit) have unique global minimums over a range of Beta. Hence lower bound solutions can be obtained without assuming or estimating Beta. The existence and uniqueness of these lower bounds are proven. Some real data examples are given to show how these lower bounds can be easily established and to demonstrate their practicality. The method developed here has proven to be extremely useful when using the Weibull distribution in analysis of no-failure or few-failures data. The results are applicable not only in the aerospace industry but anywhere that system reliabilities are high.

Huang, Zhaofeng↗

SERFE Ground Unit EVA Series After Three Year Spacesuit Stowage Period

NASA’s spacesuit government reference design for returning to the Moon is called the Exploration Extravehicular Mobility Unit (xEMU). The xEMU subassembly that provides life support, such as oxygen and thermal control, is the Portable Life Support System (PLSS). Inside the PLSS is a new technology that NASA wanted to test to provide cooling to the crew during EVAs (ExtraVehicular Activity). This technology is called the Spacesuit Water Membrane Evaporator (SWME). In order to test SWME in an improved thermal control loop (TCL) both on Earth and in Space, the Spacesuit Evaporation Rejection Flight Experiment (SERFE) was created. The Ground unit, or testbed at Johnson Space Center (JSC), tested the cooling technology in Earth’s gravity, while the Flight unit, or payload on the International Space Station (ISS), tested the cooling technology in micro-gravity. Since fluids flow differently in micro-gravity, testing in both environments would provide important data for improving cooling performance during EVAs. Both units completed 25 simulated EVAs with the same settings so SWME performance on the ground could be compared to the ISS. The Flight unit was completed first and performed EVAs on the ISS between 2020 and 2022. The Ground unit performed EVAs between 2021 and 2022. When the Flight unit came back from the ISS, it was taken apart for analysis. This analysis looked at how well SWME was able to maintain its heat rejection capability after various dwell times, such as a 90 day Airlock Coolant Loop Recovery (ALCLR) cycle, when the Extravehicular Mobility Unit (EMU) currently on the ISS would normally need maintenance. After a three year simulated spacesuit dwell, the Ground unit performed another EVA series in 2025 to test SWME’s shelf life. The results from this test series will inform mission planning as NASA plans to go back to the Moon and beyond.

Michael Lewandowski↗

SERFE Ground Unit EVA Series After Three Year Spacesuit Stowage Period

NASA’s spacesuit government reference design for returning to the Moon is called the Exploration Extravehicular Mobility Unit (xEMU). The xEMU subassembly that provides life support, such as oxygen and thermal control, is the Portable Life Support System (PLSS). Inside the PLSS is a new technology that NASA wanted to test to provide cooling to the crew during EVAs (ExtraVehicular Activity). This technology is called the Spacesuit Water Membrane Evaporator (SWME). In order to test SWME in an improved thermal control loop (TCL) both on Earth and in Space, the Spacesuit Evaporation Rejection Flight Experiment (SERFE) was created. The Ground unit, or testbed at Johnson Space Center (JSC), tested the cooling technology in Earth’s gravity, while the Flight unit, or payload on the International Space Station (ISS), tested the cooling technology in micro-gravity. Since fluids flow differently in micro-gravity, testing in both environments would provide important data for improving cooling performance during EVAs. Both units completed 25 simulated EVAs with the same settings so SWME performance on the ground could be compared to the ISS. The Flight unit was completed first and performed EVAs on the ISS between 2020 and 2022. The Ground unit performed EVAs between 2021 and 2022. When the Flight unit came back from the ISS, it was taken apart for analysis. This analysis looked at how well SWME was able to maintain its heat rejection capability after various dwell times, such as a 90 day Airlock Coolant Loop Recovery (ALCLR) cycle, when the Extravehicular Mobility Unit (EMU) currently on the ISS would normally need maintenance. After a three year simulated spacesuit dwell, the Ground unit performed another EVA series in 2025 to test SWME’s shelf life. The results from this test series will inform mission planning as NASA plans to go back to the Moon and beyond.

SWME↗

The Neurodata Without Borders ecosystem for neurophysiological data science

The neurophysiology of cells and tissues are monitored electrophysiologically and optically in diverse experiments and species, ranging from flies to humans. Understanding the brain requires integration of data across this diversity, and thus these data must be findable, accessible, interoperable, and reusable (FAIR). This requires a standard language for data and metadata that can coevolve with neuroscience. We describe design and implementation principles for a language for neurophysiology data. Our open-source software (Neurodata Without Borders, NWB) defines and modularizes the interdependent, yet separable, components of a data language. We demonstrate NWB’s impact through unified description of neurophysiology data across diverse modalities and species. NWB exists in an ecosystem, which includes data management, analysis, visualization, and archive tools. Thus, the NWB data language enables reproduction, interchange, and reuse of diverse neurophysiology data. More broadly, the design principles of NWB are generally applicable to enhance discovery across biology through data FAIRness.

59 BASIC BIOLOGICAL SCIENCES↗

Voltage and temperature effects on low cobalt lithium-ion battery cathode degradation

Degradation of low cobalt lithium-ion cathodes was tested using a full factorial combination of upper cut-off voltage (4.0 V and 4.3 V vs. Li/Li + ) and operating temperature (25 °C and 60 °C). Half-cell batteries were analyzed with electrochemical and microstructural characterization methods. Electrochemical performance was assessed with galvanostatic cycling, cyclic voltammetry (CV), and electrochemical impedance spectroscopy (EIS) supported by distribution of relaxation times (DRT) analysis. Electrode microstructure was characterized with scanning electron microscopy (SEM), X-ray diffraction (XRD), and X-ray absorption near edge structure (XANES) imaging. Higher cut-off voltage cycling shows presence of NiO x formation, a low diffusivity rock-salt phase, in both CV and XRD data. XRD patterns confirmed that the rock-salt phase was beginning to form at the low cut-off voltage at high temperature, but in much lower intensity than at the high cut-off voltage. Higher temperature accelerates degradation processes at both voltages. Degradation factors at high temperature include NiO x formation, cathode material dissolution, and electrolyte decomposition. SEM analysis suggests that supporting phases may isolate and disconnect active material particles reducing capacity retention and battery life cycle. DRT analysis and XANES imaging show that both high temperature samples revealed a NiO x phase based on an increased diffusive impedance and a visible shift in the XANES spectra. The low cut-off voltage, high temperature sample showed a split peak and shift to lower energies indicating early formation of the NiO x phase. The diffusive impedance, which hinders intercalation and deintercalation, is driven by the formation of the NiO x phase. While primarily driven by cut-off voltage, elevated temperature also contributes to this degradation mechanism.

electrochemical impedance spectroscopy↗

JT9D-7A /SP/ jet engine performance deterioration trends

It is noted that increasing fuel costs and the decreasing availability of fuel supplies have lead to an increase in the importance of maintaining good specific fuel consumption over the life cycle of jet engines. Attention is given to an engine diagnostics program sponsored by NASA Lewis Research Center which has the objectives of identifying and quantifying the levels, trends, and causes of engine performance deterioration. It is reported that as part of the program, a series of installed engine calibrations were performed on two new Pan American World Airways 747 SP aircraft. A discussion of this specific test program and the results of the analysis of the data are presented.

Richter, G. P.↗

The Einstein observatory stellar X-ray database - An overview

The paper presents the motivations for and the methodology followed in building the 'Einstein Observatory Stellar X-ray Database' based on the uniform analysis of all Einstein Observatory Imaging Proportional Counter fields obtained during the life of the HEAO-2 mission. The database has been implemented using the INGRES database system, so that statistical analyses of the properties of the full detection catalog are relatively easily and flexibly accomplished. Some illustrative examples will furnish a general view both of the kind and the amount of the archived information, and of the statistical approach used in analyzing the global properties of the data.

Sciortino, S.↗

Development of the Architectural Simulation Model for Future Launch Systems and its Application to an Existing Launch Fleet

A significant portion of lifecycle costs for launch vehicles are generated during the operations phase. Research indicates that operations costs can account for a large percentage of the total life-cycle costs of reusable space transportation systems. These costs are largely determined by decisions made early during conceptual design. Therefore, operational considerations are an important part of vehicle design and concept analysis process that needs to be modeled and studied early in the design phase. However, this is a difficult and challenging task due to uncertainties of operations definitions, the dynamic and combinatorial nature of the processes, and lack of analytical models and the scarcity of historical data during the conceptual design phase. Ultimately, NASA would like to know the best mix of launch vehicle concepts that would meet the missions launch dates at the minimum cost. To answer this question, we first need to develop a model to estimate the total cost, including the operational cost, to accomplish this set of missions. In this project, we have developed and implemented a discrete-event simulation model using ARENA (a simulation modeling environment) to determine this cost assessment. Discrete-event simulation is widely used in modeling complex systems, including transportation systems, due to its flexibility, and ability to capture the dynamics of the system. The simulation model accepts manifest inputs including the set of missions that need to be accomplished over a period of time, the clients (e.g., NASA or DoD) who wish to transport the payload to space, the payload weights, and their destinations (e.g., International Space Station, LEO, or GEO). A user of the simulation model can define an architecture of reusable or expendable launch vehicles to achieve these missions. Launch vehicles may belong to different families where each family may have it own set of resources, processing times, and cost factors. The goal is to capture the required resource levels of the major launch elements and their required facilities. The model s output can show whether or not a certain architecture of vehicles can meet the launch dates, and if not, how much the delay cost would be. It will also produce aggregate figures of missions cost based on element procurement cost, processing cost, cargo integration cost, delay cost, and mission support cost. One of the most useful features of this model is that it is stochastic where it accepts statistical distributions to represent the processing times mimicking the stochastic nature of real systems.

Rabadi, Ghaith↗

AIRS Impact on the Analysis and Forecast Track of Tropical Cyclone Nargis in a Global Data Assimilation and Forecasting System

Tropical cyclones in the northern Indian Ocean pose serious challenges to operational weather forecasting systems, partly due to their shorter lifespan and more erratic track, compared to those in the Atlantic and the Pacific. Moreover, the automated analyses of cyclones over the northern Indian Ocean, produced by operational global data assimilation systems (DASs), are generally of inferior quality than in other basins. In this work it is shown that the assimilation of Atmospheric Infrared Sounder (AIRS) temperature retrievals under partial cloudy conditions can significantly impact the representation of the cyclone Nargis (which caused devastating loss of life in Myanmar in May 2008) in a global DAS. Forecasts produced from these improved analyses by a global model produce substantially smaller track errors. The impact of the assimilation of clear-sky radiances on the same DAS and forecasting system is positive, but smaller than the one obtained by ingestion of AIRS retrievals, possibly due to poorer coverage.

Reale, O.↗

Predictive Modeling and Uncertainty Quantification in Condition Monitoring of Active Components: A Reactor Coolant Pump Use Case

This work develops data-driven models for onset of thermal barrier leakage in reactor coolant pumps. It incorporates uncertainty quantification to enhance the reliability and robustness of pre- dictions. Using synthetic data generated by the Generic Pressurized Water Reactor simulator, realistic degradation scenarios were simulated across lifecycle stages—beginning, middle, and end of life. Key variables, including differential pressure, flow rate, vibration, and temperatures, were analyzed using machine learning framework. The fully connected neural network models demonstrated exceptional performance, achieving R2 scores exceeding 0.99 and root mean square errors as low as around 8.23 × 10-2 gallon per minute (gpm) for the three stages of the lifecy- cle. UQ analysis further validated the model’s robustness, with narrow uncertainty bounds during steady-state operations and appropriately wider bounds during transitional phases, reflecting the physical behavior of the system. This work addresses important gaps in real-time condition moni- toring and regulatory compliance by integrating advanced condition monitoring technologies with UQ into IST programs. The ability to detect thermal barrier leakage early and quantify prediction reliability supports optimizing maintenance strategies while ensuring nuclear power plants’ safe and reliable operation.

99 - GENERAL AND MISCELLANEOUS↗

Expanding Repository Data Available For Sharing And Knowledge Discovery

Some of the hardest space biology and space health challenges require data-intensive, bioinformatic, meta-analytical, and computer-assisted research approaches. These challenges include examining interdisciplinary space life science research across experiments and across interacting spaceflight hazards (radiation, altered gravity, confinement, hostile-closed environments, distance-duration from Earth). The approaches to confront these challenges involve mining multiple datasets simultaneously from various hierarchical organizations of biological complexity, all while concurrently evaluating how experimental design factors affect endpoints of standard assays. To enable this field, it is essential that principal investigators (PIs) submit data in a structure so it can be maximally re-used. The purpose of the NASA Ames Life Sciences Data Archive (ALSDA) is to collect, curate, and make publicly available all non-human space-relevant biological data. ALSDA must also ensure data are open-access, and maximally findable, accessible, interoperable, and reusable (FAIR). The scope of ALSDA data collected and submitted by PIs include subject and study design metadata, assay metadata parameters, raw and processed assay data, assay imagery/video, and subject-experienced mission data telemetry (radiation, temperature, humidity, acoustics, vibrations, etc.). ALSDA recently integrated into a collaborative group of Open Science projects to facilitate a suite of new tools and workflows that will improve data submission, accessibility, and reusability by implementing digital data submission agreements, and adopting the data management system originally developed by NASA GeneLab. ALSDA intends to bring current biological repository data and all future collected data into this new scientific data reuse reality. This new suite of tools will enable ALSDA to deploy a science curation system using scientific assay configurations for the data submission portal. It will capture essential assay parameters according to established standards in each sub-field within biology. The submission portal expedites data collection by enhancing ease of PI data submission, providing a user interface and specificity for which data is to be submitted. Data submissions can be brought into cutting-edge informatic analysis portals to enable mining of physiological, behavioral, biochemical, and imaging datasets in conjunction with ‘omics-level datasets. As ALSDA datasets are submitted, curated, and published (e.g., micro-computed tomography, histology, pulse oximetry, serum metabolites, magnetic resonance imaging, intraocular pressure, novel object recognition, etc.), the merging together of spaceflight data along this multi-hierarchical complexity of biology will enable informatics and data-intensive approaches resulting in knowledge discoveries across missions, space hazards, and biological disciplines.

life science↗

Intrinsically stretchable neuromorphic devices for on-body processing of health data with artificial intelligence

For leveraging wearable technologies to advance precision medicine, personalized and learning-based analysis of continuously acquired health data is indispensable, for which neuromorphic computing could provide the most efficient implementation of artificial intelligence (AI) data processing. For realizing on-body neuromorphic computing, skin-like stretchability is required, but yet to be combined with the suite of desired neuromorphic metrics, including linear, symmetric weight update, and sufficient state retention, for achieving high computing efficiency. Here, we report an intrinsically stretchable neuromorphic device based on an electrochemical transistor, which provides a large number (>800) of states, linear/symmetric weight update, excellent switching endurance (>100 million), good state retention (>10 4 s), together with high stretchability of 100% strain. Further integration into a prototype array successfully realized the implementation of vector-matrix multiplication even at 100% strain. Finally, we demonstrate the feasibility of implementing AI-based classification of health signals (as exemplified by electrocardiograms) with a high accuracy that is minimally influenced by the stretched state of the neuromorphic hardware. Finally, this work breaks the ground for combining AI data analysis into skin-like wearable electronics for achieving human-integrated/mimetic intelligent systems.

60 APPLIED LIFE SCIENCES↗

What Should Health Departments Do with HIV Sequence Data?

Many countries and US states have mandatory statues that require reporting of HIV clinical data including genetic sequencing results to the public health departments. Because genetic sequencing is a part of routine care for HIV infected persons, health departments have extensive sequence collections spanning years and even decades of the HIV epidemic. How should these data be used (or not) in public health practice? This is a complex, multi-faceted question that weighs personal risks against public health benefit. The answer is neither straightforward nor universal. However, to make that judgement—of how genetic sequence data should be used in describing and combating the HIV epidemic—we need a clear image of what a phylogenetically enhanced HIV surveillance system can do and what benefit it might provide. In this paper, we present a positive case for how up-to-date analysis of HIV sequence databases managed by health departments can provide unique and actionable information of how HIV is spreading in local communities. We discuss this question broadly, with examples from the US, as it is globally relevant for all health authorities that collect HIV genetic data.

60 APPLIED LIFE SCIENCES↗

Sensory characterization of a ready-to-eat sweetpotato breakfast cereal by descriptive analysis

The sweetpotato [Ipomoea batatas (L.) Lam], an important industry in the United States, has been selected as a candidate crop to be grown on future long-duration space missions by NASA. Raw sweetpotato roots were processed into flour, which was used to formulate ready-to-eat breakfast cereal (RTEBC). Twelve trained panelists evaluated the sensory attributes of the extruded RTEBC using descriptive analysis. The samples were significantly different (P<0.05) for all attributes. Twelve perceived sensory attributes, which could be used to differentiate the appearance, texture, and flavor of sweetpotato RTEBC, were described. The data could be used to optimize the RTEBC and for designing studies to test its consumer acceptance.

NASA Discipline Life Support Systems↗