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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 361 records · Page 20

Progressive Damage Analysis of Laminated Composite (PDALC)-A Computational Model Implemented in the NASA COMET Finite Element Code

A method for analysis of progressive failure in the Computational Structural Mechanics Testbed is presented in this report. The relationship employed in this analysis describes the matrix crack damage and fiber fracture via kinematics-based volume-averaged variables. Damage accumulation during monotonic and cyclic loads is predicted by damage evolution laws for tensile load conditions. The implementation of this damage model required the development of two testbed processors. While this report concentrates on the theory and usage of these processors, a complete list of all testbed processors and inputs that are required for this analysis are included. Sample calculations for laminates subjected to monotonic and cyclic loads were performed to illustrate the damage accumulation, stress redistribution, and changes to the global response that occur during the load history. Residual strength predictions made with this information compared favorably with experimental measurements.

Lo, David C.↗

Progressive Damage Analysis of Laminated Composite (PDALC) (A Computational Model Implemented in the NASA COMET Finite Element Code)

A method for analysis of progressive failure in the Computational Structural Mechanics Testbed is presented in this report. The relationship employed in this analysis describes the matrix crack damage and fiber fracture via kinematics-based volume-averaged damage variables. Damage accumulation during monotonic and cyclic loads is predicted by damage evolution laws for tensile load conditions. The implementation of this damage model required the development of two testbed processors. While this report concentrates on the theory and usage of these processors, a complete listing of all testbed processors and inputs that are required for this analysis are included. Sample calculations for laminates subjected to monotonic and cyclic loads were performed to illustrate the damage accumulation, stress redistribution, and changes to the global response that occurs during the loading history. Residual strength predictions made with this information compared favorably with experimental measurements.

Coats, Timothy W.↗

Steering Aircraft Clear of Choppy Air

AeroTech Research (U.S.A.), Inc., a leader in turbulence-detection and warning systems, has been involved with NASA Aviation Safety research since 1998. AeroTech served as a contractor for the TPAWS government/industry development project, and was funded by NASA to develop the E-Turb Mode Radar algorithms and the TAPS software. (Other contributors to this project include the National Center for Atmospheric Research, the FAA, North Carolina State University, and the Research Triangle Institute.) The radar algorithms combine an aircraft's turbulenceresponse characteristics with radar measurements to determine the predicted turbulence loads the aircraft will experience, and present this information to the pilot. The TAPS software monitors and processes onboard aircraft sensor data; generates automatic reports when an aircraft encounters turbulence and a set turbulence threshold is exceeded; and then displays the reports and underlying information to ground personnel to improve situational awareness of the location and the severity of the turbulence encounter.

Source record↗

Mission Information and Test Systems Summary of Accomplishments, 2011

This annual report covers the activities of the NASA DRFC Mission Information and Test Systems, which includes the Western Aeronautical Test Range, the Simulation Engineering Branch, the Information Services and the Dryden Technical Laboratory (Flight Loads Lab). This report contains highlights, current projects and various awards achieved during in 2011

McMorrow, Sean E.↗

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

A previous study 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 HNPs occurred well into astronauts' careers or in somecases 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. In addition, when an HNP occurs after spaceflight, is it related to previous spaceflight exposure? The purpose of this study was to investigate whether multiple missions, sex, age, vehicle landing dynamics, and flight duration affect the risk of developing an HNP usinga competing risks model. The outcome of the study will inform the Human System Risk Board assessment of back pain, inform the risk of injury due to dynamic loads, and update the previous dataset, which contained events up to December 31, 2006.

Feiveson, A.↗

Microstructure Quantification and Random Forest Regression Models for Li4Ti5O12–Ni Property Prediction

All-solid-state structural lithium-ion batteries are sought to enable all-electric propulsion in next generation aerospace concepts through improved safety and systems level weight savings. In this work, the influence of processing conditions on microstructural evolution was evaluated for anode composites of strain-free Li4Ti5O12 and metallic nickel current collector. Beyond size distributions, this study explored methods of quantifying microstructural features that describe changes in the spatial distribution and coalescence of nickel particles as a function of sample composition and sintering conditions. Processing-microstructure-property relationships were described by microstructure quantifiers including nickel particle count per area, nearest neighbor distance distribution, and edge-to-edge distance distribution. Machine learning methods were applied to compare the relative influence of processing conditions and microstructural features on electrical conductivity and mechanical strength to optimize for simultaneous energy storage and load bearing performance. Insights gained from this work inform future evaluation of alternative energy storage materials and microstructures for multifunctional performance, and generation of microstructural descriptors strengthens modeling across length scales.

anode↗

Overview of Light Weight Radioisotope Heater Unit (LWRHU) User’s Guide

Idaho National Laboratory (INL) has recently compiled a user’s guide for the Light Weight Radioisotope Heater Unit (LWRHU). This guide gives an overview of the LWRHU to potential users. Information and data on mass properties, dimensions, thermal loads, and interfaces are discussed.

07 ISOTOPE AND RADIATION SOURCES↗

Overview of Light Weight Radioisotope Heating Unit (LWRHU) User’s Guide

Idaho National Laboratory (INL) has recently compiled a user’s guide for the LightWeight Radioisotope Heating Unit (LWRHU). This guide gives an overview of the LWRHU to potential users. Information and data on mass properties, dimensions, thermal loads, and interfaces are discussed.

42 ENGINEERING↗

Measurement of Oil-Film Pressures in Journal Bearings under Constant and Variable Loads

In a study of journal bearings, the measurement of the oil-film strength produces some significant information. A new instrument is described by means of which the pressure of the oil film in bearings (under constant or alternating load) can be measured and recorded. With this device, the pressure distribution in the lubricating film of a bearing bushing was measured (under different operating conditions on a journal bearing) in the pulsator-bearing-testing machine. These tests are described and discussed in the present report.

Buske, A.↗

Mechanism-Informed Breakdown: Understanding Degradation by Controlling Voltage-Hold Patterns in Proton Exchange Membrane Water Electrolyzers

Low catalyst loadings pose challenges to performance stability in proton exchange membrane (PEM) water electrolysis over extended operation. To study the impact of degradation mechanisms and voltage loss rates, different stress tests are applied to membrane electrode assemblies. Potential cycling conditions were observed to induce higher degrees of iridium (Ir) oxide crystallization, ionomer degradation, and catalyst layer (CL) thinning, which likely contributed to higher kinetic loss rates. On the other hand, while Ir migrating into the PEM (Ir band) generally impairs performance, the interconnected and more uniform Ir band formed under a constant 2 V hold may allow for Ir at the catalyst/membrane interface to remain electronically connected and kinetically accessible, as well as indicate greater Ir site access during the applied stressor. The 2 V hold also demonstrates improved kinetic durability through a lower Tafel slope, faster polarization kinetics, and reduced charge transfer resistance. In contrast, potential cycling caused the migration of disconnected Ir agglomerates into the membrane bulk and created a steady increase in charge transfer resistance, a more dramatic decrease in capacitance (46.7% loss), and significant damage to the surrounding ionomer, indicating a decline in both the quality and quantity of active sites in the anode CL. This work underscores the distinct degradation pathways associated with load holds versus cycling, highlighting the role of catalyst-ionomer interactions in kinetic performance and long-term stability. These insights can inform operational strategies for PEM electrolyzers powered by intermittent energy sources, aiming to minimize efficiency losses over extended operation.

36 MATERIALS SCIENCE↗

Retrospective Analysis of Inflight Exercise Loading and Physiological Outcomes

Astronauts perform exercise throughout their missions to counter the health declines that occur as a result of long-term exposure to weightlessness. Although all astronauts perform exercise during their missions, the specific prescriptions, and thus the mechanical loading, differs among individuals. For example, inflight ground reaction force data indicate that subject-specific differences exist in foot forces created when exercising on the second-generation treadmill (T2) [1]. The current exercise devices allow astronauts to complete prescriptions at higher intensities, resulting in greater benefits with increased efficiency. Although physiological outcomes have improved, the specific factors related to the increased benefits are unknown. In-flight exercise hardware collect data that allows for exploratory analyses to determine if specific performance factors relate to physiological outcomes. These analyses are vital for understanding which components of exercise are most critical for optimal human health and performance. The relationship between exercise performance variables and physiological changes during flight has yet to be fully investigated. Identifying the critical performance variables that relate to improved physiological outcomes is vital for creating current and future exercise prescriptions to optimize astronaut health. The specific aims of this project are: 1) To quantify the exercise-related mechanical loading experienced by crewmembers on T2 and ARED during their mission on ISS; 2) To explore relationships between exercise loading variables, bone, and muscle health changes during the mission; 3) To determine if specific mechanical loading variables are more critical than others in protecting physiology; 4) To develop methodology for operational use in monitoring accumulated training loads during crew exercise programs. This retrospective analysis, which is currently in progress, is being conducted using data from astronauts that have flown long-duration missions onboard the ISS and have had access to exercise on the T2 and the Advanced Resistive Exercise Device (ARED). The specific exercise prescriptions vary for each astronaut. General exercise summary metrics will be developed to quantify exercise intensities, volumes, and durations for each subject. Where available, ground reaction force data will be used to quantify mechanical loading experienced by each astronaut. These inflight exercise metrics will be investigated relative to changes in pre- to post-flight bone and muscle health to identify which specific variables are related with improved or degraded physiological outcomes. The information generated from this analysis will fill gaps related to typical bone loading characterization, exercise performance capability, exercise volume and efficiency, and importance of exercise hardware. In addition, methods for quantification of exercise loading for use in monitoring the exercise programs during future space missions will be explored with the intent to inform exercise scientists and trainers as to the critical aspects of inflight exercise prescriptions.

Ploutz-Snyder, L. L.↗

Forced guidance and distribution of practice in sequential information processing.

Distribution of practice and forced guidance were used in a sequential information-processing task in an attempt to increase the capacity of human information-processing mechanisms. A reaction time index of the psychological refractory period was used as the response measure. Massing of practice lengthened response times while forced guidance shortened them. Interpretation was in terms of load reduction upon the response-selection stage of the information-processing system.-

Decker, L. R.↗

Clinical Decision Support Project

As NASA plans for exploration missions into deep space, significant challenges are realized due to the distance from Earth. Beside the effects of microgravity and radiation exposure, the astronauts face the additional constraints of isolation, lack of resupply, increasingly difficult evacuation, and delayed and disrupted communication with ground-based medical care providers. These constraints require a paradigm shift from current medical care where crews rely on the real-time communications with ground-based medical care providers toward Earth-independent medical operations for astronaut medical care. Medical expertise and decision-making are ground-based for current International Space Station and planned Lunar missions. However, a deep space exploration crew will need to autonomously perform the detection, diagnosis, treatment, and prevention of medical conditions. One approach to provide Earth-independent medical operations is to augment the requisite knowledge, skills, and abilities (KSAs) of a time-constrained crew—operating under stressful conditions, combatting fatigue, and facing a potential medical crisis—with a robust clinical decision support system (CDSS). The CDSS is envisioned as an integrated, software-based tool deployed on a laptop computer or handheld device. The CDSS will assist the crew and ground support when interacting with knowledge/data bases (e.g. records, pharmacy, schedule), instrumentation (e.g. imaging, physiological monitoring devices), and habitat (e.g. wellness system, task performance system) and vehicle systems (e.g. environmental system, communication system). In addition, the human interface will employ a context-based approach that accounts for the crew’s situation. Thus, extraneous and clinically/operationally non-relevant information are reduced to avoid an increase in cognitive load. The framework of an ideal spaceflight CDSS is to include core and advanced analytical features that maintain a flexible platform for integrating new technology in the future. The Exploration Medical Capability (ExMC) Element of the Human Research Program (HRP) is expanding the boundaries of space medical systems to advance the care of astronauts on future exploration missions beyond low Earth orbit by actively identifying and testing next-generation medical care and crew health maintenance technologies. The Clinical Decision Support (CDS) project addressed ap Medical-701 within the Inflight Medical Conditions risk: “We need to increase inflight medical capabilities and identify new capabilities that (a) maximize benefit and/or (b) reduce “costs” on human system/mission/vehicle resources.” Though mass, volume, and power will face increasing constraints, the projected computational capabilities of spacecraft systems will increase exponentially as information technology advances in this decade and beyond. Hence, data, software, and computational resources will play an essential and synergistic role in maintaining crew health, wellness, and performance in deep space missions. The focus of the CDS project was to develop recommended requirements for an in-vehicle CDSS that acts as a ‘virtual assistant’ for delivering optimal health, performance, and medical care during exploration missions. In fiscal year 2022 (FY22), the CDS project was chartered to baseline and/or revise all CDS project related documentation and update the CDS project model to include the revised CDSS Concept of Operations, revised systems-based modeling language (SysML) activity diagrams, and baseline requirements. The focus of this presentation will be an overview of the CDS products and CDS model content.

Decision Support↗

Ablation loading of barium ions into a surface-electrode trap

Trapped-ion quantum information processing may benefit from qubits encoded in isotopes that are practically available in only small quantities, e.g., due to low natural abundance or radioactivity. Laser ablation provides a method of controllably liberating neutral atoms or ions from low-volume targets, but energetic ablation products can be difficult to confine in the small ion-electrode distance, micron-scale microfabricated traps amenable to high-speed, high-fidelity manipulation of ion arrays. Here, we investigate ablation-based ion loading into surface-electrode traps of different sizes to test a model describing ion loading probability as a function of effective trap volume and other trap parameters. We characterize loading of ablated barium from a metallic source in two cryogenic surface-electrode traps with 730 and 50 μm ion-electrode distances. Furthermore, our loading rate agrees with a predictive analytical model, providing insight for the confinement of limited-quantity species of interest for quantum computing, simulation, and sensing.

74 ATOMIC AND MOLECULAR PHYSICS↗

Assessment of Base Loads Generated by an Exercise Device in the HALO Module

The purpose of this document is to prescribe a uniform procedure that can be used to postprocess base loads generated by a crew member and an exercise device in the Gateway Habitation and Logistics Outpost (HALO) module. This memo has three primary sections. First, the exercise loads pass through a Vibration Isolation and Stabilization (VIS) system notionally depicted in Figure 1 for the purpose of preliminary analyses. This is described in Section 2. Next, these loads are processed in frequency domain as explained in Section 3. Finally, the resulting outputs are compared with a Gateway Program Loads and Dynamics (L&D) allocation given to the VIS system. This information is provided in Section 4.

Exercise↗

OPFLearn.jl [SWR-21-109]

OPFLearn.jl is a Julia package for creating datasets for machine learning approaches to solving AC optimal power flow (AC OPF). It was developed to provide researchers with a standardized way to efficiently create AC OPF datasets that are representative of more of the AC OPF feasible load space compared to typical dataset creation methods. The OPFLearn dataset creation method uses a relaxed AC OPF formulation to reduce the volume of the unclassified input space throughout the dataset creation process. Over time this input space tightens around the relaxed AC OPF feasible region to increase the percentage of feasible load profiles found while uniformly sampling the input space. Load samples are processed using AC OPF formulations from PowerModels.jl. More information on the dataset creation method can be found in our publication, "OPF-Learn: An Open-Source Framework for Creating Representative AC Optimal Power Flow Datasets". To use OPFLearn.jl a PowerModels network data dictionary is required (can be loaded from Matpower ".m" files) to define the network the dataset is being created for.

Joswig-Jones, Trager↗

OPFLearn.jl v0.1.2 5/18/2023 [SWR-21-109]

OPFLearn.jl is a Julia package for creating datasets for machine learning approaches to solving AC optimal power flow (AC OPF). It was developed to provide researchers with a standardized way to efficiently create AC OPF datasets that are representative of more of the AC OPF feasible load space compared to typical dataset creation methods. The OPFLearn dataset creation method uses a relaxed AC OPF formulation to reduce the volume of the unclassified input space throughout the dataset creation process. Over time this input space tightens around the relaxed AC OPF feasible region to increase the percentage of feasible load profiles found while uniformly sampling the input space. Load samples are processed using AC OPF formulations from PowerModels.jl. More information on the dataset creation method can be found in our publication, "OPF-Learn: An Open-Source Framework for Creating Representative AC Optimal Power Flow Datasets". To use OPFLearn.jl a PowerModels network data dictionary is required (can be loaded from Matpower ".m" files) to define the network the dataset is being created for.

Joswig-Jones, Trager↗

Reducing Commercial Building Process Loads and Refrigeration Unit Energy Consumption

This resource provides guidance on larger PPLs, many of which are hardwired. Examples include elevators, enterprise servers, freezers, and water fountains with chillers, which are often collectively referred to as "process loads." This resource also outlines how to assess process loads in a building, describes the procedure for identifying which loads to target for reduction, and provides an overview of reduction strategies. In this resource, process loads are broken into five categories - food handling, refrigeration, internal mobility, data center and information technology, and water handling.

commercial buildings↗