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At least 307 records · Page 17

Time-Dependent Material Data Essential for the Durability Analysis of Composite Flywheels Provided by Compressive Experiments

Successful spaceflight operations require onboard power management systems that reliably achieve mission objectives for a minimal launch weight. Because of their high specific energies and potential for reduced maintenance and logistics, composite flywheels are an attractive alternative to electrochemical batteries. The Rotor Durability Team, which comprises members from the Ohio Aerospace Institute (OAI) and the NASA Glenn Research Center, completed a program of elevated temperature testing at Glenn' s Life Prediction Branch's Fatigue Laboratory. The experiments provided unique design data essential to the safety and durability of flywheel energy storage systems for the International Space Station and other manned spaceflight applications. Analysis of the experimental data (ref. 1) demonstrated that the compressive stress relaxation of composite flywheel rotor material is significantly greater than the commonly available tensile stress relaxation data. Durability analysis of compression preloaded flywheel rotors is required for accurate safe-life predictions for use in the International Space Station.

Thesken, John C.↗

A Prognostics Framework for Battery Health Monitoring Integrated with Thermal Modeling

Urban Air Mobility (UAM) promises to revolutionize transportation in major cities, offering passenger travel, cargo delivery, and emergency medical services through a network of electric vertical takeoff and landing (eVTOL) aircraft. However, the limited range of current eVTOLs, due to the low specific energy of lithium-ion batteries along with a possibility of thermal runaway conditions poses significant safety concerns, leading to potentially compromising operational safety. To address this critical challenge, researchers are actively evaluating the impact of flight and environmental conditions on onboard lithium-ion battery health. This involves carefully assessing the performance of battery packs under laboratory and operational conditions for developing models to estimate future health using prognostics framework. This study examines the effectiveness of evaluating battery degradation leading to catastrophic failures under varying operational conditions in laboratory. These are captured using physics based models of underlying phenomenons and integrated into the prognostics framework. A fully charged battery undergoes controlled discharge cycles at varying C-rates based on the simulated power draw profile, with current and voltage, temperature data recorded throughout the experiment. The observed data provides valuable insights into how different operating conditions and mission profiles affect battery performance. This information is crucial for developing strategies to optimize battery systems, enhance range, and ultimately ensure the safe and reliable operation of UAM vehicles.

Thermal Modeling↗

A Prognostics Framework for Battery Health Monitoring Integrated with Thermal Modeling

Urban Air Mobility (UAM) promises to revolutionize transportation in major cities, offering passenger travel, cargo delivery, and emergency medical services through a network of electric vertical takeoff and landing (eVTOL) aircraft. However, the limited range of current eVTOLs, due to the low specific energy of lithium-ion batteries along with a possibility of thermal runaway conditions poses significant safety concerns, leading to potentially compromising operational safety. To address this critical challenge, researchers are actively evaluating the impact of flight and environmental conditions on onboard lithium-ion battery health. This involves carefully assessing the performance of battery packs under laboratory and operational conditions for developing models to estimate future health using prognostics framework. This study examines the effectiveness of evaluating battery degradation leading to catastrophic failures under varying operational conditions in laboratory. These are captured using physics based models of underlying phenomenons and integrated into the prognostics framework. A fully charged battery undergoes controlled discharge cycles at varying C-rates based on the simulated power draw profile, with current and voltage, temperature data recorded throughout the experiment. The observed data provides valuable insights into how different operating conditions and mission profiles affect battery performance. This information is crucial for developing strategies to optimize battery systems, enhance range, and ultimately ensure the safe and reliable operation of UAM vehicles.

Thermal Modeling↗

A Prognostics Framework for Battery Health Monitoring Integrated with Thermal Modeling

Urban Air Mobility (UAM) promises to revolutionize transportation in major cities, offering passenger travel, cargo delivery, and emergency medical services through a network of electric vertical takeoff and landing (eVTOL) aircraft. However, the limited range of current eVTOLs, due to the low specific energy of lithium-ion batteries along with a possibility of thermal runaway conditions poses significant safety concerns, leading to potentially compromising operational safety. To address this critical challenge, researchers are actively evaluating the impact of flight and environmental conditions on onboard lithium-ion battery health. This involves carefully assessing the performance of battery packs under laboratory and operational conditions for developing models to estimate future health using prognostics framework. This study examines the effectiveness of evaluating battery degradation leading to catastrophic failures under varying operational conditions in laboratory. These are captured using physics based models of underlying phenomenons and integrated into the prognostics framework. A fully charged battery undergoes controlled discharge cycles at varying C-rates based on the simulated power draw profile, with current and voltage, temperature data recorded throughout the experiment. The observed data provides valuable insights into how different operating conditions and mission profiles affect battery performance. This information is crucial for developing strategies to optimize battery systems, enhance range, and ultimately ensure the safe and reliable operation of UAM vehicles.

Thermal Modeling↗

National Aeronautics and Space Administration operations: Remote sensing experiments in the New York Bight, 7-17 April 1975

Results are given of remote sensing experiments conducted in the New York Bight between April 7-17, 1975, to evaluate the role of remote sensing technology to aid in monitoring ocean dumping. Remote sensors were flown on the C-54, U-2, and C-130 aircraft while the National Oceanic and Atmospheric Administration obtained concurrent in situ sea truth data using helicopters and surface platforms. The test site, aircraft platforms, experiments, and supporting sensors are described. The operation of each aircraft are discussed and aircraft flight lines, flight parameters, and data identification parameters are presented in figures and tables.

Usry, J. W.↗

OSO-8 soft X-ray wheel experiment: Data analysis

The soft X-ray experiment hardware and its operation are described. The device included six X-ray proportional counters, two of which, numbers 1 and 4, were pressurized with on-board methane gas supplies. Number 4 developed an excessive leak rate early in the mission and was turned off on 1975 day number 282 except for brief (typically 2-hour) periods up to day 585 after which it as left off. Counter 1 worked satisfactorily until 1975 day number 1095 (January 1, 1978) at which time the on-board methane supply was depleted. The other four counters were sealed and all except number 3 worked satisfactorily throughout the mission which terminated with permanent satellie shut-down on day 1369. This was the first large area thin-window, gas-flow X-ray detector to be flown in orbit. The background problems were severe and consumed a very large portion of the data analysis effort. These background problems were associated with the Earth's trapped electron belts.

Kraushaar, W. L.↗

Rossi-alpha Analysis of CURIE Experiment

Critical assembly measurement and operations are crucial to the development of benchmark data to support research into criticality safety, radiation-detection development, and the overall application of nuclear technologies. Accurate nuclear data are needed for accurate predictive simulations, and validation using critical experiments is an important part of the nuclear data pipeline. The accuracy of nuclear data are improved using more robust and targeted measurements. In particular, the intermediate energy range of uranium is of great interest. LANL has successfully performed the Zeus series of experiments on the Comet assembly to investigate the intermediate energy range for HEU with various moderators. A successor to these experiments is the benchmark for the Critical Unresolved Region Integral Experiment (CURIE), designed to be sensitive to the unresolved resonance region (URR). This experiment is designed using polytetrafluoroethylene, more commonly known as Teflon, moderators. The CURIE experiment was successfully conducted at the National Criticality Experiments Research Center (NCERC). The Rossi-alpha method was used to evaluate the propensity of the CURIE configurations to sustain fission chains by estimating the prompt neutron decay constant α. This work evaluates the α at delayed critical using Rossi-alpha for different Teflon moderator thicknesses in the CURIE experiment. These results will help improve understanding of the CURIE benchmark experiments.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Enhanced Component Performance Study: Air-Operated Valves 1998–2020

This report presents an enhanced performance evaluation of air-operated valves (AOVs) at U.S. commercial nuclear power plants. The data used in this study are based on the operating experience failure reports from calendar year 1998 through 2020 as reported in the Institute of Nuclear Power Operations (INPO) Industry Reporting and Information System (IRIS). The AOV failure modes considered are failure-to-open/close (FTOC), failure to operate or control (FTOP), and spurious operation (SO). The component reliability estimates and the reliability data are trended for the most recent 10-year period while yearly estimates for reliability are provided for the entire study period. The following trends were identified for the most recent 10-year period: o Extremely statistically significant increasing trend for the frequency of FTOC demands (demands per reactor year) for low-demand (= 20 demands per year) AOVs o Extremely statistically significant increasing trend for the frequency of FTOC demands for high-demand (> 20 demands per year) AOVs o Highly statistically significant decreasing trend for the failure rate of FTOP for low-demand AOVs o Highly statistically significant decreasing trend for the frequency of FTOP events (failures per reactor year) for low-demand AOVs o Statistically significant decreasing trend for the failure rate of SO for low-demand AOVs o Statistically significant decreasing trend for the frequency of SO events (failures per reactor year) for low-demand AOVs.

99 GENERAL AND MISCELLANEOUS↗

Enhanced Component Performance Study: Motor-Operated Valves 1998-2020

This report presents an enhanced performance evaluation of motor-operated valves (MOVs) at U.S. commercial nuclear power plants. The data used in this study are based on the operating experience failure reports from calendar year 1998 through 2020 as reported in the Institute of Nuclear Power Operations (INPO) Industry Reporting and Information System (IRIS). The MOV failure modes considered are fail to open or close (FTOC), fail to operate or control (FTOP), and spurious operation (SO). The component reliability estimates and the reliability data are trended for the most recent 10-year period while yearly estimates for reliability are provided for the entire study period. The following increasing trend was identified for MOVs for the most recent 10-year period: • Low-demand MOV frequency of FTOC demands (demands per reactor year). The following increasing trends were identified for MOVs for the most recent 10-year period: • Low-demand MOV FTOC failure probability • Low-demand MOV frequency of FTOC events (failures per reactor year).

99 GENERAL AND MISCELLANEOUS↗

Enhanced Component Performance Study: Motor-Operated Valves 1998-2024

This report presents an enhanced performance evaluation of motor-operated valves (MOVs) at U.S. commercial nuclear power plants. The data used in this study are based on the operating experience failure reports from calendar year 1998 through 2024 as reported in the Institute of Nuclear Power Operations (INPO) Industry Reporting and Information System (IRIS). The MOV failure modes considered are fail to open or close (FTOC), fail to operate or control (FTOP), and spurious operation (SO). The component reliability estimates and the reliability data are trended for the most recent 10-year period while yearly estimates for reliability are provided for the entire study period. The following increasing trend was identified for MOVs for the most recent 10-year period: • Low-demand MOV frequency of FTOC demands (demands per reactor year). The following decreasing trends were identified for MOVs for the most recent 10-year period: • Low-demand MOV FTOC failure probability • High-demand MOV SO failure rate • Low-demand MOV frequency of FTOC events (failures per reactor year) • High-demand MOV frequency of SO events (failures per reactor year).

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

AIACHNE's contribution for Nuclear Energy Agency Working Party on International Nuclear Data Evaluation Co-operation Subgroup 50

The AIACHNE (AI/ML Informed cAlifornium CHi Nuclear data Experiment) project aims at designing an experiment for the 252 Cf Prompt Fission Neutron Spectrum (PFNS) that explores systematic biases in an experimental database retrieved from the EXFOR databases. To that end, machine learning (ML) methods were applied to pint-point measurement features likely related to bia. From that information, we selected a feature that should be explored by the AIACHNE experiment. Measurement features are metadata encapsulating all pertinent information about the physical measurement and analysis techniques. Examples are, for instance, what neutron and fission detectors were used for the physical metadata, and what background reduction techniques were employed for analysis techniques. Such metadata were retrieved both from EXFOR entries as well as the literature of data sets described in detail in Ref. [2]. The prerequisite for applying machine learning techniques is casting the metadata into a format that can be parsed by the algorithm. This step might seem trivial but requires to find a unique language where metadata that carry the same physics meaning across several experiments must have the same identifier. One example is, for instance, the neutron detector. As seen in Figure 1, the machine learning code identified the use of 6 Li detectors as being related to bias in some datasets of the AIACHNE 252 Cf PFNS experimental database. In fact, here are several experiments that used neutron detectors containing 6Li in the database, for instance for the example below. EXFOR format has a unique keywords describing detectors such as “SCIN” or “GLASD”. One may think that these keywords are already sufficient descriptors for ML to uniquely find an issue. However, “SCIN” (used for [3, 4]) and “GLASD” (used for [5]) fail to inform the algorithm what is the active material in the detector. And, the key common issue leading to bias in 252 Cf related to neutron detectors is not whether it is a glass detector or a scintillator. No, the issue is that 6 Li was within both detector types and that even small mistakes in the detector response functions around approximately 200 keV are amplified by the 6 Li(n,α) resonance there leading to bias in data as highlighted in Fig. 1 and Ref. [1]. Hence, the features describing the neutron detector must call out the active material in the detector, rather than the existing EXFOR detector keyword, that the ML algorithm can find physically meaningful features related to bias. The AIACHNE team used a precursor of the WPEC (Working Party on International Nuclear Data Evaluation Co-operation) SG(Subgroup)-50 format to store the metadata for the ML analysis.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

The Nimbus-6 User's Guide

Background information was given on the Nimbus 6 spacecraft and experiments as a basis for selecting, obtaining, and utilizing Nimbus 6 data in research studies. The basic spacecraft system operation and the objectives of the Nimbus 6 flight are outlined, followed by a detailed discussion of each of the experiments. The format, archiving, and access to the data are also described. Finally, the contents and format of the Nimbus 6 data catalogs are described. These catalogs will be issued periodically after the launch of Nimbus 6. They will contain representative pictorial data and daily temperature, humidity, infrared and radiometer data obtained during each period, as well as information on the collection and availability of all Nimbus 6 data.

Sissala, J. E.↗

Research analysis of Space Shuttle Orbiter entry aerothermodynamic flight data at the NASA Langley Research Center

The methods used to analyze the aerothermodynamic data gathered from the Shuttle protoflights are reviewed. Trajectory and atmospheric reconstruction allow an accurate definition of the freestream environment through which the Shuttle has flown. The reconstructions, combined with aerodynamic coefficient and convective heating rate determinations, provide predictive capability for comparison with future flights. Data are acquired by operational instrumentation (12,000 parameters), development flight instrumentation (4500 measurements), and Orbiter experiments instrumentation; tracking and meteorological data are also included in the analyses. The aerothermodynamic and aerodynamic technology base for large, winged, lifting body entry vehicles is being expanded by the analysis efforts. Sensor locations on the Shuttle and data management techniques are described.

Throckmorton, D. A.↗

Cloud Ozone Dust Imager (CODI): Investigation and Technical Plan - Volume 1

The Cloud Ozone Dust Imager (CODI) is proposed to investigate the current climatic balance of the Mars atmosphere, with particular emphasis on the important but poorly understood roles which dust and water ice aerosols play in this balance. The large atmospheric heating (20-50 K) resulting from global dust storms around Mars perihelion is well recognized. However, groundbased observations of Mars atmospheric temperatures, water vapor, and clouds since the Viking missions have identified a much colder, cloudier atmosphere around Mars aphelion that may prove as important as global dust storms in determining the interannual and long-term behavior of the Mars climate. The key climate issues CODI is designed to investigate are: 1) the degree to which non-linear interactions between atmospheric dust heating, water vapor saturation, and cloud nucleation influence the seasonal and interannual variability of the Mars atmosphere, and 2) whether the strong orbital forcing of atmospheric dust loading, temperatures and water vapor saturation determines the long-term balance of Mars water, as reflected in the north-south hemispheric asymmetries of atmospheric water vapor and polar water ice abundances. The CODI experiment will measure the daily, seasonal and (potentially) interannual variability of atmospheric dust and cloud opacities, and the key physical properties of these aerosols which determine their role in the climate cycles of Mars. CODI is a small (1.2 kg), fixed pointing camera, in which four wide-angle (+/- 70 deg) lenses illuminate fixed filters and CCD arrays. Simultaneous sky/surface imaging of Mars is obtained at an angular resolution of 0.28 deg/pixel for wavelengths of 255, 336, 502, and 673 nm (similar to Hubble Space Telescope filters). These wavelengths serve to measure atmospheric ozone (255 and 336 nm), discriminate ice and dust aerosols (336 and 673 nm), and construct color images (336, 502, and 673 nm). The CODI images are detected on four 512 x 512 pixel arrays, as partitioned on two 1024 x 1024 CCD's operated in frame transfer mode. The center of the CODI field-of-view is canted 40 deg from the zenith direction to obtain sky brightness measurements and a 20 deg surface field-of-view. Daily image observations will be conducted when the Sun is greater than or equal to 5 deg outside the edge of the CODI field-of-view, and twilight and nighttime imaging will obtained on a weekly basis. The 673 nm channel includes a polarizer wheel to obtain sky/surface polarimetry. A dust cover protects the entire lens assemblies of all four CODI channels. This opaque dust cover, which is normally opened for CODI imaging, includes a small fixed mirror and transparent window positioned above the 673 nm lens, to redirect the 673 nm field-of-view to the surface for descent imaging. Fixed pointing, internal data buffering, low operating power (2-4 W for less than or equal to 30 seconds), selective data transmission, and simple operational characteristics of the CODI experiment place minimum resource and operational demands on the Mars Surveyor 1998 lander. The CODI science goals are optimized for, but not restricted to, a low-latitude landing site (20 deg S-30 deg N). The primary CODI measurement objectives are the opacities, wave forms, particle properties (size, shape, and alignment), and heights of clouds; the opacities, particle properties, and vertical distribution of dust; and the opacity and vertical distribution of ozone. The variability of cloud, ozone, and dust opacities will be determined on diurnal, daily, and seasonal timescales. Wind velocities will be determined from cloud motions and wave characteristics; and the temporal variability of atmospheric water vapor, with limited altitude information, will be inferred from the CODI ozone observations. Secondary measurement objectives include limited descent imaging capability, surface uv-visible photometry and polarimetry, photochemistry, and meteorite infall rates.

Clancy, R. Todd↗

Check-Standard Testing Across Multiple Transonic Wind Tunnels with the Modern Design of Experiments

This paper reports the result of an analysis of wind tunnel data acquired in support of the Facility Analysis Verification & Operational Reliability (FAVOR) project. The analysis uses methods referred to collectively at Langley Research Center as the Modern Design of Experiments (MDOE). These methods quantify the total variance in a sample of wind tunnel data and partition it into explained and unexplained components. The unexplained component is further partitioned in random and systematic components. This analysis was performed on data acquired in similar wind tunnel tests executed in four different U.S. transonic facilities. The measurement environment of each facility was quantified and compared.

Deloach, Richard↗

WIRE-21 Sensor Irradiation Experiment Ready for HFIR Insertion

The ability to deploy new nuclear fuels for current or future reactor concepts requires a wealth of data regarding fuel performance during normal operation, anticipated operational occurrences, and design-basis accidents. Most of these data have historically been collected during experiments in materials test reactors, ideally with online instrumentation to collect as much data as possible. However, advanced instrumentation could also allow for in situ monitoring of fuel operating conditions during commercial reactor operation to maximize fuel utilization, reduce unnecessary conservativism in design margins, and improve operator understanding of limiting peaking factors. The latter approach would complicate fuel handling, particularly during refueling, unless the instrumentation could be placed inside the fuel rods and transmitted wirelessly to a receiver located outside the fuel’s primary pressure boundary. To this end, Westinghouse Electric Company (WEC) developed wireless sensors based on inductive coupling that can transmit information regarding fuel centerline temperatures and rod internal pressures wirelessly from within a fuel rod to a nearby instrument thimble. After testing these sensors in lower-power university research reactors, the next step is to perform high neutron fluence testing to characterize the performance of these wireless sensors under conditions that are more representative of the intended application—in this case, light-water reactors (LWRs). The removable Be (RB) positions of the High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory (ORNL) provide the neutron flux, experiment volume, and access to instrument leads required to achieve these sensor testing goals. This report summarizes the design, analysis, and assembly of the Wireless Instrumented RB Experiment 2021 (WIRE-21). This is the most highly instrumented irradiation experiment ever performed in HFIR. The experiment will use seven different sensing techniques to measure temperature, pressure, neutron flux, and neutron fluence during reactor operation. In addition to WEC’s wireless temperature and pressure sensors, WIRE-21 includes an array of thermocouples, self-powered neutron detectors, spatially distributed fiber optic temperature sensors, passive SiC temperature monitors, and flux wires. The design of WIRE-21 and the cabling that was installed in HFIR also provide the infrastructure to enable accelerated, economical testing of advanced sensor technologies while leveraging the extremely high neutron flux that is available in HFIR. The containment for WIRE-21 is similar to previous RB irradiation vehicles but includes a few modifications, most notably the use of integrated compression seals to pass a larger number of sensor leads through the experiment’s pressure boundary. In addition to the sensor leads, inert gas lines are passed into the experiment to enable active temperature control and the ability to pneumatically actuate a bellows-driven pressure sensor. WIRE-21 is targeting component temperatures (300–350°C) and neutron fluence levels (~10 22 n/cm 2 ) that would be expected in the plenum region of LWR fuels, except for the active sensing region of the wireless temperature sensor, which is targeting LWR fuel centerline temperatures (~800–1,100°C). WIRE-21 was successfully assembled, passed all nondestructive examination, and was delivered to HFIR for insertion during upcoming cycle 498 (April 2022).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Pilot interaction with cockpit automation - Operational experiences with the Flight Management System

Results are presented of two studies on the potential effect of cockpit automation on the pilot's performance, which provide data on pilots' difficulties with understanding and operating one of the core systems of cockpit automation, the Flight Management System (FMS). The results of both studies indicate that, although pilots do become proficient in standard FMS operations through ground training and subsequent flight experience, they still have difficulties tracking the FMS status and behavior in certain flight contexts and show gaps in the understanding of the functional structure of the system. The results suggest that design-related factors such as opaque interfaces contribute to these difficulties, which can affect the pilot's situation awareness.

Sarter, Nadine B.↗