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At least 1,099 records · Page 61

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 Robust and Flexible Design for GCEP Unattended Online Enrichment Monitoring: An OLEM Collection Node Network

Oak Ridge National Laoratory (ORNL) has engineered an on-line enrichment monitor (OLEM) to continuously measure U-235 emissions from the UF6 gas flowing through a unit header pipe of a gas centrifuge enrichment plant (GCEP) as a component of the International Atomic Energy Agency s (IAEA) new generation of technology to support enrichment plant safeguards1. In contrast to other enrichment monitoring approaches, OLEM calibrates and corrects for the pressure and temperature dependent UF6 gas-density without external radiation sources by using the inherent unit header pipe pressure dynamics and combining U-235 gamma-ray spectrometery using a shielded NaI detector with gas pressure and temperature data near the spectrum measurement point to obtain the enrichment of the gas as a function of time. From a safeguards perspective, OLEM can provide early detection of a GCEP being misused for production of highly enriched uranium, but would not detect directly the isolation and use of a cascade within the production unit to produce HEU. OLEM may also reduce the number of samples collected for destructive assay and, if coupled with load cell monitoring, could support isotope mass balance verification and unattended cylinder verification. The earlier paper presented OLEM as one component along with shared load cells and unattended cylinder verification, in the IAEA emering toolbox for unattended instruments at GCEPs1 and described the OLEM concept and how previous modeling studies and field measurements helped confirm the viability of a passive on-line enrichment monitor for meeting IAEA objectives and to support the development of performance targets. Phase I of the United States Support Program (USSP) OLEM project completed a preliminary hardware, software and communications design; phase II will build and test field prototypes in controlled laboratory settings and then at an operational facility. That paper also discussed many of the OLEM collection node commercial off the shelf (COTS) components and summarized the OLEM collection node data security provisions. This paper will discuss a secure and redundant network of OLEM collection nodes, auxiliary detection units and supporting junction boxes distributed throughout a facility for monitoring enrichment on product, feed and tails unit header pipes; the purpose and capability of the built-in Electronic Optical Sealing System (EOSS) network gateway; and a network approach for obtaining reliable and authenticated pressure measurements.

Younkin, James R↗

Lifetime Prediction of IGBT in a STATCOM Using Modified-Graphical Rainflow Counting Algorithm

Rainflow algorithms are one of the best counting methods used in fatigue and failure analysis [17]. There have been many approaches to the rainflow algorithm, some proposing modifications. Graphical Rainflow Method (GRM) was proposed recently with a claim of faster execution times [10]. However, the steps of the graphical method of rainflow algorithm, when implemented, do not generate the same output as the four-point or ASTM standard algorithm. A modified graphical method is presented and discussed in this paper to overcome the shortcomings of graphical rainflow algorithm. A fast rainflow algorithm based on four-point algorithm but considering point comparison than range comparison is also presented. A comparison between the performances of the common rainflow algorithms [6-10], including the proposed methods, in terms of execution time, memory used, and efficiency, complexity, and load sequences is presented. Finally, the rainflow algorithm is applied to temperature data of an IGBT in assessing the lifetime of a STATCOM operating for power factor correction of the load. From 5-minute data load profiles available, the lifetime is estimated to be at 3.4 years.

Gopi Reddy, Lakshmi Reddy↗

Bayesian Models for Life Prediction and Fault-Mode Classification in Solid State Lamps

A new method has been developed for assessment of the onset of degradation in solid state luminaires to classifY failure mechanisms by using metrics beyond lumen degradation that are currently used for identification of failure. Luminous Flux output, Correlated Color Temperature Data on Philips LED Lamps has been gathered under 85°C/85%RH till lamp failure. The acquired data has been used in conjunction with Bayesian Probabilistic Models to identifY luminaires with onset of degradation much prior to failure through identification of decision boundaries between lamps with accrued damage and lamps beyond the failure threshold in the feature space. In addition luminaires with different failure modes have been classified separately from healthy pristine luminaires. It is expected that, the new test technique will allow the development of failure distributions without testing till L 70 life for the manifestation of failure.

Lall, Pradeep↗

Bayesian probabilistic model for life prediction and fault mode classification of solid state luminaires

A new method has been developed for assessment of the onset of degradation in solid state luminaires to classify failure mechanisms by using metrics beyond lumen degradation that are currently used for identification of failure. Luminous Flux output, Correlated Color Temperature Data on Philips LED Lamps has been gathered under 85°C/85%RH till lamp failure. Failure modes of the test population of the lamps have been studied to understand the failure mechanisms in 85°C/85%RH accelerated test. Results indicate that the dominant failure mechanism is the discoloration of the LED encapsulant inside the lamps which is the likely cause for the luminous flux degradation and the color shift. The acquired data has been used in conjunction with Bayesian Probabilistic Models to identify luminaires with onset of degradation much prior to failure through identification of decision boundaries between lamps with accrued damage and lamps beyond the failure threshold in the feature space. In addition luminaires with different failure modes have been classified separately from healthy pristine luminaires. The α-λ plots have been used to evaluate the robustness of the proposed methodology. Results show that the predicted degradation for the lamps tracks the true degradation observed during 85°C/85%RH during accelerated life test fairly closely within the ±20% confidence bounds. Correlation of model prediction with experimental results indicates that the presented methodology allows the early identification of the onset of failure much prior to development of complete failure distributions and can be used for assessing the damage state of SSLs in fairly large deployments. It is expected that, the new prediction technique will allow the development of failure distributions without testing till L70 life for the manifestation of failure.

Bayesian probability↗

Life Prediction and Classification of Failure Modes in Solid State Luminaires Using Bayesian Probabilistic Models

A new method has been developed for assessment of the onset of degradation in solid state luminaires to classify failure mechanisms by using metrics beyond lumen degradation that are currently used for identification of failure. Luminous Flux output, Correlated Color Temperature Data on Philips LED Lamps has been gathered under 85°C/85%RH till lamp failure. The acquired data has been used in conjunction with Bayesian Probabilistic Models to identify luminaires with onset of degradation much prior to failure through identification of decision boundaries between lamps with accrued damage and lamps beyond the failure threshold in the feature space. In addition luminaires with different failure modes have been classified separately from healthy pristine luminaires. It is expected that, the new test technique will allow the development of failure distributions without testing till L70 life for the manifestation of failure.

Lall, Pradeep↗

Modeling and Analysis Methods for an On-line Enrichment Monitor

The International Atomic Energy Agency (IAEA) has developed an On-Line Enrichment Monitor (OLEM) as one possible component in a new generation of safeguards measures for uranium enrichment plants. The OLEM measures 235U emissions from the UF6 gas flowing through a unit header pipe using NaI(Tl) spectrometers, and corrects for gas density changes using pressure and temperature sensors in order to determine the enrichment of the gas as a function of time. In parallel with the OLEM instrument development, a Virtual OLEM (VOLEM) software tool has been developed that is capable of producing synthetic gamma-ray, pressure, and temperature data representative of a wide range of enrichment plant operating conditions. VOLEM complements instrument development activities and allows the study of OLEM for scenarios that will be difficult or impossible to evaluate empirically. Uses of VOLEM include: investigation of hardware design options; inter-comparison of candidate gamma-ray spectral analysis and enrichment estimation algorithms; uncertainty budget analysis and performance prediction for typical and atypical operational scenarios; and testing of the OLEM data acquisition, analysis and reporting software. This paper describes the technical foundations of VOLEM and illustrates how it can be used. An overview of the nominal instrument design and deployment scenario for OLEM is provided, with emphasis on the key online-assay measurement challenge: accurately determining the portion of the total 235U signal that comes from a background that includes solid uranium deposits on the piping walls. Monte Carlo modeling tools, data analysis algorithms and uncertainty quantification methods are described. VOLEM is then used to quantitatively explore the uncertainty budgets and predicted instrument performance for a plausible range of typical plant operating parameters, and one set of candidate analysis algorithms. Additionally, a series of VOLEM case studies illustrates how an online enrichment monitor might respond in scenarios expected to be atypical, for example weak pressure transients or significant changes in background levels.

Smith, Leon E.↗

Effect of Clad Fast Neutron Flux Distribution on Quarter-Core Fuel Performance Calculations with BISON

As part of the Consortium for Advanced Simulation of Light Water Reactors (CASL), the Virtual Environment for Reactor Applications (VERA) is being developed to provide high-fidelity multiphysics simulations of nuclear reactor cores. Over the past year, a one-way coupling capability has been developed, taking power and temperature data from MPACT/CTF calculations and running standalone BISON fuel rod cases. This has allowed CASL contributors to gain insight into the fuel performance characteristics while a more tightly coupled methodology between MPACT, CTF, and BISON has been under development. Many of the initial analyses have focused on the Watts Bar Unit 1 core using a fast flux factor—the default approach—which defines the clad fast flux as a linear function of the local linear heat rate. While this approach is more valid when considering single rod cases in isolation, in larger problems such as full-sized reactors, the local linear heat rate does not directly correlate to the clad fast neutron flux. For example, variations in assembly enrichment can lead to larger neutron fluxes in neighboring assemblies that may be at lower enrichment and power. Similarly, considering axial effects, spacer grids suppress power locally, but the fast neutron flux is significantly less affected, and the approach can lead to an underestimation of the fast neutron flux at that time. A poor estimation of the clad fast flux values can affect the clad creep rate, fuel-clad gap, and clad stresses. Additionally, the fast flux factor has been considered constant throughout the life of the rod. As the cycle progresses, the spectrum will harden as burnable absorbers and 235U deplete, so the fast flux would be expected to increase as the spectrum hardens. The effect on quantities of interest are highlighted for the first cycle of the Watts Bar Unit 1 core, comparing the results from an explicit clad fast flux representation from MPACT to the constant fast flux factor approach used in previous analyses. Future work will consider multicycle effects to assess the impact at higher burnups.

Stimpson, Shane G.↗

Joint UAS-Balloon Activities (JUBA) Field Campaign Report

Using internal investment funds within Sandia National Laboratories’ (SNL) Division 6000, the Joint UAS-Balloon Activity (JUBA) was a collaborative exercise between SNL Organizations 6533 and 6913 (later 8863) to demonstrate simultaneous flights of tethered balloons and unmanned aerial systems (UAS) on the North Slope of Alaska. JUBA UAS and tethered balloon flights were conducted within the Restricted Airspace associated with the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) Climate Research Facility third ARM Mobile Facility (AMF3) site at Oliktok Point, Alaska. The Restricted Airspace occupies a two-nautical-mile radius around Oliktok Point. JUBA was conducted at the Sandia Arctic Site, which is approximately 2 km east-southeast of the AMF3. JUBA activities occurred from 08/08/17 and 08/10/17. Atmospheric measurements from tethered balloons can occur for a long duration, but offer limited spatial variation. Measurements from UAS could offer increased spatial variability. To understand how balloon and UAS activities could occur together, JUBA activities included the following: Developing aviation safety plans for the simultaneous, collocated operation of tethered balloons and UAS Adapting tethered balloon-based fiber optic distributed temperature sensing (DTS) measurements to a UAS platform Creating solutions to technical challenges such as: Developing a motor system to match the fiber deployment rate with the ascent/descent rate of the UAS Evaluating methods of identifying the surface in the DTS temperature profile Correlating simultaneous balloon and UAS DTS temperature measurements Assessing the effects of a fiber optic rotary joint on the DTS temperature measurements Determining what UAS-based sensors provided the best calibration source for the DTS temperature data.

North Slope of Alaska, arctic processes, unmanned ↗

Introducing GEOPHIRES v2.0: Updated Geothermal Techno-Economic Simulation Tool

This paper presents an updated version of the geothermal techno-economic simulation tool GEOPHIRES (GEOthermal energy for Production of Heat and electricity ('IR') Economically Simulated). GEOPHIRES combines engineering models of the reservoir, wellbores, and surface plant facilities of a geothermal plant with an economic model to estimate the capital and operation and maintenance costs, lifetime energy production, and overall levelized cost of energy. The available end-use options are electricity, direct-use heat, and cogeneration. The main updates in the new version include conversion of the source code from FORTRAN to Python, the option to import temperature data (e.g., measured or from stand-alone reservoir simulator), updated cost correlations, and more flexibility in selecting the time step and number of injection and production wells. In this paper, we provide an overview of all the updates and two case studies to illustrate the tool's new capabilities.

15 GEOTHERMAL ENERGY↗

Effects of Reactive Power on Photovoltaic Inverter Reliability and Lifetime

For predicting the reliability and lifetime of Photovoltaic (PV) inverters, thermal cycling is considered the most important stressors in the inverter system. To realize this, a detailed electrothermal model of the PV inverter was developed along with the controllers. The model was verified by developing an in-house inverter, which was placed inside a thermal chamber to verify the losses and temperature rise within the system at various temperatures. After the verification of the model, a reduced order model of the inverter was implemented which can translate the mission profile of ambient temperature and solar irradiance into load profile of junction temperatures of the switches. The estimated junction temperature data was used to identify the reliability indices and predict the useful lifetime of the inverter system. After developing the models to predict useful lifetime of the system, the impact of reactive power on the overall reliability of the system was studied. Experiments show that lifetime and reliability of the inverter decreases as the operating power factor decreases from unity. The results are presented and discussed here.

14 SOLAR ENERGY↗

Molten salt to supercritical CO2 diffusion-bonded heat exchanger testing to support component certification for advanced nuclear power systems

Commercial utilization of the diffusion-bonded heat exchanger (DBHE) for high-temperature applications has prompted an ASME Boiler and Pressure Vessel Code Case development effort to employ these components in Section III (nuclear plant) applications. As part of this effort, a series of DBHE have been fabricated. These heat exchangers will be among the first printed-circuit geometries to be tested for functionality in a molten salt environment. These 15-25kW test specimens will be evaluated under steady-state conditions to compare pressure drop and terminal temperatures measurements with those predicted by existing flow and heat transfer correlations. The test units will then be subjected to thermal transients similar to those expected in Generation IV reactor systems by varying the hot and cold fluid mass flow rates and by changing inlet temperatures. Data collected from these tests will narrow the technical gaps related to two-fluid PCHE and identify special design requirements of compact heat exchangers containing primary reactor coolant. Descriptions of one of two test units and the testing plan are discussed here.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Supercritical carbon dioxide tubular flow under temporally varying thermal boundary condition

During transient operation of fusion power plants the amount of thermal energy transferred from plasma to surrounding blanket modules will be varied over time, and will affect behavior of the working fluid inside the blanket and power conversion system where the coolant is in a supercritical state. Transient behavior of the power is in pulsed state in tokamak. The Optimized Supercritical Cycle Operation (OSCO) loop is constructed to investigate the thermohydraulic characteristics of the supercritical fluid under temporally varying thermal boundary condition. In this study the tube outer wall temperature data are measured for abrupt change in thermal power as a preliminary power transient test. The OSCO test conditions are selected to include the erratic behavior of the supercritical fluid under pseudo-critical condition during transient. In order to incorporate the delayed response of utilized thermocouples, a time constant is applied to adjust the obtained results. Along with the experimental study, computational fluid dynamic software is used to perform detailed analysis over the test section geometry. The preliminary test results are presented for comparison against the available correlations from the literature. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Effects of Rangeland Evapotranspiration on Groundwater Recharge, Discharge, and Flow at the Tuba City, Arizona, Disposal Site - 17159

The US Department of Energy Office of Legacy Management is modeling groundwater flow and contaminant transport at a former uranium mill site near Tuba City, Arizona. A goal is to project groundwater travel times and flow volumes between the former mill site and Moenkopi Wash, a down-gradient stream. Aquifer recharge and discharge are sensitive model parameters; however, assigning representative rates is inexact and involves approximations. We applied a remote sensing algorithm to determine spatially variable evapotranspiration (ET), precipitation recharge, and groundwater discharge rates for use in a large scale groundwater flow model for the site. ET is the combination of evaporation and plant transpiration from soil and groundwater. We estimated landscape-scale ET over a 13-year period (2000 to 2012) for distinct plant communities within a 3531-hectare groundwater model domain (GMD), and then evaluated effects of ET on groundwater recharge and discharge within the GMD. Our empirical algorithm was derived from ground ET measurements, multispectral satellite imagery, and temperature data. Groundwater recharge or discharge rates were calculated for each plant community (or ET Zone) as the difference between precipitation (PPT) and ET rates. Recharge occurred in plant communities where PPT exceeded ET; discharge occurred where ET exceeded PPT. Estimates of groundwater recharge rates for upland plant communities that survive on meteoric water ranged from 0 to 88 mm yr{sup -1}. Estimates of groundwater discharge for phreatophyte plant communities ranged from 23 mm yr{sup -1} to 150 mm yr{sup -1}. Phreatophytes are plants that survive by extracting groundwater. Zero recharge occurred in plant communities where ET rates equaled annual average precipitation. An increase in groundwater recharge (PPT > ET) was associated with past land disturbances and heavy livestock grazing in upland areas. Groundwater discharge (ET > PPT) was highest in riparian phreatophyte communities, but lower than optimal in upland phreatophyte communities impacted by heavy grazing. Protecting phreatophyte communities from grazing at Tuba City could potentially increase ET from 153 mm yr{sup -1} to at least 500 mm yr{sup -1}. The validity of using the ET algorithm to estimate recharge and discharge was evaluated by comparing the net volumetric outflow rate for the model domain with base flow measurements collected from Moenkopi Wash. Modeled outflow approximated measured flow gains in the Wash, increasing our confidence in the ET algorithm and in the model. Results suggest that rangeland management practices that reduce groundwater recharge rates and increase groundwater discharge rates should be evaluated as part of an overall groundwater remediation strategy. (authors)

54 ENVIRONMENTAL SCIENCES↗

Multiphysics Demonstration of Temperature-Driven Assembly Bowing in SFRs using MOOSE-Based Codes

Core bowing is an important passive safety mechanism in liquid metal cooled fast reactors. When the core restraint system is properly designed, temperature and flux gradients influence assemblies in the core to bow into less reactive configurations during accident scenarios, resulting in negative reactivity feedback. Prediction of core bowing involves complex interplay of radiation transport, impacts of fluid flow and heat transfer on duct temperature, and mechanical responses to the induced temperature and flux gradients. Under the U.S. Department of Energy Office of Nuclear Energy’s Advanced Modeling and Simulation (NEAMS) Program [1], an integrated multiphysics approach is being developed to model the core bowing phenomena in liquid metal-cooled fast reactors with the Multiphysics Object Oriented Simulation Environment (MOOSE) [2]. In this methodology, the MOOSE-based reactor physics code Griffin [3] will solve the neutron transport equation and determine the power distribution. With the detailed power distribution from Griffin, the subchannel analysis codes MOOSE-Subchannel [4] and Pronghorn [5] are utilized to calculate the assembly temperature distribution. MOOSE’s Solid Mechanics [6] and Contact [7] Modules are leveraged to calculate the thermal expansion and duct bowing displacement with the duct wall temperature from thermal hydraulics calculation. In this work, an initial one-way coupling demonstration of the integrated multiphysics approach has been performed on a seven-assembly problem based on the sodium-cooled fast reactor ABR-1000 design [8]. The neutronics calculation with Griffin is not yet involved in the current simulation. MOOSE-Subchannel and Pronghorn evaluate fluid and solid temperature based on a fixed power distribution. In addition, one-way coupling is utilized in this coupled calculation, via Pronghorn passing the duct temperature data to the MOOSE Solid Mechanics calculation. An assessment of the Solid Mechanics module was performed in parallel to verify duct bowing behavior with duct-to-duct contact phenomenon [9]. The displacement from MOOSE Solid Mechanics is not yet transferred back and utilized in the Pronghorn and MOOSE-Subchannel calculation. This model will be available on the National Reactor Innovation Center (NRIC) Virtual Test Bed (VTB) repository [10]. Future stages of this work will involve solving problems of increasing complexity as well as adding more physics (e.g. reactor physics) to the integrated workflow to reach the end goal of modeling the core bowing phenomenon with an integrated multiphysics workflow.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Constraining the redshift evolution of the cosmic microwave background blackbody temperature with Planck data

We constrain the deviation of adiabatic evolution of the universe using the data on the cosmic microwave background (CMB) temperature anisotropies measured by the Planck satellite and a sample of 481 X-ray selected clusters with spectroscopically measured redshifts. To avoid antenna beam effects, we bring all of the maps to the same resolution. We use a CMB template to subtract the cosmological signal while preserving the Thermal Sunyaev–Zeldovich (TSZ) anisotropies; next, we remove galactic foreground emissions around each cluster and we mask out all known point sources. If the CMB blackbody temperature scales with redshift as T(z)=T{sub 0}(1+z){sup 1−α}, we constrain deviations of adiabatic evolution to be α = −0.007 ± 0.013, consistent with the temperature-redshift relation of the standard cosmological model. This result could suffer from a potential bias δα associated with the CMB template. We quantify it to be |δα|⩽0.02, with the same sign as the measured value of α. Our result is free from those biases associated with using TSZ selected clusters; it represents the best constraint to date of the temperature-redshift relation of the Big Bang model using only CMB data, confirming previous results.

79 ASTRONOMY AND ASTROPHYSICS↗