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At least 1,369 records · Page 76

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DOE OSTI2023

Preliminary Development of Heat Transfer Model-Based Control Algorithms of Liquid Sodium Purification System: Advanced Sensors and Instrumentation Advanced Controls

Monitoring the operation of sodium purification system is essential for efficient operation of sodium fast reactors. In this work, a heat transfer model has been developed for monitoring the plugging meter and cold trap systems at the Mechanisms Engineering Test Loop (METL) liquid sodium facility at Argonne National Laboratory. The model of the purification system was developed by treating the respective aspects of the cold trap purification loop and plugging meter diagnostic loop as two separate control volumes using information from the METL piping and instrumentation diagram (P&ID). A model predictive controller was designed using first order differential equations with the specified boundary conditions. The system behavior was studied with a tuned optimized procedure using the internal cold trap temperature and plugging meter outlet temperature as control variables, and the air blower temperature as an independent variable respectively. Results of computer simulations obtained in this study compared favorably with experimental data showing very good reference tracking response with negligible overshoot as both plugging meter and cold trap physical models approach the setpoint.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

Development of an open-source regional data assimilation system in PEcAn v. 1.7.2: application to carbon cycle reanalysis across the contiguous US using SIPNET

Abstract. The ability to monitor, understand, and predict the dynamics of the terrestrial carbon cycle requires the capacity to robustly and coherently synthesize multiple streams of information that each provide partial information about different pools and fluxes. In this study, we introduce a new terrestrial carbon cycle data assimilation system, built on the PEcAn model–data eco-informatics system, and its application for the development of a proof-of-concept carbon “reanalysis” product that harmonizes carbon pools (leaf, wood, soil) and fluxes (GPP, Ra, Rh, NEE) across the contiguous United States from 1986–2019. We first calibrated this system against plant trait and flux tower net ecosystem exchange (NEE) using a novel emulated hierarchical Bayesian approach. Next, we extended the Tobit–Wishart ensemble filter (TWEnF) state data assimilation (SDA) framework, a generalization of the common ensemble Kalman filter which accounts for censored data and provides a fully Bayesian estimate of model process error, to a regional-scale system with a calibrated localization. Combined with additional workflows for propagating parameter, initial condition, and driver uncertainty, this represents the most complete and robust uncertainty accounting available for terrestrial carbon models. Our initial reanalysis was run on an irregular grid of ∼ 500 points selected using a stratified sampling method to efficiently capture environmental heterogeneity. Remotely sensed observations of aboveground biomass (Landsat LandTrendr) and leaf area index (LAI) (MODIS MOD15) were sequentially assimilated into the SIPNET model. Reanalysis soil carbon, which was indirectly constrained based on modeled covariances, showed general agreement with SoilGrids, an independent soil carbon data product. Reanalysis NEE, which was constrained based on posterior ensemble weights, also showed good agreement with eddy flux tower NEE and reduced root mean square error (RMSE) compared to the calibrated forecast. Ultimately, PEcAn's new open-source regional data assimilation framework provides a scalable workflow for harmonizing multiple data constraints and providing a uniform synthetic platform for carbon monitoring, reporting, and verification (MRV) as well as accelerating terrestrial carbon cycle research.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Shock tube/laser absorption measurement of the rate constant of the reaction: H 2 O 2 + CO 2 2OH + CO 2

We address the role of the linear mixing rule in the kinetics of the H 2 O 2 decomposition system by reporting the rate constant for H 2 O 2 + M = 2OH + M (M = Ar and CO 2 ) in the temperature range of 1087-1234 K at low pressures in a mixture of 20% CO 2 in Argon. The reaction rate constant was inferred from H 2 O concentrations monitored by using a laser-absorption spectroscopy-based water diagnostic. To the best of our knowledge, this is the first measurement of the rate constant of this reaction in a mixture to be reported in literature. A significant discrepancy was found between the rate constants derived using the traditional linear mixing rule and the reduced pressure linear mixing rule. Furthermore, this discrepancy can have serious implications on the predictive accuracy of these kinetic models, especially under conditions relevant to the operation of supercritical CO 2 (sCO 2 ) power cycles that rely on oxy-fuel combustion in a working fluid comprised almost entirely of CO 2 .

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2022

Laser Doppler vibrometry for piezoelectric coefficient ($d_{33}$) measurements in irradiated aluminum nitride

Sensors used for experiments in advanced reactors must survive in harsh environments. Few material systems can be used to construct sensors viable for extreme conditions. Aluminum nitride (AlN) is one such material because it has high thermal stability and radiation resistance and sustains good piezoelectric and dielectric properties at high temperatures. In this work, the piezoelectric coefficient $d_{33}$ of the AlN single-crystal with thermal and irradiation damage was investigated using an indirect method with a laser Doppler vibrometer (LDV). Surface electrodes were deposited on the AlN samples, and the vibration response of the samples to an applied voltage was monitored using the LDV as a function of the excitation frequency. The $d_{33}$ estimation was based on the excitation voltage and the thickness-mode displacement extracted from the LDV measurements. Further, six AlN substrates were irradiated with 8 MeV Al 2+ at three fluences (10 15 , 10 16 , and 10 17 ions/cm 2 ) and two temperatures (300 °C and 500 °C). The $d_{33}$ for the six irradiated samples and one pristine sample were measured, and the measurement uncertainty was estimated based on five repeated tests. All samples were also measured by a commercial piezometer for comparison. The experimental results demonstrate that the piezoelectric coefficients obtained by LDV were about 0.8–1.16 pm/V lower than those obtained by the piezometer. With the compensation of the clamping effect, the corrected LDV values are similar to the piezometer results. Both show similar trends in all samples, which validates the feasibility of the proposed method for $d_{33}$ measurement. Based on the LDV results, the irradiated samples show a 12%–22% decrease in $d_{33}$ compared with the pristine samples. The samples irradiated under the same fluence at a higher temperature (500 °C) demonstrated a lower $d_{33}$ than those at 300 °C. The effect of the retro-reflective tape, sample temperature, and sample size on the $d_{33}$ measurement were also studied.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Neural-network decoders for measurement induced phase transitions

Open quantum systems have been shown to host a plethora of exotic dynamical phases. Measurement-induced entanglement phase transitions in monitored quantum systems are a striking example of this phenomena. However, naive realizations of such phase transitions requires an exponential number of repetitions of the experiment which is practically unfeasible on large systems. Recently, it has been proposed that these phase transitions can be probed locally via entangling reference qubits and studying their purification dynamics. In this work, we leverage modern machine learning tools to devise a neural network decoder to determine the state of the reference qubits conditioned on the measurement outcomes. We show that the entanglement phase transition manifests itself as a stark change in the learnability of the decoder function. We study the complexity and scalability of this approach in both Clifford and Haar random circuits and discuss how it can be utilized to detect entanglement phase transitions in generic experiments.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2023

The Ionization Profile Monitors in the Recycler Ring

The ionization profile monitors (IPMs) are used to measure the beam size in synchrotrons. Both the Fermilab Recycler and Main Injector (MI) machines have IPMs. However, they were not well understood enough to provide confidence in their measurements. Accurately measuring beam size through the IPMs was crucial to recognize the loss mechanisms for accelerators and to keep the beam loss to a minimum. Thus, performing measurements with different parameters using the IPMs led to a better analysis on how changes in conditions affect the beam size. The IPM measurements are compared with that of multi-wires in the upstream transfer line after applying corrections. The results were compared with other diagnostics and the change in the beam size for different parameters are presented in this paper.

43 PARTICLE ACCELERATORS↗

DOE OSTI2026

A Physics-Based Digital Twin for Wave Elevation and Seabed Moment Estimation of Offshore Monopiles: Preprint

In this work, we present a proof of concept of a physics-based digital twin for a monopile structure (with overhead inertia) subjected to wave loading. The digital twin is formulated using reduced-order models derived from first principles and combined with a Kalman filter for state estimation. The proposed framework estimates the monopile top motion, the wave elevation, and the section forces and moments along the pile using primarily acceleration measurements at the monopile top. Key innovations include the use of a hydrodynamic shape function to represent distributed wave loading in a compact and computationally efficient manner, and the introduction of a shaping filter to augment the state-space with wave kinematics. Synthetic measurement data are generated using OpenFAST and used as a reference to assess the performance of the digital twin. Results demonstrate that the wave elevation can be accurately reconstructed without direct sea-state measurements as long as the wave regime is inertia-dominated. Under the ideal tested conditions, the total hydrodynamic force and sea-bed bending moment are estimated with relative errors on the order of 1% and correlation coefficients exceeding 96%. Future work will evaluate the estimator's performance under operational uncertainties and more complex loading conditions.

17 WIND ENERGY↗

DOE OSTI2021

Fast and Non-Destructive Determination of Water Content in Ionic Liquids at Varying Temperatures by Raman Spectroscopy and Multivariate Regression Analysis

Imidazolium acetate ionic liquids (ILs) have been utilized as promising solvents in many applications that involve varying water content and temperature. These experimental variables affect the anion-cation intermolecular interactions, which in turn influence the performance of the ILs in these applications. Here, this paper shows Raman spectroscopy can be used as an operando method to measure water content in IL solvents when simultaneous temperature changes may occur. The Raman spectra of 1-alkyl-3-methylimidazolium acetate ILs (alkyl chain length n = 2, 4, 6, 8) with varying water content (from 0.028 to 0.899 water mole fraction) and temperature (from 78.1 K to 423.1 K) were measured. Increasing the water content or decreasing the temperature of the tested ILs weakens the anion-cation intermolecular interactions. The water content of these ILs can be quantified even in conditions when the temperature is changing using Raman spectroscopy combined with multivariate regression analysis, including principal component regression (PCR), partial-least-squares regression (PLSR), and artificial neural networks (ANNs). The ANN model combined with partial-least-squares (PLS) achieves the highest prediction accuracy of water content in ILs at varying temperatures (RMSECV = 0.017, R 2 CV = 99.1%, RMSEP = 0.019, R 2 P = 98.8%, RPD = 8.93). Raman spectroscopy provides a potential fast non-destructive operando method to monitor the water content of ILs even in applications when the temperature may be simultaneously altered; this information can lead to the optimized use of these ILs in many applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Leak detection in a subcritical boiler

Thermal power plants experience cycling duty leading to the fatigue of the boiler and heat exchanger tubes. As a result, tube failures occur frequently in coal fired fleets leading to forced outages. Furthermore, because the tube leaks have been the major source of unwanted shutdowns and the number of outages is increasing, present work focuses on the detection and isolation of the leak in a subcritical boiler based upon the process data from a commercial coalfired power plant. The mass balance equation around the steam drum was analyzed using timeseries data collected from a 300 MW power plant. The ratio of the feed water mass flow rate to the steam mass flow rate was defined as a key parameter for detecting leaks. The difference in slope between the feedwater and steam mass flow rate during the normal and faulty operations was established as the upper control limit for real time monitoring. To reduce false alarm rates that arise when raw signal is directly compared against the threshold due to common process fluctuations, an optimal filter was derived for smoothing. It was found that the optimal filter reacted much more quickly to process changes than an exponential moving average filter, around 8 h earlier on average. Occurrence of relatively high false alarm rates even in the filtered responses was related to the cycling of the boiler from the base load condition. Variable threshold was established to keep false alarm rates to the minimum while maintaining the leak detection rate. Finally, the leak was located at the economizer and this could readily be isolated by investigating the magnitude of the mass flow rates ratio and the temperature at the economizer outlet.

42 ENGINEERING↗

DOE OSTI2021

A study on computational fluid dynamics modeling of a refrigerated container for COVID-19 vaccine distribution with experimental validation

A key issue with the distribution of vaccines to prevent COVID-19 is the temperature level required during transport, storage, and distribution. Typical refrigerated transport containers can provide a temperature-controlled environment down to -30 °C. However, the Pfizer vaccine must be carefully transported and stored under a lower temperature between -80 °C and -60 °C. One way to provide the required temperature is to pack the vaccine vials into small packages containing dry ice. Dry ice sublimates from a solid to a gas, which limits the allowable transport duration. This can be mitigated by transporting in a -30 °C refrigerated container. Moreover, because the dry ice will sublimate and thereby release CO 2 gas into the transport container, monitoring the CO 2 concentration within the refrigerated container is also essential. In the present work, a 3D computational fluid dynamics model was developed based on a commercially available refrigerated container and validated with experimental data. The airflow, temperature distribution, and CO 2 concentration within the container were obtained from the simulations. The modeling results can provide guidance on preparing experimental setups, thus saving time and lowering cost, and also provide insight into safety precautions needed to avoid hazardous conditions associated with the release of CO 2 during vaccine distribution.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Seismic Tremors From Sea‐Landfast Ice Interactions Near Utqiaġvik, Alaska

The mechanical state of Arctic landfast sea ice remains poorly constrained due to limited observations. This study investigates interactions between drifting sea ice and the coastal landfast ice near Utqiaġvik, Alaska by integrating data from broadband seismometer, Distributed Acoustic Sensing, and marine radar. We find that decreases in sea ice velocity, marking transitions from drift to compressive contact, coincide with increased seismic energy. Tremor characteristics vary seasonally with ice conditions. In January, dense ice packs produced sustained harmonic tremors with gliding and U-shaped spectral features, consistent with repetitive stick-slip motion at the ice–ice or ice–ground interface under velocity-weakening friction. In April, smaller fragmented floes generated short-lived, chaotic tremors linked to brittle failure and spatially dispersed impacts. These findings demonstrate that seismic tremors encode the mechanical properties of interacting ice, offering a new tool to distinguish ice regimes and monitor evolving Arctic coastal dynamics under climate change.

58 GEOSCIENCES↗

DOE OSTI2020

Toroidal Field Reversing Switch

A motor-driven, high-current switch is being designed by Stäubli Electrical Connectors in collaboration with Princeton Plasma Physics Laboratory to reverse the DIII-D Toroidal field coil current. The existing field reversing procedure requires approximately 4 h of labor performed between run days to reconfigure the bus work, thus requiring a separate run day to complete experimental scans with both field directions. This typically results in different wall conditions which complicate the results or make them invalid. The proposed switch will complete the reversal process in approximately 4-5 min, between shots, so that wall conditions are not a factor, and easily fits within the 10-12 min DIII-D shot cycle. The switch is a compact design fitting into a 157.5 × 41 cm envelope. The switch uses two copper pins that slide between Stäubli MULTILAM contacts. The switch is rated for total current of 180-kA dc for 10 s with a 12-min repetition rate; the maximum operating coil current is 124-kA dc. The switch diagnostics include: voltage drop, current monitor, thermal monitors, position sensors, and motor torque. Here, the switch is rated for 300 cycles per year, and 3000 cycles overall before contact replacement, with contact inspection yearly. The design details and operation of the switch are covered in this article.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

Coastal-Fog Microphysics Using In-Situ Observations and GOES-R Retrievals

Here, the objective of this work is to evaluate GOES-R based fog conditions occurred during the C-FOG (Toward Improving Coastal Fog Prediction) field campaign. C-FOG is designed to advance understanding of fog formation, development, and dissipation over coastal environments to improve its predictability. The project took place along coastlines and open water environments of Eastern Canada (Nova Scotia, NS and the Island of Newfoundland, NL) during August-October of 2018 where environmental conditions play an important role for late season’s fog formation. During the C-FOG field campaign, instruments were located at the Ferryland Supersite, NL, with 2 main sites, and five satellite sites, as well as on the Research Vessel (R/V) Hugh R. Sharp. Key measurement instruments included a Gondola carrying a CDP (cloud droplet probe) and a BCP (backscatter cloud probe) was used for measuring droplet spectra from 1-75 µm on the R/V. A LPM (laser precipitation monitor) with 100 µm-1 cm size range and an OPC (optical particle counter) with 0.3-17 µm at 16 spectral channels provided information for fog and drizzle discrimination. Remote sensing platforms (e.g. profiling microwave radiometer, PMWR), Ceilometer, Lidar), meteorological towers, tethered balloons, and GOES-R products (e.g. fog coverage and droplet size and liquid water path) were used to evaluate fog over horizontal and vertical dimensions. Results suggest that effective radius, phase, liquid water path, and liquid water content values obtained from GOES-R and PMWR were comparable to ground based in-situ observations. It is concluded that integration of observations and nowcasting products may help improve short term local fog predictions.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

Comparison of mercury (Hg) bioaccumulation with mono- and mixed Lemna minor and Spirodela polyrhiza cultures

Mercury (Hg) is a prevalent and harmful contaminant that persists in the environment. For phytoremediation, it is important to discover which plants can bioaccumulate meaningful amounts of Hg while also tolerating its toxicity. Additionally, increasing biodiversity could create a more resilient and self-sustaining system for remediation. This study explores whether mixed populations of Lemna minor and Spirodela polyrhiza can better bioaccumulate and tolerate Hg than monocultures. Mono- and mixed cultures of L. minor and S. polyrhiza were grown in mesocosms of 0.5 μg/L or 100 μg/L Hg ( HgCl2) spiked water for 96 h. Change in weight of duckweed was used to assess Hg tolerance. Diffusive gradients in thin-films (DGTs) were used as surrogate monitoring devices for bioavailable levels of Hg. For biomass growth, the mixed culture of the L. minor was greater than the monoculture at the high dose. The L. minor accumulated more Hg in the mixed culture at the low dose while the S. polyrhiza was higher in the mixed at the high dose. Hg speciation in water was modeled using Windermere Humic Aqueous Model 7 (WHAM7) to compare the bioavailable species indicated by the DGTs. Potentially due to the controlled conditions, the WHAM7 output of bioavailable Hg was almost 1:1 to that estimated by the DGTs, indicating good predictive capability of geochemical modeling and passive sampler DGT on metal bioavailability. Altogether, the mixed cultures statistically performed as well as or better than the monocultures when tolerating and bioaccumulating Hg. However, there needs to be further work to see if the significant differences translate into practical differences worth the extra resources to maintain multiple species.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

DOE OSTI2022

Multicycle flash sintering of cubic Y 2 O 3 -stabilized ZrO 2 : An in situ energy dispersive synchrotron x-ray diffraction study with high temporal resolution

The current induced unit cell volume changes, (111) Bragg peak full width at half maximum (FWHM) and its integrated intensity in 8 % Y 2 O 3 stabilized ZrO 2 (8 %YSZ) solid state electrolyte was monitored during a triple-flash sintering experiment by in situ energy dispersive x-ray diffraction using a polychromatic synchrotron probe (max, photon energy 200 keV) with 2 second temporal resolution. The first spontaneous singularity in the unit cell volume (+0.54 %) was observed at 899 °C under 15 V/mm applied field intensity, which was associated with 13 mA/mm 2 current draw and an increase in density to 97 %. Following anelastic relaxation of the unit cell volume under open circuit conditions, the same applied field was applied twice in a row which resulted in additional induced singularities at 925 °C (+0.48 %) and 944 °C (+0.42 %). A floating baseline, which was above the thermal expansion baseline, was observed from 833 to 969 °C and was attributed to Joule heating. In conclusion, the singularity at 899 °C is associated with a sharp change in (111) FWHM and a 34 % decrease in integrated peak area that was attributed to changes in the distribution of oxygen vacancies and the changes in their concentration as induced by the applied field in the spontaneous transient stage of flash sintering.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Subspace-Driven Learning for Anomaly Detection in Process Transients

Nuclear power plant (NPP) monitoring and diagnostic centers are actively investigating and implementing automated anomaly detection algorithms to help plants catch anomalies sooner, thereby preventing or reducing the duration of unexpected shutdowns. Current machine learning-based anomaly detection methods are expected to be highly effective during stable, full-power operations because NPPs typically operate as baseload power generators, meaning there are extensive operating data available from plant equipment. However, it is expected that anomaly detection methods will face significant challenges during transient conditions (i.e., when power output falls below full power) because plants only occasionally operate at these lower power levels, generating sparse transient operational data, and resulting in false alarms or missed detections. Here, to address this issue, transfer learning is used, which for this problem leverages knowledge (in the form of learned features) from stable, full-power operations to improve detection accuracy during transient conditions, even with limited data. In this effort, a novel subspace approach is developed to transfer a subset of the data features from full power operation to transients. This approach is validated through experiments using synthetic data and was found to outperform two baseline transfer learning approaches in anomaly detection performance across a range of amounts of transient data used in the training process.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗

DOE OSTI2024

Electron bunch position determination using a high frequency button beam position monitor in the AWAKE facility

The AWAKE facility uses novel proton beam-driven plasma wakefields to accelerate electron bunches over 10m of Rubidium plasma. Precise monitoring of 2 diverse beam types necessitates an electron beam position monitor (BPM) working in a frequency regime of tens of GHz. A high frequency conical button-style BPM with a working regime of up to 40 GHz has been investigated as a way to discriminate the electromagnetic fields of 19 MeV, 4 ps electron bunches propagating spatially and temporally together with a 400 GeV, 170 ps proton bunch in the AWAKE common beamline. The sensitivity of the HF BPM to the electron beam position is determined under various beam conditions, with both electrons and protons, and integration with a TRIUMF front-end is discussed.

43 PARTICLE ACCELERATORS↗

DOE OSTI2021

Indoor Occupant Counting by RF Backscattering

Building HVAC (heating, ventilation and air conditioning) consumes approximately 13% of all energy consumption in USA. Motion detectors, cameras and user programmable thermostats have been shown to be ineffective for HVAC controls to save energy, mostly due to the user concerns of comfort, reliability and privacy. A new HVAC control system based on real-time occupant counting that is fully automated, highly accurate, economically sensible and preserving privacy and aesthetics can thus bring forth a disruptive impact to this large energy sector. Our indoor occupant monitoring technology is based on the radio-frequency identification system (RFID), deployed in the room, not on the occupants. One reader with four antennas can be deployed on the ceiling or behind the ceiling panels for every thousand square feet in home, office and assisted living, with or without room partitions. The sticker-like passive tag, 10 cents each and maintenance-free, are profusely hidden on the wall or inside the furniture at arbitrary position, preserving privacy and aesthetics. The large number of tags can realize diverse observation points to accommodate arbitrary room layouts, which is impractical by other active units of camera, infrared, radar or lidar. With 20 tags, the system can reliably detect the number of occupants. For 100 tags, occupant posture and location can be known. The technology has been verified in the research labs and test buildings with very high accuracy. When the real-time occupant number can be accurately known without assuming devices on occupants or occupant motion, the building HVAC system can be automated to achieve building energy saving without sacrificing occupant comfort. According to our limited testing in a few types of building models and the simplified cost calculation, the RFID system has low overall cost in production, deployment, operation and maintenance. The signal processing algorithm based on machine learning requires very small number of training cases as most learning is transferrable for various layouts, and very low computational needs during operation, according to our testing in four different room sizes and layouts. In our preliminary estimate from HVAC saving alone, the RFID system can potentially pay for itself within 1.5 years, in addition to the other enhancement in building automation systems (BAS). Our commercialization strategy and business pitch deck focus on venturing this Cornell occupant monitoring technology into BAS and energy management markets. We have identified three broad BAS market segments of senior living, residential buildings, and office buildings. We have put together the minimum viable product characteristics for these identified segments, including analyses on total cost and competing technologies, as well as the fit and technical gaps for these market segments. We intend to bring the technology to market by licensing or partnering with existing BAS vendors. A list of potential collaborators and licensing partner candidates was assembled for different aspects of integrating our technology into a potential product that can be used with BAS.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗