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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

FY 23 Filtration of Hanford Tank 241-SY-101 Supernatant at 16 °C

Approximately 9 liters of supernatant from Hanford waste tank 241-SY-101 was delivered by Washington River Protection Solutions to the Radiochemical Processing Laboratory (RPL) at Pacific Northwest National Laboratory. The thirty-six SY-101 sample bottles were comprised of six sets of six samples, with each set pulled from a unique tank sampling level. Prior to testing, samples from each level were composited to provide nominally level-independent feed for dead end filtration and ion exchange testing. The composited 241-SY-101 supernatant was chilled to 16 °C for 1 week prior to testing. Filtration testing was then conducted using a backpulse dead-end filter (BDEF) system equipped with a feed vessel and a Mott inline filter Model 6610 (Media Grade 5) in the hot cells of the RPL. This was done to provide waste processing benchmarks for 200 West Area wastes in the West Area Risk Management project. The feed was filtered through the BDEF system at a targeted flux of 0.065 gpm/ft 2 . During filtration of the differential pressure required to effect filtration at 0.065 gpm/ft 2 increased little over the filtration campaign and never reached 2 psid (the Tank Side Cesium Removal system action limit). This indicates that the Media Grade 5 filter should perform well when processing SY-101 supernatant. After completing filtration of the SY-101 feed, the filter was cleaned. Solids concentrated from the backpulse solutions displayed calcium phosphate, aluminum oxides, aluminum-chromium nanoparticle agglomerates. Electron diffraction was used to determine the types of phases that were present in the solids. Most of the phases found were only weakly crystalline, possibly owing to their rapid precipitation during the process water treatment. The identifications of the phases therefore are tentative.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

KIPM Detector Characterization in QUIET

Kinetic Inductance Phonon‑Mediated (KIPM) detectors are superconducting microwave resonators that sense energy depositions in the substrate through a transient shift in their resonant frequency. In this work, I installed new devices in the QUIET cryogenic facility and used a network analyzer to drive them across a range of power levels. At each setting, I measured the transmitted signal and fit it to a simple notch‑filter model, allowing us to extract key performance metrics. Despite the increased noise at low power, the model consistently captured the resonance behavior. I first measured the resonance parameters as a function of RF drive power, then repeated the measurement across a range of temperatures to test whether the device behaved like an MKID. While the notch-filter fits captured the resonance reliably, the observed temperature dependence did not match the expected MKID signature — indicating that these first in-house fabricated chips are not yet functioning as true MKIDs. Overall, this reframes our work as a study of resonance parameter extraction and identification, pointing towards future iterations of device design and fabrication to get the true MKID response.

Savitala, Akash [U. Washington, Seattle (main); Fe↗
DOE OSTI2024

Filtration of Hanford Tank 241-AN-107 Supernatant at 16 °C

Approximately 9 liters of supernatant from Hanford waste tank 241-AN-107 was delivered by Washington River Protection Solutions to the Radiochemical Processing Laboratory (RPL) at Pacific Northwest National Laboratory. The thirty-six AN-107 sample bottles consisted of six sets of six samples, with each set pulled from a unique tank sampling level. Prior to testing, samples from each level were composited to provide nominally level-independent feed for dead end filtration and ion exchange testing. The composited 241-AN-107 supernatant was chilled to 16 °C for 1 week prior to testing. Filtration testing was then conducted using a backpulse dead-end filter (BDEF) system equipped with a feed vessel and a Mott inline filter Model 6610 (Media Grade 5) in the hot cells of the RPL. The purpose of this testing is to a) demonstrate dead-end filtration (DEF) of AN-107 feed at reduced temperature to obtain prototypic tank side cesium removal (TSCR) flux rates and identify issues that may impact filtration after dilution to 5.5M Na, and b) provide feed for a follow on ion exchange unit operation. The feed was filtered through the BDEF system at a targeted flux of 0.065 gpm/ft 2 . During filtration the differential pressure required to effect filtration at 0.065 gpm/ft 2 was slow to increase for most of the filtration campaign. After all the feed bottles had been pumped into the slurry reservoir, the bottoms of the bottles were added to the reservoir and transmembrane pressure (TMP) reached 2.0 psid (the TSCR action limit). The prototypic filter cleaning process was unable to effectively restore filter performance, and cleaning with oxalic acid was required before flow through the filter could be restored. This indicates that the Media Grade 5 filter may require an alternative cleaning protocol when processing AN-107 supernatant. After completing filtration of the AN-107 feed, the filter was cleaned. Solids concentrated from the backpulse solutions were composed of natrophosphate, Mn-Fe phases, and fluoro-natrophosphate that occurred as particle agglomerates. The individual particles were in some cases 100s of micrometers across which is consistent with prior observations from AN-107 supernate waste characterizations.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Fiscal Year 2021 Filtration of Hanford Tank 241-AP-107 Supernatant Samples Obtained at Prototypic Tank Level and Filtered at 16 °C

Bench-scale filtration testing of 8.5 liters of supernatant from Hanford waste tank 241-AP-107, chilled to 16 °C, was conducted using a backpulse dead-end filter (BDEF) filtration system equipped with a feed vessel and a Mott inline filter Model 6610 (Media Grade 5) in the hot cells of the Radiochemical Processing Laboratory at Pacific Northwest National Laboratory. This was done to assess the impact of a lower sampling location within the tank as well the lowered filtration temperature on supernatant stability and fouling. The as-received samples were transferred to 1.5-liter poly bottles and held at 16 °C for approximately 1 week prior to filtration. The feed was filtered through the BDEF system at a targeted flux of 0.065 gpm/ft 2 to match the prototypic operation of the TSCR system. During the initial period of filtration, the differential pressure required to effect filtration at 0.065 gpm/ft 2 increased until it reached 2 psid [the Tank Side Cesium Removal (TSCR) action limit] at 26 hours. After this, the filter was backpulsed to dislodge accumulated solids and reduce this pressure differential. An additional eight backpulses were conducted during the initial filtration period; each time, the target pressure was reached sooner than during the previous interval. Volume filtered decreased from 0.9 to 0.03 m 3 /m 2 over the course of 14 processing hours. After the ninth backpulse, the backpulse frequency had become unsustainable, and it was decided to perform an extensive filter cleaning. The filter was cleaned by draining the chilled AP-107 feed into chilled holding containers, introducing 0.1 M NaOH into the feed vessel, and recirculating the NaOH through the system for 20 minutes before allowing the system to soak for 2 hours without temperature control. A measurable decrease in filter resistance during this recirculation indicated that the 0.1 M NaOH was likely dissolving some of the solids that had deposited on the filter. Post cleaning, the filter resistance was effectively restored to initial conditions as the initial transmembrane pressure was restored to original levels. However, resumed processing of the AP-107 feed at 16 °C continued to result in an increased rate of filter resistance. An additional five backpulses were conducted (four during feed processing, one during subsequent cleaning) before the conclusion of the test. Solids concentrated from the backpulse solutions displayed sodium oxalate-type phases, Al-oxides and sodium Al-oxides/carbonates, iron oxides, and Ca-bearing phases (calcite). The scanning electron microscopy analyses also revealed a large distribution of particles, with some particles, notably sodium phosphate dodecahydrate, having diameters close to 0.5 mm.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Filtration of Hanford Tank 241-AW-105 Supernatant at 16 °C

Approximately 9 L of supernatant from Hanford waste tank 241-AW-105 was delivered by Hanford Tank Waste Operations and Closure (H2C) to the Radiochemical Processing Laboratory (RPL) at Pacific Northwest National Laboratory (PNNL). The thirty-six 241-AW-105 sample bottles consisted of four sets of nine samples, with each set pulled from a unique tank sampling level. Prior to testing, samples from each level were composited and diluted to 5.5 M Na to provide nominally level-independent feed for dead-end filtration and ion exchange testing. The composited 241-AW-105 supernatant was chilled to 16 °C for 1 week prior to testing. Filtration testing was then conducted using a backpulse dead-end filter (BDEF) system equipped with a feed vessel and a Mott inline filter (Model 6610, Media Grade 5) in the hot cells of the RPL. The purpose of this testing was to (a) demonstrate dead-end filtration (DEF) of 241-AW-105 feed at reduced temperature to obtain prototypic Tank Side Cesium Removal (TSCR) flux rates and identify issues that may impact filtration after dilution to 5.5 M Na, and (b) provide feed for follow-on ion exchange unit operation. The feed was filtered through the BDEF system at a targeted flux of 0.065 gpm/ft2. For most of the filtration campaign, the differential pressure required to effect filtration at 0.065 gpm/ft2 was slow to increase. After all the feed bottles had been pumped into the slurry reservoir, the bottoms of the bottles were added to the reservoir and transmembrane pressure (TMP) reached 2.0 psid (the TSCR action limit). A backpulse was performed after >50 hours of filtration to remove fouled solids and reduce the TMP. The filter was cleaned after completing filtration of the 241-AW-105 feed, and clean water flux tests showed filter performance was effectively restored. Solids concentrated from the backpulse solutions were composed of steel-like particles, uranium-bearing phases, Mn-Fe phases, a Ce-bearing phase, Zr phases, and some smaller Ca-bearing particles. The Ca-bearing and U bearing phases were identified as calcite and clarkeite, respectively.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Fiscal Year 2022. Filtration of Hanford Tank 241-AP-101 Supernatant at 16 °C

Bench-scale filtration testing of ~9 liters of supernatant from Hanford waste tank 241-AP-101, chilled to 16 °C, was conducted using a backpulse dead-end filter (BDEF) filtration system equipped with a feed vessel and a Mott inline filter Model 6610 (Media Grade 5) in the hot cells of the Radiochemical Processing Laboratory at Pacific Northwest National Laboratory. This was done to assess the performance of the anticipated third feed to the Tank Side Cesium Removal (TSCR) system. The as-received samples were diluted to the target sodium concentration and transferred to 1.5-liter polyethylene bottles and held at 16 °C for approximately 1 week prior to filtration. The feed was filtered through the BDEF system at a targeted flux of 0.065 gpm/ft 2 to match the prototypic operation of the TSCR system. During filtration, the differential pressure required to effect filtration at 0.065 gpm/ft 2 increased little over the filtration campaign and never reached 2 psid (the TSCR action limit). This indicates that the TSCR filter should perform well when processing AP-101 supernatant. After completing filtration of the AP-101 feed, the filter was cleaned. Solids concentrated from the backpulse solutions displayed sodium nitrate-type phases, aluminum and silicon phases reported as cancrinite or nitrate-cancrinite, a mixed chromium-aluminum oxide, iron oxides, and Ca-bearing phases (calcite). Scanning electron microscopy analyses showed that the average particle size was 0.5 micron.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Boosting H I -Galaxy Cross-Clustering Signal through Higher-Order Cross-Correlations

After reionization, neutral hydrogen (${\rm H\, \small {I}}$) traces the large-scale structure (LSS) of the Universe, enabling ${\rm H\, \small {I}}$ intensity mapping (IM) to capture the LSS in 3D and constrain key cosmological parameters. We present a new framework utilizing higher-order cross-correlations to study ${\rm H\, \small {I}}$ clustering around galaxies, tested using real-space data from the IllustrisTNG300 simulation. This approach computes the joint distributions of k-nearest neighbor (kNN) optical galaxies and the ${\rm H\, \small {I}}$ brightness temperature field smoothed at relevant scales (the kNN-field framework), providing sensitivity to all higher-order cross-correlations, unlike two-point statistics. To simulate ${\rm H\, \small {I}}$ data from actual surveys, we add random thermal noise and apply a simple foreground cleaning model, filtering out Fourier modes of the brightness temperature field with k ∥ < k min,∥ . Under current levels of thermal noise and foreground cleaning, typical of a Canadian Hydrogen Intensity Mapping Experiment (CHIME)-like survey, the ${\rm H\, \small {I}}$-galaxy cross-correlation signal in our simulations, using the kNN-field framework, is detectable at >30σ across r = [3, 12] h –1 Mpc. In contrast, the detectability of the standard two-point correlation function (2PCF) over the same scales depends strongly on the foreground filter: a sharp k ∥ filter can spuriously boost detection to 8σ due to position-space ringing, whereas a less sharp filter yields no detection. Nonetheless, we conclude that kNN-field cross-correlations are robustly detectable across a broad range of foreground filtering and thermal noise conditions, suggesting their potential for enhanced constraining power over 2PCFs.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

KIPM Detector Characterization in QUIET

Kinetic Inductance Phonon‑Mediated (KIPM) detectors are superconducting microwave resonators on silicon that sense bursts of energy through tiny shifts in their resonance. In this work, we installed new devices in the QUIET facility's cryogenic test setup and used a network analyzer to drive them across a range of power levels. At each setting, we measured the transmitted signal and fit it to a simple notch‑filter model, allowing us to extract key performance metrics. And despite the increased noise at low power, our model consistently captured the resonance behavior. We observed that the resonant frequency stayed stable across most powers, the device s internal quality factor improved with stronger signals, and its coupling strength peaked mid‑range before leveling off. Overall, these findings confirm the detector s performance, laying groundwork for future work on energy calibration with pulsed optical sources.

Savitala, Akash [Washington U., Seattle; Fermilab]↗
DOE OSTI2023

Process Cycle Modeling with AI

Here a convoluted process model-filtering technique is presented that can build and successfully train the structural property artifacts of materials after multiple heat treatment cycles.

Romanov, Vyacheslav↗
DOE OSTI2025

Nonlinear Ensemble Filtering with Diffusion Models: Application to the Surface Quasigeostrophic Dynamics

The intersection between classical data assimilation methods and novel machine learning techniques has attracted significant interest in recent years. Here, we explore another promising solution in which diffusion models are used to formulate a robust nonlinear ensemble filter for sequential data assimilation. Unlike standard machine learning methods, the proposed ensemble score filter (EnSF) is completely training free and can efficiently generate a set of analysis ensemble members. Here, in this study, we apply the EnSF to a surface quasigeostrophic model and compare its performance against the popular local ensemble transform Kalman filter (LETKF), which makes Gaussian assumptions in the analysis step. Numerical tests demonstrate that EnSF maintains stable performance in the absence of localization and for a variety of experimental settings. We find that while LETKF maintains optimal performance in the case of linear observations of the entire state and a perfect model, EnSF shows improvements over LETKF when nonlinear observations are assimilated and the system is subject to unexpected model errors. A spectral decomposition of the analysis results in this nonlinear observation regime shows that the largest improvements over LETKF occur at large scales (small wavenumbers), where LETKF lacks sufficient ensemble spread. Overall, this initial application of EnSF to a geophysical model of intermediate complexity motivates further development of the algorithm for more realistic problems.

Artificial intelligence↗
DOE OSTI2022

Multifidelity Ensemble Kalman Filtering Using Surrogate Models Defined by Theory-Guided Autoencoders

Data assimilation is a Bayesian inference process that obtains an enhanced understanding of a physical system of interest by fusing information from an inexact physics-based model, and from noisy sparse observations of reality. The multifidelity ensemble Kalman filter (MFEnKF) recently developed by the authors combines a full-order physical model and a hierarchy of reduced order surrogate models in order to increase the computational efficiency of data assimilation. The standard MFEnKF uses linear couplings between models, and is statistically optimal in case of Gaussian probability densities. This work extends the MFEnKF into to make use of a broader class of surrogate model such as those based on machine learning methods such as autoencoders non-linear couplings in between the model hierarchies. We identify the right-invertibility property for autoencoders as being a key predictor of success in the forecasting power of autoencoder-based reduced order models. We propose a methodology that allows us to construct reduced order surrogate models that are more accurate than the ones obtained via conventional linear methods. Numerical experiments with the canonical Lorenz'96 model illustrate that nonlinear surrogates perform better than linear projection-based ones in the context of multifidelity ensemble Kalman filtering. We additionality show a large-scale proof-of-concept result with the quasi-geostrophic equations, showing the competitiveness of the method with a traditional reduced order model-based MFEnKF.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Large-Eddy Simulation of a wind turbine using a Filtered Actuator Line Model

When dealing with multirotor devices such as quadcopters or wind farms, the cost of blade-resolved large-eddy simulation (LES) becomes prohibitive. Combining LES with a family of lower-fidelity models, called actuator line models (ALMs), has grown in popularity in the past decade. ALM replaces full blade resolution with an array of actuator points or lines parameterized by aerodynamic lift/drag polar plots along the blades. Body forces computed based on these actuator points are then projected onto the LES flow mesh, mimicking the effect of rotating blades on the flow. However, the optimal projection radius and the associated LES grid size is often too restrictive for multirotor simulations. Recently, a new tip-correction-based filtered ALM (F-ALM) was proposed by Martinez-Tossas and Meneveau (2019), which allows coarser-than-optimal grids by avoiding the associated overprediction of thrust. In this work, F-ALM is implemented into a high-order, in-house LES code to simulate National Renewable Energy Laboratory Phase VI wind turbine. It is then followed by a comparison between the baseline ALM and the newly implemented F-ALM in terms of instantaneous and time-averaged flow fields and blade loads, revealing the advantages of F-ALM in preventing the overprediction of power on coarse grids. Finally, this encourages accurate and affordable simulations of multirotor devices in the future.

17 WIND ENERGY↗
DOE OSTI2026

Data-based filtered dissipation rate modelling for multi-modal turbulent combustion: evaluating a priori model generalizability

Manifold-based models offer a computationally efficient alternative to directly transporting the thermochemical state in computational simulations of turbulent reacting flows, projecting the high-dimensional thermochemical state-space onto a low-dimensional manifold. Recent efforts have yielded a manifold-based model applicable to multi-modal combustion, enabling reconstruction of the thermochemical state from solutions to two-dimensional manifold equations in mixture fraction and generalized progress variable that are parameterised by three scalar dissipation rates. In coarse-grained simulations such as Large Eddy Simulation (LES), closure of the multi-modal manifold equations and subfilter variances/covariance requires closure of three filtered scalar dissipation rates. Here, the present work adopts a data-based approach, providing closure for the three filtered scalar dissipation rates via deep neural networks (DNNs). High-fidelity datasets corresponding to an autoigniting n-dodecane jet flame and a bluff body swirl-stabilized confined lifted spray flame of two aviation fuels (Jet-A and C1) with different ignition propensities are leveraged to generate training data that spans a diverse range of thermodynamic conditions and combustion modes, including low- and high-temperature ignition regimes in addition to premixed and nonpremixed behaviour. A final DNN model is trained to enforce inherent physical constraints by learning nonlinear functional transformations of the three filtered scalar dissipation rates. The generalizability of this constrained DNN model is demonstrated a priori via conditional statistics evaluated on the lifted spray flame with C1–a configuration that had not been included in the training data. Excellent DNN agreement with conditional DNS statistics is observed, and integrated gradients are computed to identify the most sensitive input variables. The similarity of the marginal PDFs of the most informative input variables and outputs across configurations are quantified via the Wasserstein metric, demonstrating that data-based models may successfully generalize to unseen parametric conditions so long as the most informative input variables share similar distributions across training and testing datasets.

Data-based modelling↗
DOE OSTI2022

Estimation of plasma properties using an extended Kalman filter with plasma global models

A physically-constrained extended Kalman filter (EKF) is applied to various zero-dimensional global models for the estimation of plasma properties using time-dependent experimental data such as the plasma density or ion flux. The capability of the EKF is demonstrated to estimate unknown system states simultaneously, such as reaction rate coefficients and the absorbed electron input power, which can be difficult, if not impossible, to measure experimentally. Global models accounting for pure argon reactions and argon-oxygen reactions are used in this work to demonstrate the ability of the filter to estimate dynamic and complex systems. Furthermore, the results obtained from the EKF plasma global model illustrate that model-data fusion techniques can be used to estimate plasma properties and processes for time-varying systems, such as pulsed discharges.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Development of a Model Correlating Axial HEPA Filter Performance Between Elevated and Standard Conditions

The ASME AG-1 Code specifies minimum rated airflow based on standard cubic feet per minute (SCFM) for axial high efficiency particulate air (HEPA) filters and actual cubic feet per minute (ACFM) for radial HEPA filters with corresponding maximum pressure drop. A quantitative analysis can be performed to demonstrate the variation in filter efficiency and develop a correlation of performance between axial filters subjected to ACFM and SCFM. This study illustrates the variation in filter efficiency of axial HEPA filters subjected to ACFM and SCFM flow rate conditions at varying atmospheric pressures. It also presents the methods used to calculate correction factors to convert filter efficiency and pressure drop from elevated to standard conditions. The Axial Large Scale Test Stand (ALSTS) in the Institute for Clean Energy Technology (ICET) at Mississippi State University has been utilized to control aerosol concentration, flowrate, atmospheric pressure, relative humidity, and temperature. The filter test matrix consists of axial HEPA filters rated at 1,000 and 1,500 CFM with varying filter pack types. Each filter is subjected to varying pressures of 14.70 psi, 13.55 psi, 12.40 psi, and 11.25 psi, temperatures of 70 deg. F, 110 deg. F, and 150 deg. F, and relative humidities of 50% and 80%, resulting in twenty-four unique testing points. The corresponding SCFM flow rates are computed for each point in order to form a comparison. Evaluation of the effects of designating ACFM or SCFM will be based upon the filter efficiencies of generated Dioctyl Phthalate (DOP) particles at a diameter of 0.3 micrometers. The results show filter efficiency decreasing as atmospheric pressure decreases due to increased filter face velocity. A correlation model is developed to convert filter efficiency and pressure drop at elevated conditions to those of standard pressure, relative humidity, and temperature.

42 ENGINEERING↗
DOE OSTI2026

Characterizing Turbulence at a Forest Edge: Comparing Sub-Filter Scale Turbulence Models in Simulations of Flow over a Canopy

In wildfires, atmospheric turbulence plays a major role in the transfer of turbulent kinetic energy. Understanding how turbulence feeds back into a dynamical system is important, down to the varying small scales of fuel structures (i.e. pine needles, grass). Large eddy simulations (LES) are a common way of numerically representing turbulence. The Smagorinsky model (1963) serves as one of the most studied sub-grid scale representations in LES. In this investigation, the Smagorinsky model was implemented in HIGRAD/FIRETEC, LANL’s coupled fire-atmosphere model. This study was motivated by the need to quantitatively investigate the vorticity budget equation in HIGRAD/FIRETEC. The Smagorinsky turbulent kinetic energy (TKE) was compared to FIRETEC’s 1.5-order TKE eddy-viscosity subgrid-scale model, known as the Linn turbulence model. This was done in simulations of flow over flat terrain with a homogeneous, cuboidal canopy in the center of the domain. Examinations of the modeled vertical TKE profile and turbulent statistics at the leading edge, and throughout the canopy, show that the Smagorinsky model provides comparable results to that of the original closure model posed in FIRETEC.

58 GEOSCIENCES↗