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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Uncertainty Aware Deep Learning for Fault Prediction Using Multivariate Time Series Signals

The superconducting radio-frequency cavities are a crucial component of the Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab. When a cavity faults, beam delivery to experimental end users is disrupted. Prediction of cavity faults prior to onset is essential to reduce operation and maintenance costs. In this work, a parallel long short-term memory (LSTM)-convolution neural network (CNN)-based deep learning (DL) model is proposed to predict impending faults using pre-fault signals. Further, we introduce an uncertainty quantification approach using Monte Carlo dropout with the LSTM-CNN model to ascertain confidence in the prediction. The model was tested using multivariate time series signals from stable cavity operations and before faults. Initial results show that on the test dataset, the model can identify impending faults before their onset with an average 10-fold cross validation accuracy of 97.39% and a standard deviation of 0.12% using a 100-ms time window. It is also observed that the model performs better as the prediction time moves closer to the fault onset. For additional context, we compare the performance of the model with three machine-learning-based (ML) fault prediction models. Our proposed parallel LSTM-CNN-based DL method shows better performance than the ML-based methods.

Rahman, Md Monibor↗
DOE OSTI2025

Neural network-based classification and regression of magnetohydrodynamic modes in tokamaks

We present a machine learning-based magnetohydrodynamic (MHD) classifier and regressor that utilizes real or complex-valued 3D magnetic sensor array data to determine neoclassical tearing mode (NTM) onset times in tokamaks with millisecond accuracy. The input dataset consists of poloidal profiles of complex Fourier amplitudes with an n = 1 toroidal mode number from 144 human-labeled ITER Baseline Scenario discharges in the DIII-D tokamak, spanning both tearing-dominated and sawtooth-dominated regimes. Since m, n = 2,1 NTMs frequently emerge alongside sawteeth at the same frequency in this scenario, the focus is on isolating the m = 1 and m = 2 components of the n = 1 MHD mode near the tearing onset. To improve model regularization and prediction stability, singular value decomposition was applied to balance the sawtooth and tearing datasets. The enriched datasets facilitated training neural networks that learn the key distinguishing features of sawtooth and tearing modes in the poloidal profiles of their magnetic amplitude and phase. When the modes occur independently, the networks achieve perfect classification due to the modes’ distinct characteristics and low measurement noise. In the more experimentally relevant case where both modes coexist, the networks maintain exceptional performance across key metrics. Tests on synthetic data with known ground truth demonstrate the superior accuracy of the neural network trained on complex-valued input compared to models using real amplitude, phase, or pseudo-complex data, achieving both a mean time delay and standard deviation below 1 ms. Notably, standard linear regression methods fitting the dominant singular modes to the data closely match the neural network’s performance. Applying these methods across a broad range of H-mode scenarios will enable future studies to systematically identify dominant NTM triggers as scenario-specific variables, paving the way for more effective tearing mode avoidance strategies in future fusion reactor designs.

machine learning↗
DOE OSTI2021

Design and characterization of a single-channel microwave interferometer for the Helicon Physics Prototype eXperiment

A heterodyne interferometer for measuring the plasma electron density in Helicon Physics Prototype eXperiment (HPPX) has been developed and characterized in the laboratory. The heterodyne-type interferometer uses a probing beam of 85 GHz and a reference beam of 85.7 GHz by using two Gunn oscillators for facilitating frequency modulation. The cutoff density for this frequency is 8.96 x 10 19 m –3 that is much higher than the nominal electron density of the HPPX plasmas. The maximum deflection angle due to the refraction effect is estimated to be 0.63° assuming a parabolic electron density profile, and the impact on the measurement is negligible for the plasmas with a size of 100 mm. Two identical HDPE lenses act as the vacuum windows, and the lenses working together with the transmitter and receiver horns, form a beam with the beam waist of about 20 mm located at the plasma center. The characterization results of the lens and the critical microwave components show good performance. The plasma electron density measurement results are in line with the expectation. Furthermore, the Signal to Noise Ratio (SNR) of the measurement is defined as SNR = 20lg($\bar{n}_{e}$/S), where $\bar{n}_{e}$ and S are respectively the average electron density and the standard deviation of the signal, and the SNR is 80 dB. Finally, this demonstrates the system's capability of providing a clear and detailed density resolution.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Overview of interpretive modelling of fusion performance in JET DTE2 discharges with TRANSP

In the paper we present an overview of interpretive modelling of a database of JET-ILW 2021 D-T discharges using the TRANSP code. The main aim is to assess our capability of computationally reproducing the fusion performance of various D-T plasma scenarios using different external heating and D-T mixtures, and to understand the performance driving mechanisms. We find that interpretive simulations confirm a general power-law relationship between increasing external heating power and fusion output, which is supported by absolutely calibrated neutron yield measurements. A comparison of measured and computed D-T neutron rates shows that the calculations' discrepancy depends on the absolute neutron yield. The calculations are found to agree well with measurements for higher performing discharges with external heating power above ~20 MW, while low-neutron shots display an average discrepancy of around +40% compared to measured neutron yields. A similar trend is found for the ratio between thermal and beam-target fusion, where larger discrepancies are seen in shots with dominant beam-driven performance. We compare the observations to studies of JET-ILW D discharges, to find that on average the fusion performance is well modelled over a range of heating power, although an increased unsystematic deviation for lower-performing shots is observed. The ratio between thermal and beam-induced D-T fusion is found to be increasing weakly with growing external heating power, with a maximum value of ≳1 achieved in a baseline scenario experiment. An evaluation of the fusion power computational uncertainty shows a strong dependence on the plasma scenario type and fusion drive characteristics, varying between ±25% and 35%. D-T fusion alpha simulations show that the ratio between volume-integrated electron and ion heating from alphas is ≲10 for the majority of analysed discharges. Alphas are computed to contribute between ~15% and 40% to the total electron heating in the core of highest performing D-T discharges. An alternative workflow to TRANSP was employed to model JET D-T plasmas with the highest fusion yield and dominant non-thermal fusion component because of the use of fundamental radio-frequency heating of a large minority in the scenario, which is calculated to have provided ~10% to the total fusion power.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Characterizing core and edge turbulence regimes with fluctuation imaging diagnostics in Wendelstein 7-X

Two density fluctuation imaging systems, phase contrast imaging (PCI) and gas puff imaging (GPI) measure spatially resolved density fluctuations with high time resolution throughout the core plasma (PCI) and in the scrape-off layer (GPI) of the Wendelstein 7-X (W7-X) stellarator. Both systems combined give a comprehensive overview of overall fluctuation levels, spectral properties such as their distribution in frequency and wavenumber space as well as their spatial distribution. These tools are used to assess changes in density turbulence in three representative discharges that transition into stable divertor detachment by different strategies (impurity seeding, density ramping and power starvation). Several general trends are identified when the radiated power fraction is systematically increased: In the plasma edge, the line emission observed by GPI shifts radially inward with a drop in electron temperature, and normalized intensity fluctuation profiles follow this inward shift. Skewness and kurtosis of these edge fluctuations are reduced, indicating a reduction of large intermittent transport events, and poloidal phase velocities decrease in magnitude. These observations are consistent with a reduced power input into the plasma edge and a general reduction of turbulent activity. Core density fluctuation levels remain nearly constant in the impurity seeding scenario, indicating that detachment does not significantly impact turbulence there. However, a strong reduction in the dominant outboard fluctuation phase velocity is observed that deviates from the previous interpretation of neoclassical radial electric field changes, showing that the core plasma is not completely unaffected. In the density ramp and power starvation scenarios, undesirable and irregular large-scale events arise clearly in both diagnostic systems as the radiative fraction is increased. Impurity seeding therefore seems to be a promising strategy on W7-X to achieve detachment without significantly altering core turbulence, especially when targeting a specific operating point in core density and heating power.

Wendelstein 7-X↗
DOE OSTI2025

Mitigation of ICRF—edge plasma interaction in Alcator C-Mod

The parasitic interaction between ion cyclotron range of frequencies (ICRF) waves and the edge plasma has long limited high-power ICRF utilization in magnetically confined fusion plasmas. In this paper, we report on the successful mitigation of this interaction by power tapering a four-strap field-aligned (FA) antenna in the Alcator C-Mod tokamak. With the antenna operated in dipole phasing ($0\pi0\pi$), the ratio of the power coupled by the central two straps ($P_\mathrm {cent}$) to the power coupled by the outer two straps was varied at fixed total coupled ICRF power ($P_\mathrm {tot}$). With $P_\mathrm {cent}$/$P_\mathrm {tot} \approx 0.8-0.9$, no enhancement of the plasma potential was measured despite 1 MW of coupled ICRF power. When the antenna is powered, energy deposition increases on its four corners and on neighboring limiter tiles magnetically connected to some of those corners. The energy deposited on the antenna and limiter is minimized together with near-field plasma potentials. Additionally, we show that deviation from $P_\mathrm {cent}$/$P_\mathrm {tot} \approx 0.8$ enhances wave-plasma interactions in places not magnetically connected to the antenna. These far-field effects are correlated with changes in the antenna spectrum. Hence, on C-Mod, near-field and far-field interactions were minimized for about the same range of $P_\mathrm {cent}$/$P_\mathrm {tot}$. Optimal power tapering was also found to improve ICRF heating efficiency and facilitate H-mode access. Finally, we show that the heat flux pattern on the toroidally aligned antennas reverses with the direction of the RF-induced E×B flow in front of the antenna, a correlation not observed for the FA antenna. We argue that the RF-induced E×B flow, which carries high-density plasma from the near-SOL, is aligned with the FA antenna and does not intercept its corners, where the plasma potential is large. This could explain the previously reported smaller impurity generation by the FA antenna (Wukitch et al 2013 Phys. Plasmas 20 056117).

Alcator C-Mod↗
DOE OSTI2020

Experimental studies of 1.5 – 1.6 μm high-power single-frequency semiconductor lasers

High-power semiconductor laser systems based on 1.5 – 1.6 μm single-frequency distributed feedback (DFB) lasers with a sidewall Bragg diffraction grating are developed and their current – voltage, light – current, and spectral characteristics are experimentally studied. The characteristics of conventional lasers with a Fabry – Perot cavity and DFB lasers fabricated from one and the same heterostructure are compared. At a pump current not exceeding 700 mA, a conventional laser with a cavity length of 1.6 mm and a mesa-stripe width of 3 μm emits a power no lower than 200 mW versus 150 mW of the DFB laser; both lasers are mounted in a housing 11 mm in diameter. The DFB laser mounted in a butterfly housing emits a power no lower than 100 mW at the exit of the single-mode cable at a pump current not exceeding 500 mA, which, at a 60 % coupling efficiency, corresponds to a power no lower than 165 mW; the side-mode suppression ratio in this case is no lower than 53 dB. It is shown that the wavelength deviation with changing pump current and temperature is almost an order of magnitude lower for the DFB laser than for the conventional laser. (paper)

36 MATERIALS SCIENCE↗
DOE OSTI2022

Hybrid time–frequency domain dual-probe coherent anti-Stokes Raman scattering for simultaneous temperature and pressure measurements in compressible flows via spectral fitting

We demonstrate a hybrid time–frequency spectroscopic method for simultaneous temperature/pressure measurements in nonreacting compressible flows with known gas composition. Hybrid femtosecond–picosecond, pure-rotational coherent anti-Stokes Raman scattering (CARS), with two independent, time-delayed probe pulses, is deployed for single-laser-shot measurements of temperature and pressure profiles along an ∼ <#comment/> 5 -mm line. The theory of dual-probe CARS is presented, along with a discussion of the iterative fitting of experimental spectra. Temperature is obtained from spectra acquired with an early, near-collision-free probe time delay ( τ <#comment/> 1 = 0 p s ) and pressure from spectra obtained at probe delays of τ <#comment/> 2 = 150 − <#comment/> 1000 p s , where collisions significantly impact the spectral profile. Unique solutions for temperature and pressure are obtained by iteratively fitting the two spectra to account for small collisional effects observed for the near zero probe delay spectrum. A dual-probe pure-rotational CARS system, in a 1D line-imaging configuration, is developed to demonstrate effectively the simultaneous temperature and pressure profiles recorded along the axial centerline of a highly underexpanded jet. The underexpanded air jet permits evaluation of this hybrid time–frequency domain approach for temperature and pressure measurements across a wide range of low-temperature–low-pressure conditions of interest in supersonic ground-test facilities. Single-laser-shot measurement precisions in both quantities and pressure measurement accuracy are systematically evaluated in the quiet zone upstream of the Mach disk. Precise thermometry approaching 1%−2% is observed in regions of high CARS signal-to-noise ratios. Pressure measurements are optimized at probe time delays where the ratio of the late probe delay to the Raman lifetime exceeds four ( τ <#comment/> 2 / τ <#comment/> R > <#comment/> 4 ). The impact of low-temperature Raman linewidths on CARS pressure measurements is evaluated, and comparisons of CARS pressures obtained with our recent low-temperature pure-rotational Raman linewidth data and extrapolated high-temperature Q -branch linewidths are presented. Considering all measurements with τ <#comment/> 2 / τ <#comment/> R ≥ <#comment/> 4.0 , measured pressures were on average 7.9% of the computed isentropic values with average shot-to-shot deviations representing a combination of instrument noise and fluid fluctuations of 5.0%.

Retter, Jonathan E.↗
DOE OSTI2022

Modelling the Alfvén eigenmode induced fast-ion flow measured by an imaging neutral particle analyzer

An imaging neutral particle analyzer (INPA) provides energy and radially resolved measurements of the confined fast-ion population ranging from the high-field side to the edge on the midplane of the DIII-D tokamak. In recent experiments, it was used to diagnose fast-ion flow in the INPA-interrogated phase-space driven by multiple, marginally unstable Alfvén eigenmodes (AEs). Here, the key features of this measured fast-ion flow are: (I) a fast-ion flow from q min and the injection energy (81 keV) towards lower energies and plasma periphery.(II) A flow from the same location towards higher energies and the plasma core, (III) a phase-space 'hole' at the injected energy and plasma core and (IV) a pile-up at the plasma core at lower energies (~60 keV). Ad hoc energetic particle diffusivity modelling of TRANSP significantly deviates from the observation. Comparably, a reduced modelling, i.e. a combination of NOVA-K and ASCOT5 code with the measured mode structure and amplitude, generally reproduce some key features of the observed phase-space flow, but largely failed to interpret fast ion depletion near the plasma axis. At last, self-consistent, first-principle multi-phase hybrid simulations that include realistic neutral beam injection and collisions are able to reproduce most features of the time-resolved phase-space flow. During consecutive hybrid phases, an RSAE consistent with the experiment grows and saturates, redistributing the injected fast ions. The resulting synthetic INPA images are in good agreement with the measurement near the injection energy. The simulations track the fast-ion redistribution within the INPA range, confirming that the measured fast-ion flow follows streamlines defined by the intersection of phase-space surfaces of constant magnetic moment μ and constant E' = nE + ωP φ , where n and ω are the instability toroidal mode number and frequency, and E and P φ the ion energy and toroidal canonical momentum. Nonperturbative effects are required to reproduce the depletion of fast ions near the magnetic axis at the injection energy.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Design and commissioning of an e-beam irradiation beamline at the Upgraded Injector Test Facility at Jefferson Lab

We report the Upgraded Injector Test Facility (UITF) at Jefferson Lab is a continuous-wave superconducting linear accelerator capable of providing an electron beam with energy up to 10 MeV. A beamline for electron-beam irradiation has been designed, installed and successfully commissioned at this facility, aimed at the degradation study of 1,4-dioxane and per- and polyfluoroalkyl substances (PFAS) in wastewater treatment. A solenoid with a peak axial magnetic field of up to 0.28 T and a set of raster coils were used to obtain a Gaussian beam profile with a transverse standard deviation of ~ 15.0 mm at the target location. Monte-Carlo simulations using FLUKA were carried out to calculate the total absorbed dose and the dose distribution in the sample volume inside the target cell. The simulations were benchmarked experimentally by dosimetry mapping using optichromic dosimeters. The results of the irradiation experiments showed a ~ 95% reduction of 1,4-dioxane in ultra-pure water for a dose of 1 kGy, demonstrating the potential of electron-beam irradiation towards addressing growing challenges in environmental remediation.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Comparison of fiber-optic distributed temperature sensing and high-sensitivity sensor spatial surveying of stream temperature

Measuring surface water temperature spatial variability is needed to estimate the interaction between surface water and groundwater, evaluate fish habitat and thermal inertia, and to estimate streamflow frequency and duration. Fiber optic distributed temperature sensing (FO-DTS) has been used in rivers and lakes, providing high-resolution and sensitive temperature monitoring over large temporal and spatial scales. However, in streams with cobbly or bedrock-lined streambeds and variable bathymetry, use of FO-DTS to measure temperature close to the surface water and groundwater interface can be challenging if even feasible. FO-DTS can also be costly, involve difficult installations, and require an advanced understanding of the technology, calibration, and data processing. In this study, we compared FO-DTS stream temperature survey results to an alternative temperature survey method employing a towed transect of high-resolution temperature loggers spaced at 1-m and transported in the stream along the study reach, to measure the spatial distribution of stream-water temperature in East Fork Poplar Creek near Oak Ridge, Tennessee, USA. We assessed the applicability and limitations of the two methods, and quantitatively compared in-situ temperature survey results measured simultaneously with each method. Regression results showed strong temporal and spatial correlation between the two methods. Differences were only elevated near the stream banks in areas that were coincident with correlation slope deviations from unity, which was attributed to shallower water and lower data density. Kriging standard errors were also low at channel center with minor increases near the stream banks. Furthermore, the results suggested that the array of the individual temperature sensors can provide a practical alternative to FO-DTS for thermal characterization of surface water, providing slightly lower spatial and temporal resolution, but with higher accuracy of temperature measurement, with greater simplicity, and with a broader range of conditions where it may be applied.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

The first high-redshift cavity power measurements of cool-core galaxy clusters with the International LOFAR Telescope

Radio-mode feedback associated with the active galactic nuclei (AGNs) at the cores of galaxy clusters injects a large amount of energy into the intracluster medium (ICM), offsetting radiative losses through X-ray emission. This mechanism prevents the ICM from rapidly cooling down and fueling extreme starburst activity as it accretes onto the central galaxies, and it is therefore a key ingredient in the evolution of galaxy clusters. However, the influence and mode of feedback at high redshifts (z ∼ 1) remains largely unknown. Low-frequency sub-arcsecond-resolution radio observations taken with the International LOFAR Telescope have demonstrated their ability to assist X-ray observations with constraining the energy output from the AGNs (or “cavity power”) in galaxy clusters, thereby enabling research at higher redshifts than before. In this pilot project, we tested this hybrid method on a high-redshift (0.6 < z < 1.3) sample of 13 galaxy clusters for the first time with the aim of verifying the performance of this method at these redshifts and providing the first estimates of the cavity power associated with the central AGN for a sample of distant clusters. We were able to detect clear radio lobes in three out of 13 galaxy clusters at redshifts of 0.7 < z < 0.9, and we used these detections in combination with ICM pressures surrounding the radio lobes obtained from standard profiles to calculate the corresponding cavity powers of the AGNs. Combining our results with the literature, the current data appear to suggest that the average cavity power peaked at a redshift ofz ∼ 0.4 and slowly decreases toward higher redshifts. However, we require more and tighter constraints on the cavity volume and a better understanding of our observational systematics to confirm any deviation of the cavity power trend from a constant level.

Astronomy & Astrophysics↗
DOE OSTI2025

Observed and Imputed Volumetric Soil Water Content Timeseries for the New Mexico Elevation Gradient

Reliable soil water content (SWC) data are essential for understanding dryland ecosystem dynamics, but high-frequency SWC sensors often fail, creating gaps in critical datasets. To address this, we developed a Bayesian mixture model that imputes missing SWC using both linear interpolation and an ecosystem water balance model (SOILWAT2), tested across six AmeriFlux eddy covariance tower sites in the New Mexico Elevation Gradient, demonstrating its effectiveness in reconstructing SWC patterns while providing insights into the factors driving SWC variability. Daily volumetric soil water content (SWC) data are provided as csv-formatted spreadsheets for the six AmeriFlux sites (US-Seg, US-Ses, US-Wjs, US-Mpi, US-Vcp, and US-Vcs). For each site there is an observed SWC file (site_SWC_gapfill.csv) and a file that contains imputed SWC (imputed_SWC_site.csv). The observed SWC files contain temperature corrected sensor values, tower precipitation data, as well as outputs from SOILWAT2 simulations that were used to impute SWC. The imputed files contain the original observed SWC values and the imputed missing SWC values. When SWC was missing from the original data, the missing value was imputed based on the Bayesian imputation mixture model. The posterior mean of all imputed values is reported as "mean_X". When the observed SWC was NOT missing, mean_X = observed SWC value (original data). The standard deviation, 2.5th percentile and the 97.5th percentile for the imputed values are also reported in the imputed files. There are readme text files for each file type explaining the contents of each column.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Machine Learning Driven Contouring of High-Frequency Four-Dimensional Cardiac Ultrasound Data

Automatic boundary detection of 4D ultrasound (4DUS) cardiac data is a promising yet challenging application at the intersection of machine learning and medicine. Using recently developed murine 4DUS cardiac imaging data, we demonstrate here a set of three machine learning models that predict left ventricular wall kinematics along both the endo- and epi-cardial boundaries. Each model is fundamentally built on three key features: (1) the projection of raw US data to a lower dimensional subspace, (2) a smoothing spline basis across time, and (3) a strategic parameterization of the left ventricular boundaries. Model 1 is constructed such that boundary predictions are based on individual short-axis images, regardless of their relative position in the ventricle. Model 2 simultaneously incorporates parallel short-axis image data into their predictions. Model 3 builds on the multi-slice approach of model 2, but assists predictions with a single ground-truth position at end-diastole. To assess the performance of each model, Monte Carlo cross validation was used to assess the performance of each model on unseen data. For predicting the radial distance of the endocardium, models 1, 2, and 3 yielded average R2 values of 0.41, 0.49, and 0.71, respectively. Monte Carlo simulations of the endocardial wall showed significantly closer predictions when using model 2 versus model 1 at a rate of 48.67%, and using model 3 versus model 2 at a rate of 83.50%. These finding suggest that a machine learning approach where multi-slice data are simultaneously used as input and predictions are aided by a single user input yields the most robust performance. Subsequently, we explore the how metrics of cardiac kinematics compare between ground-truth contours and predicted boundaries. We observed negligible deviations from ground-truth when using predicted boundaries alone, except in the case of early diastolic strain rate, providing confidence for the use of such machine learning models for rapid and reliable assessments of murine cardiac function. To our knowledge, this is the first application of machine learning to murine left ventricular 4DUS data. Future work will be needed to strengthen both model performance and applicability to different cardiac disease models.

4D ultrasound↗
DOE OSTI2026

SPT-3G D1: Quadratic-Estimator CMB Lensing Reconstruction and Cosmology

We present a map of the cosmic microwave background (CMB) lensing potential reconstructed from observations taken during the 2019 and 2020 seasons with the third-generation camera on the South Pole Telescope (SPT), covering the $1500\,{\rm deg}^{2}$ SPT-3G Main field, referred to as the SPT-3G D1 dataset. From the multi-frequency temperature and polarization data, we reconstruct the CMB lensing field using a quadratic estimator that jointly accounts for the $T$, $E$, and $B$ fields and their covariance. The resulting lensing map is dominated by polarization information for $L \lesssim 600$ and provides the highest signal-to-noise measurement per mode reported to date. With nuisance parameters fixed to their best-fit values, we measure a lensing amplitude consistent with unity at $2\%$ precision relative to the $Λ$CDM model that best fits the combined Planck, ACT DR6, and SPT-3G D1 $TT/TE/EE$ likelihoods (${\rm CMB}_{\rm SPA}$). We further measure the structure-growth parameter $σ_{8}Ω_{\rm m}^{0.25}$ to be $0.6046\pm0.0096$ from the SPT-3G D1 lensing spectrum alone and $0.6020\pm0.0084$ when combined with ACT DR6 and Planck PR4 CMB lensing. By further combining this with ${\rm CMB}_{\rm SPA}$ and the latest DESI DR2 BAO data, we obtain $\sum m_ν < 0.072\,\mathrm{eV}$ (95% C.L.) when allowing the neutrino mass to vary within $Λ$CDM. Compared with previous work, the better agreement of our measurement with DESI DR2 BAO yields both this relaxed upper bound and reduced ($\mathord{\sim}2σ$) preferences for nonzero spatial curvature and for deviations of $(w_0,w_a)$ from the $Λ$CDM expectation. When we combine CMB lensing with the DES Y3 3$\times$2pt analysis, we obtain $S_{8}=0.811\pm0.011$, corresponding to a $1.4\%$ constraint on the late-time clustering amplitude. This precision is competitive with that obtained from the primary CMB within $Λ$CDM.

Omori, Y. [Chicago U., Astron. Astrophys. Ctr.; Ch↗
DOE OSTI2021

Assessment of Model Hub Height Wind Speed Performance Using DOE Lidar Buoy Data

As the offshore wind industry continues to gain momentum both in the U.S. and globally, reanalysis products remain essential tools for the lifecycle of a wind farm. From project siting and production estimates to determining construction and maintenance windows, reanalysis products play an important role. These regional and global long-term models also serve as inputs to higher resolution models. With such wide-ranging impacts on the offshore wind industry, the need for validation of reanalysis products is strong, particularly at typical turbine hub heights. Pacific Northwest National Laboratory (PNNL) operates two AXYS WindSentinelTM buoys for the U.S. Department of Energy (DOE) in order to collect meteorological and oceanographic data, including hub height wind speed, in areas of interest for offshore wind development. This work uses DOE buoy observations off the coasts of New Jersey and Virginia to evaluate the performance of Modern Era Retrospective Analysis for Research and Applications-2 (MERRA-2), the North American Regional Reanalysis (NARR), the European Center for Medium-Range Weather Forecasts (ECMWF) Reanalysis 5th generation (ERA5), and the National Oceanic and Atmospheric Administration (NOAA) assimilation system Rapid Refresh (RAP). Biases and degrees of correspondence are determined for each reanalysis product in order to provide insights on the performance and uncertainty for long-term wind resource characterization. With the baseline metrics determined, this work proceeds with an investigation into the sources of large deviations between the modeled and observed hub height wind speeds during the East Coast lidar buoy deployments. Consistent sources of reanalysis model error include stably stratified flow conditions, high wind shear, flow parallel to the coastline, and tropical and winter storms. For the near shore New Jersey location, offshore winds (i.e. blowing from land to water) tend to be associated with model overestimation of observed hub height wind speed, while winds parallel to the coastline are correlated with model underestimation of wind speed. Similarly, near the Virginia buoy, during southerly winds (parallel to the coastline) models underestimate the observed wind speed due to coastal upwelling. Reanalysis model wind speeds underestimate the hub height winds with increasing stable atmospheric stratification. Reanalysis model biases are seen when the observed wind speeds approach or exceed typical turbine cut-out speeds (around 20 m s-1). Large model errors during winter and tropical storm events, high wind speed events, and ramp events are often the result of wind speed timing and magnitude offsets. Overall, ERA5 provides the most successful representation of observed offshore hub height wind speeds at the U.S. East Coast buoy locations and is therefore best suited as an input boundary condition for model case studies. ERA5 performs well for a variety of atmospheric phenomena, including storms and sea breezes, however RAP, the next most successful reanalysis model, performs best in capturing the frequency of ramp events.

17 WIND ENERGY↗
DOE OSTI2023

Uniqueness of relaxation times determined by dielectric spectroscopy

Dielectric spectroscopy is extremely powerful to study molecular dynamics, because of the very broad frequency range. Often multiple processes superimpose resulting in spectra that expand over several orders of magnitude, with some of the contributions partially hidden. For illustration, we selected two examples, (i) normal mode of high molar mass polymers partially hidden by conductivity and polarization and (ii) contour length fluctuations partially hidden by reptation using the well-studied polyisoprene melts as example. The intuitive approach to describe experimental spectra and to extract relaxation times is the addition of two or more model functions. Here, we use the empirical Havriliak-Negami function to illustrate the ambiguity of the extracted relaxation time, despite an excellent agreement of the fit with experimental data. We show that there are an infinite number of solutions for which a perfect description of experimental data can be achieved. However, a simple mathematical relationship indicates uniqueness of the pairs of the relaxation strength and relaxation time. Sacrificing the absolute value of the relaxation time enables to find the temperature dependence of the parameters with a high accuracy. For the specific cases studied here, the time temperature superposition (TTS) is very useful to confirm the principle. However, the derivation is not based on a specific temperature dependence, hence, independent from the TTS. We compare new and traditional approaches and find the same trend for the temperature dependence. The important advantage of the new technology is the knowledge of the accuracy of the relaxation times. Relaxation times determined from data for which the peak is clearly visible are the same within the experimental accuracy for traditional and new technology. However, for data where a dominant process hides the peak, substantial deviations can be observed. Finally, we conclude that the new approach is particularly helpful for cases in which relaxation times need to be determined without having access to the associated peak position.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Statistical evaluation of microscale stress conditions leading to void nucleation in the weak shock regime

Here, we investigate the heterogeneity of the stress state driven by anisotropic deformation response at the single crystal level through five statistical volume element (SVE) calculations of polycrystalline BCC tantalum. This work focuses on grain boundaries as a prominent material defect type prone to void nucleation based upon experimental observations of predominantly intergranular void nucleation in this material. The SVEs are constructed to be statistically representative of larger volumes of material and are meshed such that mean and standard deviation of grain size and orientation information is reconstructed. The computational meshes feature hexahedral (brick) elements and smooth conformal grain boundaries where significant stress concentration is known to occur, a tail effect of interest in the extreme events process of dynamic ductile damage. An existing micromechanical crystallographic plasticity model shown to capture the single crystal behavior of BCC tantalum well is used to perform the polycrystal calculations. The model includes representation of the non-Schmid effect of non-planar screw dislocation kinetics in tantalum. A three-dimensional stress state time profile predicted by damage modeling of a flyer plate impact experiment is applied as boundary conditions to each SVE. Resulting grain boundary stress state statistics are strongly non-Gaussian. Significant structural evolution is observed within the compressive hold before unloading into tension in the stress profile. Strong angular dependence of grain boundary traction magnitude with shock direction is observed. Non-Schmid effects continue to suggest their influence on propensity of microstructural defect types to nucleate voids. A general void nucleation criterion is proposed using probability theory. The general framework is specified to polycrystalline BCC tantalum in the weak shock regime to include the SVE calculations and literature molecular dynamics calculations of grain boundary void nucleation strength. Probability density functions (PDFs) are used to describe the interaction between the local stress state heterogeneity and the distributed grain boundary void nucleation strength state. A causation entropy maximization procedure removes the requirement for ad hoc selection of a PDF functional form and provides a rigorous procedure for data-based PDF determination. The resulting physically informed PDF describes the spatial appearance frequency of nucleated voids as a function of applied macroscale pressure. Lower length scale physics are thus packaged in a precise and computationally efficient way to provide computational plasticity insight to macroscale dynamic ductile damage models.

36 MATERIALS SCIENCE↗