An ultra-wideband, high-power coaxial diagnostic for measurement of waveform directionality
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The goal of this project was to develop and validate two complementary, cost-effective remote sensing technologies to monitor avian fatalities at utility-scale solar facilities: fixed platform (Animal Activity Monitoring-AAM) and aerial-based (Uncrewed Aircraft Systems-UAS). This project used these features with machine learning to automate the detection of avian carcasses and nests at solar facilities.
This SAND report collects the results from the LDRD project “SHAZAM”, which aimed to push the limits of performance for self-healing, self-assembling power systems whose sectionalizing and load-control agents rely on local measurements only (i.e., only what they can measure at their own terminals, with no data sharing between agents). This work includes self-networking microgrids. The key objectives of this work were a) to demonstrate how high the performance of local-measurement-only self-assembling power systems can be; and b) to solve certain technical problems associated with such systems, such as their inability to prevent the accidental formation of closed loops and their tendency to thermally overload some conductors. “SHAZAM” investigators a) demonstrated that the performance of such systems can be surprisingly high, b) demonstrated that such systems are quite robust to all kinds of variations, and c) developed and demonstrated solutions to several key challenges associated with this type of system.
Accurately quantifying the energy use of artificial intelligence (AI) training is critical for infrastructure planning, carbon accounting, and sustainable data center operation, but few studies have directly measured the power consumption of production workloads on contemporary hardware. By combining empirical measurements from Brookhaven National Laboratory during AI training on 8-graphics-processing-unit H100 systems with open-source benchmarking data, we develop statistical models relating computational intensity to node-level power consumption. We measure the gap between manufacturer-rated thermal design power (TDP) and actual power demand during AI training. Our analysis reveals that even computationally intensive workloads operate at only 76% of the 10.2 kW TDP rating. Our architecture-specific model, calibrated to floating-point operations, predicts energy consumption with 11.4% mean absolute percentage error, significantly outperforming TDP-based approaches (27%–37% error). We identified distinct power signatures between transformer and convolutional neural network architectures, with transformers showing characteristic fluctuations that may impact grid stability. These results provide a measurement-grounded basis for improving AI training energy estimates, enabling more reliable infrastructure sizing, cost projections, and environmental impact assessments.
We demonstrate spin pumping driven by a strongly coupled magnon-photon system using a ferromagnet-coplanar superconducting resonator hybrid system at 1.4 K. Electrical readout via the inverse spin-Hall effect reveals characteristic coupling features, including mode splitting and linewidth broadening, demonstrating the electrical detection of strongly coupled microwave photons and magnons. The microwave magnon-photon coupling strength obtained by combined spin pumping and inverse spin-Hall effect measurements is compared to microwave transmission experiments. Here, microwave power-dependent measurements reveal a decrease in the coupling strength with increasing microwave power alongside the onset of nonlinearities of the superconducting resonator above a critical microwave power threshold.
Synchrophasor measurements are critical in providing wide-area situational awareness to power system operators. However, data artifacts may be introduced due to various issues such as loss of communication, loss of GPS signal, internal clock error, and vendor-specific implementation of phasor estimation algorithms. Tools designed to provide actionable insights from synchrophasor data, hence, must be designed to be robust to these data quality issues. In this work, two years of synchrophasor data sourced from multiple electric utilities in the United States were analyzed to identify examples of data quality problems. These examples were then labeled and published in the Grid Event Signature Library, a publicly available repository of power system measurements hosted by the Oak Ridge National Laboratory. This paper describes the data curation process, and illustrates two application use cases where the dataset can be valuable to the research community. In the first use case, a random forest classifier is trained to distinguish power system disturbance signatures from data anomalies introduced in synchrophasor measurements due to clock errors. The second use case studies the impact of data quality issues on an example synchrophasor application (specifically, event start time determination). The choice of data quality problems investigated is informed by the examples in the repository curated in this work.
ABSTRACT We present the one-dimensional Ly α forest power spectrum measurement using the first data provided by the Dark Energy Spectroscopic Instrument (DESI). The data sample comprises 26 330 quasar spectra, at redshift z > 2.1, contained in the DESI Early Data Release and the first 2 months of the main survey. We employ a Fast Fourier Transform (FFT) estimator and compare the resulting power spectrum to an alternative likelihood-based method in a companion paper. We investigate methodological and instrumental contaminants associated with the new DESI instrument, applying techniques similar to previous Sloan Digital Sky Survey (SDSS) measurements. We use synthetic data based on lognormal approximation to validate and correct our measurement. We compare our resulting power spectrum with previous SDSS and high-resolution measurements. With relatively small number statistics, we successfully perform the FFT measurement, which is already competitive in terms of the scale range. At the end of the DESI survey, we expect a five times larger Ly α forest sample than SDSS, providing an unprecedented precise one-dimensional power spectrum measurement.
We present the temperature and polarization angular power spectra of the CMB measured by the Atacama Cosmology Telescope (ACT) from 5400 deg2 of the 2013–2016 survey, which covers >15000 deg2 at 98 and 150 GHz. For this analysis we adopt a blinding strategy to help avoid confirmation bias and, related to this, show numerous checks for systematic error done before unblinding. Using the likelihood for the cosmological analysis we constrain secondary sources of anisotropy and foreground emission, and derive a “CMB-only” spectrum that extends to ℓ=4000. At large angular scales, foreground emission at 150 GHz is ∼1% of TT and EE within our selected regions and consistent with that found by Planck. Using the same likelihood, we obtain the cosmological parameters for ΛCDM for the ACT data alone with a prior on the optical depth of τ=0.065±0.015. ΛCDM is a good fit. The best-fit model has a reduced χ2 of 1.07 (PTE=0.07) with H0=67.9±1.5 km/s/Mpc. We show that the lensing BB signal is consistent with ΛCDM and limit the celestial EB polarization angle to ψP =−0.07ˆ±0.09ˆ. We directly cross correlate ACT with Planck and observe generally good agreement but with some discrepancies in TE. All data on which this analysis is based will be publicly released.
We report a B-mode power spectrum measurement from the cosmic microwave background (CMB) polarization anisotropy observations made using the SPTpol instrument on the South Pole Telescope. This work uses 500 deg 2 of SPTpol data, a five-fold increase over the last SPTpol B-mode release. As a result, the bandpower uncertainties have been reduced by more than a factor of two, and the measurement extends to lower multipoles: 52 < ` < 2301. Data from both 95 and 150 GHz are used, allowing for three cross-spectra: 95 GHz x 95 GHz, 95 GHz x 150 GHz, and 150 GHz x 150 GHz. B-mode power is detected at very high significance; we find P(BB < 0) = 5.8 × 10 -71 , corresponding to a 18.1 σ detection of power. With a prior on the galactic dust from Planck, WMAP and BICEP2/Keck observations, the SPTpol B-mode data can be used to set an upper limit on the tensor-to-scalar ratio, r < 0.44 at 95% confidence (the expected 1 σ constraint on r given the measurement uncertainties is 0.22). We find the measured B-mode power is consistent with the Planck best-fit ΛCDM model predictions. Scaling the predicted lensing B-mode power in this model by a factor A lens , the data prefer A lens = 1.17 ± 0.13. These data are currently the most precise measurements of B-mode power at ℓ > 320.
ReNCAT is a software application that suggests microgrid portfolios that reduce the impact of large-scale disruptions to power, as measured by the Social Burden Metric. ReNCAT examines a power distribution network to identify regions that can be isolated into microgrids that enable critical services to be provided even if the remainder of the study area is left without power. ReNCAT operates on a simplified representation of the power grid, one that aggregates and approximates loads and conductors. Microgrids are formed within the power network by setting switch states to split or join portions of the grid. ReNCAT identifies candidate microgrid portfolios with varying tradeoffs between cost and service availability.
Inter-area oscillation modes usually fall within the same frequency range of 0.1 to 1.0 Hz; thus, power oscillation damping (POD) control methods should avoid unnecessary excitation of weakly damped modes. This paper presents a decoupled control strategy to damp inter-area oscillations in the power grid. Pure oscillation mode signals are extracted from wide-area measurements and used as feedback input for POD actuators such as power system stabilizers or high-voltage direct current transmission. The decoupled control strategy is able to increase the damping of the concerned oscillation modes without deteriorating others. This proposed strategy could be implemented independently, or serve as a complement and work along with conventional POD controllers to damp concerned inter-area modes. The proposed method has been tested on a modied MinniWECC system. Extensive results indicate that inter-area oscillations can be successfully and precisely damped using the proposed decoupled strategy.
We present precision measurements of the bias parameters of the one-loop power spectrum model of the Lyman- α (Ly- α ) forest, derived within the effective field theory (EFT) of large-scale structure. We fit our model to the three-dimensional flux power spectrum measured from the ACCEL 2 hydrodynamic simulations. The EFT model fits the data with an accuracy of below 2% up to k = 2 h Mpc − 1 . Further, we analytically derive how nonlinearities in the three-dimensional clustering of the Ly- α forest introduce biases in measurements of the baryon acoustic oscillations (BAOs) scaling parameters in radial and transverse directions. From our EFT parameter measurements, we obtain a theoretical error budget of Δ α ∥ = − 0.2 % ( Δ α ⊥ = − 0.3 % ) for the radial (transverse) parameters at redshift z = 2.0 . This corresponds to a shift of − 0.3 % (0.1%) for the isotropic (anisotropic) distance measurements. We provide an estimate for the shift of the BAO peak for Ly- α -quasar cross-correlation measurements assuming analytical and simulation-based scaling relations for the nonlinear quasar bias parameters resulting in a shift of − 0.2 % ( − 0.1 % ) for the radial (transverse) dilation parameters, respectively. This analysis emphasizes the robustness of Ly- α forest BAO measurements to the theory modeling. We provide informative priors and an error budget for measuring the BAO feature—a key science driver of the currently observing Dark Energy Spectroscopic Instrument (DESI). Our work paves the way for full-shape cosmological analyses of Ly- α forest data from DESI and upcoming surveys such as the Prime Focus Spectrograph, WEAVE-QSO, and 4MOST. Published by the American Physical Society 2025
Composite Power System Reliability is defined as the computational procedure that quantifies the probability that the power system will perform the function of delivering electric power to customers adequately, on a continuous basis and with an acceptable quality. This definition leaves many details undefined and exemplifies the ambiguity in reliability analysis. The increasing deployment of wind and PV creates additional uncertainties that make reliability analysis a rather complex issue. Because of increased uncertainty the need for composite reliability analysis and utilization of results in power system planning is critical. New approaches are emerging for dealing with these problems from the operational point of view, including demand response programs, tapping on customer and distributed resource flexibility and new control approaches. The key question to be addressed is: how the new operational paradigms affect composite power system reliability. Here, this paper presents the ongoing work of the IEEE Composite System Reliability Task Force of the IEEE PES Reliability, Risk, Probability Application (RRPA) Subcommittee.
We examine the question of how to obtain bounding power (or current) for two similar loads with an unknown source circuit, but measurements of power (or current) for one load as well as models and measurements of both load impedances.
Operational lifetime extensions of existing research reactors have emphasized the need for refurbishment, replacements, and upgrades to supporting equipment and instrumentation. The Advanced Test Reactor (ATR) at Idaho National Laboratory (INL), which entered service in 1967, has recently completed the sixth core internals change-out and has scheduled operations until at least 2040. Reactor maintenance and operational risk management is critically important in the research reactor community, however supporting measurement systems sometimes get overlooked when maintenance is planned. The Fission Wire Measurement System (FWMS) is a custom measurement system designed in the 1960s to measure the beta-particle activity of irradiated uranium-aluminum fission wires. This measurement is conducted to determine the fission rate profile of the Advanced Reactor Test Critical (ATR-C) facility. The ATR-C is an open-pool, low-power test reactor that was purpose driven to resemble ATR and is used to qualify experiment configurations and verify core models prior to full-power experiment irradiations in ATR. A power distribution measurement in ATR-C uses uranium-aluminum wires that are distributed throughout the ATR-C core to validate simulation and modeling results. These measurements require 340 to 1500 wires to be irradiated and measured within a 12-hour window. The activity of the wires is measured in the required time with the FWMS, which was put into service in 1965 at the Radiation Measurements Laboratory (RML). The system consists of 4 measurement channels and one reference channel, each with a 2-pi proportional gas flow detector and the measurement channels each have an automated sample changer. This legacy system is crucial to the continued operations of ATR and has undergone some minor hardware upgrades since 1965, however the system presently relies on custom control boards, custom gas ion chambers, analog amplifiers/discriminators, and a user interface (UI) for the system written in outdated code. Much of the equipment and software is custom with no commercial replacements or support and limited documentation. The existing control software requires an operating system that is no longer supported, creating more vulnerabilities to continued operations. A project is underway with a third-party vendor to design, build, and document a new control and data acquisition system (CDAS) for the FWMS. The new upgrade will replace the control system, computer, UI, sample changer motors, and main power supply while maintaining the interface with existing detector hardware. The upgraded system will be operated in parallel with the current hardware and software to conduct validation testing. This equipment upgrade demonstrates the commitment at ATR to ensuring successful operations and potential future research reactors at INL.
We compare various diagnostics characterizing an ASDEX Upgrade upper single-null discharge to EMC3-EIRENE simulations now including volumetric recombination and main chamber plasma-wall interaction but not yet drifts. The discharge is in a small-ELM regime and is approaching detachment due to a density ramp and nitrogen seeding. Time/ELM averaged upstream density, electron and ion temperature measurements as well as downstream ion saturation current, electron temperature and power flux measurements match the simulation within the error bars before and after reaching detachment, qualifying the code for this regime. Although the Ion Cyclotron Resonance Heating (ICRH) antenna limiters are 35 mm away from the separatrix, i.e. ten times the typical near-SOL power fall-off length $\lambda^{near}_q\ =\ $3.8 mm, they receive power fluxes of several hundreds of kW exceeding the ones to the outer target in the detached phase and strongly contribute to the particle fueling. This is explained by a substantially larger far-SOL power fall-off length $\lambda^{far}_q\ =\ $25 mm possibly caused by the small ELMs in the detached phase and the occurrence of a density shoulder.
We report on the High Temperature Superconductor (HTS) based prototype accelerator magnet capable to operate at 12 T/s B-field ramping rate with a very low supporting cryogenic cooling power thus indicating a feasibility of its application in the accelerator requiring high repetition rate and high average beam power. The magnet is designed to simultaneously accelerate two particle beams in the separate beam gaps energized by a single conductor. The design, construction and the power test of the prototype fast-cycling HTS based accelerator magnet is presented while the more detailed description and power test data analysis s given in [1]. As example, the measured cryogenic power loss limit is discussed in terms of the feasibility of application of such a magnet for the construction of the 8 GeV dual proton beam Booster.
The Virtual Environment for Reactor Applications (VERA) is being developed by the Consortium for the Advanced Simulation of Light Water Reactors (CASL). Here, VERA is used to perform the Benchmark for Evaluation and Validation of Reactor Simulations (BEAVRS), which provides two cycles’ worth of operating power history, along with a full, detailed description of the geometry, and measured data. Cycle 1 and 2 are simulated with VERA and the results are compared to the measured zero power physics tests, critical boron concentration, and flux maps.