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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Evaluating Methods for Measuring Grid Frequency in Low-Inertia Power Systems: Preprint

Accurate measurement of grid frequency is a critical component of reliable grid control. Traditionally, methods such as phase locked loops (PLLs) and discrete Fourier transforms (DFTs) have been used in inverters and phasor measurement units (PMUs) to measure frequency. However, as the percentage of inverter-based resources (IBRs) such as solar and wind has increased, these conventional frequency measurement methods are proving unable to guarantee reliable control in some cases. One challenge is measuring frequency during transient events, where there is a disruption in the steady state sinusoidal voltage. During these events, the underlying frequency of the grid may barely change, but measurement methods report a large spike in frequency due to the disrupted waveform. New methods must balance between suppressing spikes in frequency during faults, and providing fast, accurate, measurements in all other grid operation conditions, especially during events with high rate-of-change-of frequency (ROCOF), which are more prevalent in high-IBR power systems. This paper first surveys frequency measurement methods that have been proposed to reduce measurement errors during transient events. Then, both conventional and more novel frequency measurement methods are tested against an IEEE standard and industry recommendations, and their performance is evaluated for events simulated in PSCAD. Results quantify the trade-offs in performance during different grid conditions and lead to suggestions for the most appropriate frequency and ROCOF measurement methods for low inertia grids.

frequency↗
DOE OSTI2020

Cost Effective 6.5% Silicon Steel Laminate for Electric Machines

Iowa State University teamed with United Technologies Research Center and the University of Delaware and demonstrated a high switching frequency non-rare earth permanent magnet motor. A prototype motor with 400 Hz switching frequency, dummy MnBi permanent magnet with 8 MGOe energy density, and 6.5%Si steel as the laminate materials was designed, built, and tested. The performance of the prototype met the expectations showing a higher frequency motor enabled by 6.5%Si steel is a viable approach to meet DOE 2022 cost and performance targets for electric vehicle drive. Adoption of 6.5%Si steel will result in 3% improvement in energy conversion efficiency of the soft magnetic materials. In addition, the ability to use non-rare earth magnet for high power density application effectively mitigate the risk of EV traction motor from the rising rare earth price.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Si-Cr-Al-Mn Alloy for High Specific Resistivity

Laboratory material produced in budget period one met the target resistivity, mechanical and magnetic requirements for the Go/No-Go decision to move to industrial trials. The chosen chemistry settled on a high Cr strategy, with moderate Mn and Al additions, providing a good comprise on core loss and induction with minimal impact on mechanical properties, important to successful downstream processing. Industrial trials began in budget period two with the chosen chemistry, referred to as Alloy X. Difficulties occurred during initial hot rolling trials. Reheating the material using the standard NOES practice caused slab cracking from high thermal gradients in areas exposed to the roof burners, this was solved using a modified reheat practice. High Cr caused poor dynamic recrystallization during hot rolling, which was solved using a modified hot rolling practice. The high Cr content of the steel also caused poor decarburization during final annealing, which necessitated lowering the melt carbon aim for the final heat, together with a modified decarburization practice. Steel was finished to final thicknesses of 0.20 – 0.50 mm and evaluated for magnetic and mechanical properties. Although the target core loss for the 0.25 and 0.35 mm material was not achieved, significant reductions in high frequency core loss were measured, compared to equivalent commercially available material. Alloy X at 0.35 mm showed a 26 % and 23 % improvement at 400 HZ and 1000 Hz respectively, over Cliffs’ M-19 (0.35 mm) commercially available NOES. At 0.25 mm, Alloy X showed a 23 % and a 26 % improvement at 400 HZ and 1000 Hz respectively, over Cliffs’ HF-10 (0.25 mm) commercially available NOES. The 0.25 mm product was chosen for motor efficiency evaluation. ORNL collaborated with Cleveland-Cliffs (CC) to build, assemble, and test two 5HP motors: a baseline motor with M19 steel and a motor made with high efficiency steel (Alloy X) developed for the project. Overall, results were as expected with comparable performance at low speeds, and with more than 8% efficiency improvement for high speeds. Increased motor steel efficiency at high frequencies not only results in direct efficiency improvements but can yield reductions in motor size and cost by facilitating higher operation speeds, or by increasing the number of poles in the machine. This allows the production of more power-dense motors which are sometimes avoided with conventional material due to increased core losses. The material developed on this project provides more viable options for achieving improved motor efficiency or reduced motor size and cost.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Evaluating methods to reduce duration of near-threshold fatigue crack growth rate measurements for low-alloy steels in hydrogen gas

Measurement of the near-threshold fatigue crack growth rate (da/dN) vs. stress-intensity factor range (∆K) relationship in hydrogen gas is essential for maximizing the calculated design fatigue life of high-pressure hydrogen storage vessels. However, such measurements are rarely performed, since the low cyclic loading frequencies applied in standard practice lead to prohibitively protracted test durations. The objective of this study was to demonstrate two means for reducing test durations when measuring near-threshold da/dN vs. ΔK relationships under decreasing ΔK for low-alloy pressure vessel steels in hydrogen gas: 1) imposing steeper K-gradients relative to the recommended limits in standards such as ASTM E647, and 2) increasing cyclic loading frequency relative to typical values applied during fatigue crack growth testing of low-alloy steels in hydrogen gas. Recognizing that steeper K-gradients could amplify loading-history effects, test methods employing this approach were designed to mitigate such effects by either maintaining constant K max or gradually increasing the K-gradient as the threshold was approached. Although the varying K-gradient method was vulnerable to loading-history effects in the form of plasticity-induced crack closure, particularly at lower stress ratio (R) and higher starting K max values, these effects could be compensated by applying the adjusted compliance ratio (ACR) method. Here, it was demonstrated that steeper K-gradients in concert with increased cyclic loading frequency reduced the duration of near-threshold fatigue crack growth tests in hydrogen gas by more than 99% relative to standard practices.

Fatigue threshold↗
DOE OSTI2024

Numerical Investigation of Observational Flux Partitioning Methods for Water Vapor and Carbon Dioxide

Abstract While yearly budgets of CO 2 flux (F c ) and evapotranspiration (ET) above vegetation can be readily obtained from eddy‐covariance measurements, the separate quantification of their soil (respiration and evaporation) and canopy (photosynthesis and transpiration) components remains an elusive yet critical research objective. In this work, we investigate four methods to partition observed total fluxes into soil and plant sources: two new and two existing approaches that are based solely on analysis of conventional high frequency eddy‐covariance (EC) data. The physical validity of the assumptions of all four methods, as well as their performance under different scenarios, are tested with the aid of large‐eddy simulations, which are used to replicate eddy‐covariance field experiments. Our results indicate that canopies with large, exposed soil patches increase the mixing and correlation of scalars; this negatively impacts the performance of the partitioning methods, all of which require some degree of uncorrelatedness between CO 2 and water vapor. In addition, best performances for all partitioning methods were found when all four flux components are non‐negligible, and measurements are collected close to the canopy top. Methods relying on the water‐use efficiency (W) perform better whenWis known a priori, but are shown to be very sensitive to uncertainties in this input variable especially when canopy fluxes dominate. We conclude by showing how the correlation coefficient between CO 2 and water vapor can be used to infer the reliability of differentWparameterizations.

Environmental Sciences & Ecology↗
DOE OSTI2023

Machine learning-based inversion for acoustic impedance with large synthetic training data: Workflow and data characterization

Where wells are sparse or training data are difficult to label with high-quality wireline-derived impedance logs, machine learning (ML)-based inversion of acoustic impedance typically depends on small training data sets, leading to biased prediction. We have advanced a novel workflow that applies large synthetic seismic training data to reduce facies-related bias. Using a geologically realistic model as the truth model, we randomly select sparse seed wells to perform sequential Gaussian simulation (SGS) for impedance models of the same geometry and simulate facies variability. We implement random forest regression on 30 features extracted from the synthetic volume. We observe that more seed wells tend to reduce facies-induced bias by sampling more types of facies, resulting in a better prediction. We then focus on the responses of SGS models to facies changes, the number of seed wells necessary for a useful synthetic model, and how much a synthetic model can help ML-based inversion. Here, we observe that the SGS synthetic training model outperforms well-direct training in general. For modeled clastic shore-zone systems in Miocene Gulf of Mexico, two or more seed wells are necessary for a significant reduction of root-mean-square error and outliners, and improvement of facies imaging. In a field-data test, we apply a similar workflow to quantitatively predict acoustic impedance, which is then converted to a sand-volume map at a high-frequency sequence (10–100 m), revealing detailed facies and sandstone patterns. Such results are valuable in many geologic and engineering applications, such as hydrocarbon and CO 2 reservoir prospecting, reserve estimation, simulation, etc.

3D seismic↗
DOE OSTI2021

Pipeline Monitoring Using Highly Sensitive Vibration Sensor Based on Fiber Ring Cavity Laser

A vibration fiber sensor based on a fiber ring cavity laser and an interferometer based single-mode-multimode-single-mode (SMS) fiber structure is proposed and experimentally demonstrated. The SMS fiber sensor is positioned within the laser cavity, where the ring laser lasing wavelength can be swept to an optimized wavelength using a simple fiber loop design. To obtain a better signal-to-noise ratio, the ring laser lasing wavelength is tuned to the maximum gain region biasing point of the SMS transmission spectrum. A wide range of vibration frequencies from 10 Hz to 400 kHz are experimentally demonstrated. In addition, the proposed highly sensitive vibration sensor system was deployed in a field-test scenario for pipeline acoustic emission monitoring. An SMS fiber sensor is mounted on an 18” diameter pipeline, and vibrations were induced at different locations using a piezoelectric transducer. The proposed method was shown to be capable of real-time pipeline vibration monitoring.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Cryogenic RF characterization of the MAGO cavity for high-frequency gravitational-wave detection

Superconducting radio-frequency (SRF) cavities are promising resonant sensors for gravitational-wave detection in the kHz-MHz frequency range. We report the cryogenic RF characterization of a prototype superconducting niobium cavity with an unconventional geometry designed for narrow electromagnetic mode separation. Following an adapted surface preparation procedure, cryogenic tests were performed at Fermilab and DESY at temperatures down to 2 K. Mechanical tuning at room temperature achieved a mode splitting of approximately 11 kHz at cryogenic temperature. High electromagnetic quality factors consistent with previous prototype cavities were measured. The measurements further revealed phase transfer characteristics relevant for stable low-level RF control as well as indications of mode coupling potentially caused by one-point multipacting. In addition, first cryogenic measurements of the mechanical eigenmodes yielded mechanical quality factors significantly below commonly assumed theoretical values. These results demonstrate the successful application of established SRF preparation and characterization techniques to a non-standard resonator geometry and provide important experimental input for the development of future SRF-based gravitational-wave detectors.

Dokuyucu, Can [DESY]↗
DOE OSTI2020

Vibro-acoustic modulation and data fusion for localizing alkali–silica reaction–induced damage in concrete

This article investigates the application of vibro-acoustic modulation testing for diagnosing damage in concrete structures. The vibro-acoustic modulation technique employs two excitation frequencies on a structure. The interaction of these excitations in the measured response indicates damage through the presence of sidebands in the frequency spectra. Past studies using this technique have mostly focused on metals and composites (thin plates or laminates). Our research focuses on concrete, which is a highly heterogeneous material susceptible to a variety of chemical, physical, and mechanical damage processes. In particular, this article investigates diagnosing cracking in concrete from an expansive gel produced by an alkali–silica reaction in the presence of moisture. Past studies have been limited to damage detection using vibro-acoustic modulation testing, whereas this article extends the technique to damage localization. A cement slab with pockets of reactive aggregate is used to investigate the diagnosis technique. The effects of different testing parameters, such as locations, magnitudes, and frequencies of the two excitations, are analyzed and incorporated in the damage localization methodology. A Bayesian probabilistic methodology is developed to fuse the information from multiple test configurations in order to construct damage probability maps for the test specimen. The results of vibro-acoustic modulation–based damage localization are validated by petrographic study of cores taken from the slab.

Karve, Pranav↗
DOE OSTI2021

Searching For Transiting Planets Around Halo Stars. I. Sample Selection and Validation

By measuring the elemental abundances of a star, we can gain insight into the composition of its initial gas cloud—the formation site of the star and its planets. Planet formation requires metals, the availability of which is determined by the elemental abundance. In the case where metals are extremely deficient, planet formation can be stifled. To investigate such a scenario requires a large sample of metal-poor stars and a search for planets therein. This paper focuses on the selection and validation of a halo star sample. We select ~17,000 metal-poor halo stars based on their Galactic kinematics, and confirm their low metallicities ([Fe/H] < -0.5), using spectroscopy from the literature. Furthermore, we perform high-resolution spectroscopic observations using LBT/PEPSI and conduct detailed metallicity ([Fe/H]) analyses on a sample of 13 previously-known halo stars that also have hot kinematics. We can use the halo star sample presented here to measure the frequency of planets and to test planet formation in extremely metal-poor environments. The result of the planet search and its implications will be presented and discussed in a companion paper by Boley et al.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Revealing a 3D Fermi Surface Pocket and Electron-Hole Tunneling in UTe 2 with Quantum Oscillations

Spin triplet superconductor UTe 2 is widely believed to host a quasi-two-dimensional Fermi surface, revealed by first-principles calculations, photoemission and quantum oscillation measurements. An outstanding question still remains as to the existence of a three-dimensional Fermi surface pocket, which is crucial for our understanding of the exotic superconducting and topological properties of UTe 2 . This 3D Fermi surface pocket appears in various theoretical models with different physics origins, but has not been unambiguously detected in experiment. Here, in this study, for the first time we provide concrete evidence for a relatively isotropic, small Fermi surface pocket of UTe 2 via quantum oscillation measurements. In addition, we observed high frequency quantum oscillations corresponding to electron-hole tunneling between adjacent electron and hole pockets. The coexistence of 2D and 3D Fermi surface pockets, as well as the breakdown orbits, provides a test bed for theoretical models and aid the realization of a unified understanding of superconducting state of UTe 2 from the first-principles approach.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Development of NDE/NDT Tools for High-Volume & High-Speed Inspection of CFRP Structures in Automotive Manufacturing

Main advantages of the air-coupled ultrasound testing (ACUT) and electromagnetic testing (EMT) techniques for NDE of CFRP composites were non-contact sensing, scalability for high-speed inspection, cost-effectiveness, and non-hazardous operation. Despite these advantages, no systems that would satisfy the project requirements were commercially available. Hence, one of the major efforts of the Michigan State University (MSU) team at the initial stage of the project was to close this technological gap by developing, optimizing, and validating array sensors that would provide sufficient sensitivity, spatial coverage, and resolution for robust defect detection. Optimization of the ACUT and EMT sensor designs was performed using experimentally validated finite element models. Initial experiments using array probes were conducted on relatively flat CFRP samples. In parallel, the MSU team designed and assembled a portable platform with two robotic arms. The robots were equipped with newly designed sensors that enabled high-speed NDE of curved CFRP parts. Presently, the developed robotic platform can be used as a demo/template NDE system, which is easily adaptable to manufacturing environments and in-line NDE. The ACUT NDE system developed by the MSU team used a high-power 4-channel pulser receiver for parallel data acquisition. The array probes were designed by stacking commercially available ACUT transducers, which operated in the frequency range between 100 kHz and 500 kHz. MSU optimized the excitation procedure and developed wave focusing cones so as to reduce the crosstalk between the transducers and to provide higher pulse repletion frequency (PRF). The through-transmission (TT) and single-side access (SSA) inspection modes were successfully implemented. In the TT-ACUT, structural defects in CFRP were detected by passing ultrasonic waves through the test part. Hence, the ACUT transmitters and receivers needed to be placed on the opposite sides of the test part. In the SSA-ACUT, guided waves (GW) were excited in the test part using the transmitters and were sensed by the receivers from the same side. Multi-channel TT-ACUT and SSA-ACUT provided high-speed NDE, and were successfully validated on CFRP test samples with interlaminar delaminations and other embedded defects The EM techniques developed by the MSU team included: 1) eddy current testing (ECT), 2) capacitive imaging (CI) and hybrid dual-mode imaging. In ECT, structural damage was detected in CFRP using coils sensor arrays. In ECT, the excitation magnetic field is generated by passing an alternating current through a coil, which is placed above the test sample. The excitation field penetrates the conductive sample and induces the eddy currents in its transect. In turn, the eddy currents generate the reaction field, which affects the total field sensed by a coil. Hence, the presence of structural flaws will alter the eddy current flow and the picked-up signal. ECT is mostly sensitive to local changes of the electric conductivity of the test sample, and CFRPs are mostly conductive in the direction of carbon fibers. Hence, ECT was well suited for the detection of fiber damage/fiber irregularities. The MSU team developed printed circuit boards (PCB) with coil sensor arrays optimized for NDE of CFRP. Unlike most commercial probes designed for ECT of metallic structures, the MSU array probes were designed for operation in [1-10] MHz frequency range, which was optimal for low-conductive CFRP. Multiple sensing topologies (coil groups excitation/sensing arrangements) were implemented and successfully validated. Capacitive Imaging (CI) technique developed by MSU was complementary to ECT. In contrast to ECT, which was sensitive to local changes of the electrical conductivity, the CI was sensitive to local changes of the dielectric constant. Therefore, CI could provide information about matrix damage/matrix irregularities in CFRP. The MSU CI sensor arrays were made of multiple circular or rectangular open-plate capacitors printed on PCB. Sensors of this type are not commercially available. In addition to ECT and CI, the MSU team developed a hybrid (dual-mode) inductive/capacitive measurement technique that synergistically combined the benefits of inductive and capacitive sensing for rapid NDE of fiber reinforced polymer (FRP) composite structures. Fiber damage and fiber irregularities in FRPs were detected by configuring hybrid sensors as coil sensors. Similarly, matrix damage, matrix irregularities and interlaminar delaminations were detected by configuring hybrid sensors as capacitive sensors. ECT and CI were performed sequentially by means of electronic switching. Hence, eliminating the need for mounting two separate sensor arrays on the probe. Portable robotic platform was developed by MSU for multi-technique high-speed NDE of CFRP test parts. The platform had two 6-axis robots, which enabled inspection of curved parts in approximately a 6×6×6 ft 3 active scan area. On the software side, the MSU team integrated scripts for NDE hardware control with scripts for robot motion control. MSU also implemented automated path planning for the robots, reconstruction of part’s surfaces via stereovision, 3D rendering of inspection data, and image processing algorithms for enhanced defect detection. Automotive composite parts manufactured by Plasan Composites from Phase I were used to validate the ACUT and EMT techniques on representative testbeds. Among those parts were three X-braces for a Dodge Viper, one composite calibration plaque with known defects at known locations, and four other test sections, including sections from a front splitter, a corner section from a composite hood, and a high-pressure RTM panel made using non crimp fabric. Other test samples included CFRP and GFRP calibration plates with fiber/matrix defects fabricated at MSU/CVRC.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Solving Seismic Wave Equations on Variable Velocity Models With Fourier Neural Operator

Here, in the study of subsurface seismic imaging, solving the acoustic wave equation is a pivotal component in existing models. The advancement of deep learning (DL) enables solving partial differential equations (PDEs), including wave equations, by applying neural networks to identify the mapping between the inputs and the solution. This approach can be faster than traditional numerical methods when numerous instances are to be solved. Previous works that concentrate on solving the wave equation by neural networks consider either a single velocity model or multiple simple velocity models, which is restricted in practice. Instead, inspired by the idea of operator learning, this work leverages the Fourier neural operator (FNO) to effectively learn the frequency domain seismic wavefields under the context of variable velocity models. We also propose a new framework paralleled FNO (PFNO) for efficiently training the FNO-based solver given multiple source locations and frequencies. Numerical experiments demonstrate the high accuracy of both FNO and PFNO with complicated velocity models in the OpenFWI datasets. Furthermore, the cross-dataset generalization test verifies that PFNO adapts to out-of-distribution velocity models. Finally, PFNO admits higher computational efficiency on large-scale testing datasets than the traditional finite-difference method. The aforementioned advantages endow the FNO-based solver with the potential to build powerful models for research on seismic waves.

58 GEOSCIENCES↗
DOE OSTI2020

Relativistic Shear Boundary Layer and the Gamma-Ray Emission of GW170817

We present an analysis of the radiation characteristics of kinetic shear boundary layers created by relativistic plasma jets. Using a model of electromagnetic field data based on particle-in-cell simulations of an electron–ion plasma, we solve the motion of individual test electrons and compute their instantaneous radiated power and peak frequency. By analyzing a large number of test electrons in this manner, we find two distinct electron populations present around the shear boundary layer. The most highly radiative electrons execute looping motion due to crossed electric and magnetic fields as they are accelerated along the bulk flow of the jet, and eventually cross the shear boundary interface at steep angles. Electrons that never cross the shear boundary interface radiate much less energy as a group. Summing over all of the highly radiative electrons, we compute the distribution of the total radiated energy as a function of the angle relative to the bulk flow. Furthermore, this result has important potential implications for the observed radiation output of short gamma-ray bursts viewed at large angles from the jet axis, such as the neutron star merger event GW170817/GRB 170817A.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

High-resolution mapping of phase-matching conditions in second-order nonlinear crystals

We demonstrate the spatial mapping of phase-matching conditions in nonlinear crystals using detuned second-harmonic generation. A beam-stabilization system cancels out the angular wobbling of the translation stages that scan the crystal under test in front of the static probe beam at the fundamental frequency. A submillimeter resolution over the full scanned aperture, 50 × 50 mm 2 , is demonstrated. The mapping of several partially deuterated potassium dihydrogen phosphate (DKDP) crystals reveals the spatially nonuniform phase-matching conditions due to internal variations in crystal properties and high-frequency surface variations.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Multi-Timescale Integrated Dynamics and Scheduling for Solar (MIDAS-Solar) (Final Technical Report)

Solar photovoltaic (PV) installations have experienced unprecedented growth in the United States. PV will become not only an energy producer but also a necessary provider of ancillary services at multiple timescales. Conventional methods to simulate power systems operations - such as long-term production simulation (which typically considers schedules from hours to minutes by using an optimization framework) and short-term transient studies (which simulate dynamics from seconds to sub-seconds using state variables and differential equations) - are not sufficient for studying the multiple-timescale variation of solar generation and its impact on system reliability. Long-term system economics and short-term system dynamics are highly coupled, particularly when the penetration level of renewable generation is extremely high, because the uncertainty and variability of solar generation will impact both power system steady-state and dynamic performance. This project helps meet and exceed the U.S. Department of Energy Office of Energy Efficiency and Renewable Energy Solar Energy Technologies Office goal of systems integration by directly addressing this stability and reliability challenge for power grid planning and operation. We have developed a temporally comprehensive, closed-loop simulation model, named Multi-timescale Integrated Dynamics and Scheduling (MIDAS), that seamlessly simulates power system operations from economic scheduling (day-ahead to hours) to dynamic response analysis (seconds to sub-seconds). For schedules with very high levels of inverter-based resources (IBRs), up to and including 100%, the stability of grid controls has been evaluated through electromagnetic transient (EMT) simulations and power-hardware-in-the-loop (PHIL) simulations of key transient events at key schedule points. Specifically, MIDAS provides: 1) a closed-loop simulation framework for simulating timescales from economic scheduling to dynamic stability analysis; 2) machine learning-based stability assessment; 3) EMT modeling and analysis for large-scale power systems; 4) MIDAS PHIL test bed. We worked with Hawaii Electric Companies to apply the MIDAS study framework to a Maui grid study. The entire island's transmission system was modeled in detail - from a yearly scheduling model, to a second-level frequency dynamic model, down to a sub-second-scale EMT model to address critical stability issues. The project demonstrated how MIDAS can help system planners and operators assess system reliability and stability while the power grid is marching toward a high-renewable, high-IBR future. In this Maui grid study, we found that 100% instantaneous IBR operation is achievable in EMT simulation and PHIL testing, and grid planners and operators might need new analysis/simulation tools to assess grid reliability and stability in the scheduling stage. MIDAS will bring Maui and other systems closer to 100% clean and stable energy futures. (In this study, we examined transient stability. Other topics necessary for 100% IBR operation, such as protection and resource adequacy, were not examined.)

100% Renewables↗
DOE OSTI2024

The Atacama Cosmology Telescope: Mitigating the Impact of Extragalactic Foregrounds for the DR6 Cosmic Microwave Background Lensing Analysis

We investigate the impact and mitigation of extragalactic foregrounds for the cosmic microwave background (CMB) lensing power spectrum analysis of Atacama Cosmology Telescope (ACT) data release 6 (DR6) data. Two independent microwave sky simulations are used to test a range of mitigation strategies. We demonstrate that finding and then subtracting point sources, finding and then subtracting models of clusters, and using a profile bias-hardened lensing estimator together reduce the fractional biases to well below statistical uncertainties, with the inferred lensing amplitude, A lens , biased by less than 0.2σ. We also show that another method where a model for the cosmic infrared background (CIB) contribution is deprojected and high-frequency data from Planck is included has similar performance. Other frequency-cleaned options do not perform as well, either incurring a large noise cost or resulting in biased recovery of the lensing spectrum. In addition to these simulation-based tests, we also present null tests on the ACT DR6 data for sensitivity of our lensing spectrum estimation to differences in foreground levels between the two ACT frequencies used, while nulling the CMB lensing signal. These tests pass whether the nulling is performed at the map or bandpower level. The CIB-deprojected measurement performed on the DR6 data is consistent with our baseline measurement, implying that contamination from the CIB is unlikely to significantly bias the DR6 lensing spectrum. This collection of tests gives confidence that the ACT DR6 lensing measurements and cosmological constraints presented in companion papers to this work are robust to extragalactic foregrounds.

79 ASTRONOMY AND ASTROPHYSICS↗