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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Fourier Analysis and Loss Modeling for Inductive Wireless Electric Vehicle Charging with Reduced Stray Field

With the growth of electric vehicle (EV) popularity, different charging options to increase user convenience and reduce charging times are being considered and researched. Among these, inductive wireless power transfer (WPT) systems for EVs are being designed to meet specifications such as stray field, power level, efficiency, misalignment tolerance, and ground clearance, which are all heavily influenced by the coil geometry. The proposed Fourier Analysis Method (FAM) is an analytical method to directly design coil geometries to meet stray field and power level requirements through an optimization of Fourier basis function coefficients. The outputs of the optimization are complex, planar coil geometries that meet the power level and stray field constraints with minimized loss factors. Contours of these potentials determine the coil conductor paths and loss models predict the system efficiency and performance over misalignment. The Fourier representation of the geometry is used to conveniently calculate the coupling over misalignment, external proximity effect loss, and ferrite loss. A 6.6 kW prototype WPT system with low stray field and high efficiency is built from the optimization results to validate the models and showcase the usefulness of the FAM design approach.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Profiling overstory survival trends following varying thinning and burning disturbance regimes in a mixed pine-hardwood forest in the US South

Prescribed burning as a silvicultural tool may be effective for achieving various management objectives, yet some practitioners have concerns about inadvertently increasing overstory tree mortality. Using extensive data from a long-term, ongoing study in northcentral Alabama, USA, that systematically applies a variety of thinning and prescribed burning disturbances on mixed pine-hardwood stands, we assess survival trends for different groups of trees. The primary research question is whether more frequent prescribed burns adversely affects overstory survival versus infrequent or no burns; secondary questions explore whether overstory survival trends differ based on thinning level, species group, or size class. Interest is in broad groups of trees, not individual tree survival or mortality; consequently, survival analysis methods are used, including nonparametric Kaplan-Meier (KM) techniques for examining single grouping factors, and parametric accelerated failure time models for analyzing simultaneous effects of multiple covariates. Leveraging relatively recent methodological advances, the statistical techniques are adjusted for interval censored data. KM survival curves showed that more frequent prescribed fires did not result in differing survival trends. Also, trees in unthinned stands had the lowest 14-year survival compared to thinned stands, oaks had the highest survival compared to pines and the others species group, and the smallest size class of overstory trees had the lowest survival. In conclusion, these results support managing transitional mixed pine-hardwoods using thinning and multiple prescribed fires to restore specific species composition and structure.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

VLBI Data Processing on Coronal Radio-sounding Experiments of Mars Express

The ESA’s Mars Express solar corona experiments were performed at two solar conjunctions in the years 2015 and 2017 by a number of radio telescopes in the European VLBI Network. This paper presents the methods to measure the frequency and phase fluctuations of the spacecraft radio signal, and the applications to study the characteristics of the plasma turbulence effects on the signal at a single station and at multiple stations via cross correlation. The power spectra of the frequency fluctuations observed between 4.9 and 76.3 R {sub s} have a power-law shape close to a Kolmogorov spectrum over the frequency interval ν {sub lo} < ν < ν {sub up}, where the nominal value of ν {sub lo} is set to 3 mHz and ν {sub up} is in the range of 0.03–0.15 Hz. The rms of the frequency fluctuations is presented as a function of the heliocentric distance. Furthermore, we analyze the variations of the electron column density fluctuations at solar offsets 4.9 R {sub s} and 9.9 R {sub s} and the cross-correlation products between the VLBI stations. The power density of the differential fluctuations between different stations decreases at ν < 0.01 Hz. Finally, the fast flow speeds of solar wind >700 km s{sup -1} are derived from the cross correlation of frequency fluctuations at ν < 0.01 Hz. The fast flow speeds of solar wind correspond to the high heliolatitude of the coronal region that the radio rays passed. The VLBI observations and analysis methods can be used to study the electron column density fluctuations and the turbulence at multiple spatial points in the inner solar wind by providing multiple lines of sight between the Earth and the spacecraft.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Perturbation theory models for LSST-era galaxy clustering: Tests with subpercent mock catalog measurements in Fourier and configuration space

Here, we analyze the clustering of galaxies using the z = 1.006 snapshot of the CosmoDC2 simulation, a high-fidelity synthetic galaxy catalog designed to validate analysis methods for the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST). We present sub-percent measurements of the galaxy auto-correlation and galaxy-dark matter cross correlations in Fourier space and configuration space for a magnitude-limited galaxy sample. At these levels of precision, the statistical errors of the measurement are comparable to the systematic effects present in the simulation and measurement procedure; nevertheless, using a hybrid-PT model, we are able to model non-linear galaxy bias with 0.5% precision up to scales of k max = 0.5 h/Mpc and r min = 4 Mpc/h. While the linear bias parameter is measured with 0.01% precision, other bias parameters are determined with considerably weaker constraints and sometimes bimodal posterior distributions. We compare our fiducial model with lower dimensional models where the higher-order bias parameters are fixed at their co-evolution values and find that leaving these parameters free provides significant improvements in our ability to model small scale information. We also compare bias parameters for galaxy samples defined using different magnitude bands and find agreement between samples containing equal numbers of galaxies. Finally, we compare bias parameters between Fourier space and configuration space and find moderate to significant tension between the two approaches. Although our model is often unable to fit the CosmoDC2 galaxy samples within the 0.1% precision of our measurements, our results suggest that the hybrid-PT model used in this analysis is capable of modeling non-linear galaxy bias within the percent level precision needed for upcoming galaxy surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Improved evaluation of safeguards parameters from spent fuel measurements with the Differential Die-Away (DDA) instrument

The Differential Die-Away (DDA) technique is a highly sensitive non-destructive assay method for characterizing and detecting the presence of fissile material within an item of interest. DDA utilizes a series of pulses from a neutron generator (NG) to actively interrogate an item of interest. The die-away time of the neutron population induced by this active interrogation and the integral of the total differential die-away signal can be used to characterize items such as nuclear waste drums and spent nuclear fuel assemblies. In this work, Los Alamos National Laboratory (LANL) conceptualized, designed, and fabricated a DDA instrument that was deployed for field test measurements at the Central Interim Storage Facility for Spent Nuclear Fuel (Clab) in Oskarshamn, Sweden. The instrument performed multiple static measurements at fixed locations and dynamic axial scans of 15 pressurized water reactor (PWR) and 10 boiling water reactor (BWR) spent fuel assemblies, collecting both passive and active measurement data. The static assays of the assemblies measured the differential die-away signal, die-away time, and total passive neutron emission rate to create calibration curves for the evaluation of assembly multiplication, burnup, initial enrichment, effective fissile mass, and total elemental plutonium mass. Each calibration curve was optimized by minimizing the relative root mean square error (RRMSE) of assembly assay results compared to declared assembly parameters. The same quantities were also measured with the axial scans, and the resulting data were applied in two ways: (1) in the creation of calibration curves to improve evaluation of the same safeguards parameters as static assays, and (2) for comparison to simulation. In most cases, across both PWR and BWR assemblies, axial scan data improved the estimation of the above parameters, quantified by decreasing the calibration curve RRMSE. These axial scan results demonstrate the ability of the DDA instrument and analysis method to characterize spent PWR and BWR fuel as well as, or better than, a static assay of the same assembly. Furthermore, the DDA instrument’s unique ability to obtain both active and passive data in a single, axial scan of an entire spent fuel assembly represents a more efficient and accurate way of assaying spent fuel for verification purposes. These results represent a significant advancement for characterizing spent nuclear fuel compared to current technologies.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Application of end-of-shift respirable crystalline silica monitoring to construction

A pilot project was conducted to determine the effect of common construction dusts as interferences in a new portable end-of-shift (EoS), direct-on-filter (DoF) sampling and analysis method for respirable crystalline silica (RCS), in this case, quartz. Construction dusts were prepared from plaster, drywall, cement and brick by grinding, aerosolizing, and collecting respirable dust with high flow rate cyclones. Filters were loaded with different levels of commercial α-quartz powder Min-u-Sil 5, and different levels of interfering dusts, singly and in combination. Samples were analyzed by Fourier Transform Infrared Spectroscopy (FTIR). Good correlations were found between nominal quartz loading (0 µg, 25 µg, 50 µg, and 100 µg) adjusted for quartz in the interfering dust and FTIR absorbance alone and in the presence of all interfering dusts. The slopes of the correlations were similar whether the loading was quartz without interference, or with plaster, drywall, and cement dusts, regardless of quantity. The results show that (a) plaster and drywall dusts do not interfere substantially; (b) cement does not interfere, but a change in the intercept suggests an effect on the background absorbance of the filter; and (c) in addition to having a substantial quartz content, brick dust contains an additional material, probably a silicate mineral, which interferes with the quartz peak. Thus, the presence of cement leads to lower quartz values and brick leads to higher values, but overall, 83% of the quartz contents predicted from the calibration data agreed within 50% of the adjusted nominal loadings within the range 20–110 µg. This result is encouraging given the high levels of interfering dusts. Nine samples loaded with smaller amounts of all four dusts together gave results within 25% of the adjusted nominal loadings. A single mixture addition of the dusts to the filter gave tighter variance in results than sequential additions. Unexpectedly, the two Certified Reference Materials (CRMs) 1878a and 1878b, gave different results when used to calibrate XRD analysis of Min-u-Sil 5.

42 ENGINEERING↗
DOE OSTI2024

Can section 45Q tax credit foster decarbonization? A case study of geologic carbon storage at Acid Gas Injection wells in the Permian Basin

Carbon capture, utilization, and storage (CCUS) is an important pathway for meeting climate mitigation goals. While the economic viability of CCUS is well understood, previous studies do not evaluate the economic feasibility of carbon capture and storage (CCS) in the Permian Basin specifically regarding the new Section 45Q tax credits. We developed a technoeconomic analysis method, evaluated the economic feasibility of CCS at the acid gas injection (AGI) wells, and assessed the implication of Section 45Q tax credits for CCS at the AGIs. We find that the compressors, well depth, and the permit and monitoring costs drive the facility costs. Compressors are the predominant contributors to capital and operating expenditure driving the levelized cost of CO 2 storage. Strategic cost reduction measures identified include 1) sourcing of low-cost electricity and 2) optimizing operational efficiency in well operations. In evaluating the impact of the tax credits on CCS projects, facility scale proved decisive. We found that facilities with an annual injection rate exceeding 10,000 MT storage capacity demonstrate economic viability contingent upon the procurement of inputs at the least cost. The new construction of AGI wells were found to be economically viable at a storage capacity of 100,000 MT. The basin is heavily focused on CCUS (tax credit – $\$$65/MT CO 2 ), which overshadows CCS ($\$$85/MT CO 2 ) opportunities. Balancing the dual objectives of CCS and CCUS requires planning and coordination for optimal resource and pore space utilization to attain the basin's decarbonization potential. We also found that CCS on AGI is a lower cost CCS option as compared to CCS on other industries.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Physiological Controls on Carbon Fluxes and Biomass Production in Miscanthus: Insights From a Process‐Based Agroecosystem Model

Biomass crops serve as essential feedstocks for renewable energy and bioproducts and play a critical role in achieving lower emissions in the transportation sector. However, dedicated perennial biomass crops such as Miscanthus × giganteus (Miscanthus) remain underrepresented in process-based agroecosystem models, limiting robust evaluation of their economic and environmental performance. In this study, we developed a data-constrained representation of the sterile triploid Miscanthus (IL clone) within the process-based model ecosys, integrating global sensitivity analysis, ensemble simulation, and parameter calibration. Planting, harvesting, and fertilization practices consistent with field management were incorporated, and phenology was constrained using PhenoCam-derived Green Chromatic Coordinate (GCC) data. Using the Morris global sensitivity analysis method, we identified 11 key physiological parameters governing plant carbon, water, and nutrient relations, particularly processes associated with CO 2 assimilation. We then conducted ensemble simulations by perturbing these parameters and calibrated the model against eddy covariance fluxes and field-measured biomass. Building on the calibrated operating state, parameter-response analyses show that different photosynthetic processes influence productivity in different ways. Protein allocation determines whether productivity increases toward a higher level, whereas electron transport capacity controls additional gains once protein allocation approaches saturation. These findings demonstrate that parameter importance depends on physiological context and on which photosynthetic processes remain limiting. Calibration and validation against observations show that ecosys can reliably reproduce carbon and water fluxes, as well as both above- and belowground biomass, with post-calibration GPP R 2 improving from 0.67 to 0.95 during the calibration period and remaining high during validation (R 2 = 0.95). These results provide a mechanistic foundation for regional simulations and sustainable bioenergy assessments.

ecosys↗
DOE OSTI2025

The DECADE cosmic shear project III: validation of analysis pipeline using spatially inhomogeneous data

We present the pipeline for the cosmic shear analysis of the Dark Energy Camera All Data Everywhere (DECADE) weak lensing dataset: a catalog consisting of 107 million galaxies observed by the Dark Energy Camera (DECam) in the northern Galactic cap. The catalog derives from a large number of disparate observing programs and is therefore more inhomogeneous across the sky compared to existing lensing surveys. First, we use simulated data-vectors to show the sensitivity of our constraints to different analysis choices in our inference pipeline, including sensitivity to residual systematics. Next we use simulations to validate our covariance modeling for inhomogeneous datasets. Finally, we show that our choices in the end-to-end cosmic shear pipeline are robust against inhomogeneities in the survey, by extracting relative shifts in the cosmology constraints across different subsets of the footprint/catalog and showing they are all consistent within 1σ to 2σ. This is done for forty-six subsets of the data and is carried out in a fully consistent manner: for each subset of the data, we re-derive the photometric redshift estimates, shear calibrations, survey transfer functions, the data vector, measurement covariance, and finally, the cosmological constraints. Our results show that existing analysis methods for weak lensing cosmology can be fairly resilient towards inhomogeneous datasets. This also motivates exploring a wider range of image data for pursuing such cosmological constraints.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Probe the Localized Electrochemical Environment Effects and Electrode Reaction Dynamics for Metal Batteries using In Situ 3D Microscopy

Uncontrollable dendrite growth is closely related to non-uniform reaction environments. However, there is a lack of understanding and analysis methods to probe the localized electrochemical environment (LEE). Here the effects of the LEE are investigated, including localized ion concentrations, current density, and electric potential, on metal plating/stripping dynamics and dendrite minimization. A novel in situ 3D microscopy technique is developed to image the morphology dynamics and deposition rate of Zn plating/stripping processes on 3D Zn–Mn anodes. Using the in situ 3D microscope, the electrode morphology changes during the reactions are directly imaged and Zn deposition rate maps at different time points are obtained. It is found that reaction kinetics are highly correlated to LEE and electrode morphology. To further quantify the LEE effects, the digital twin technique is employed that allows the accurate calculation of the electrochemical environments, such as localized ion concentrations, current density, and electric potential, which cannot be directly measured from experiments. We found that the curvature of the 3D electrode surface determines the LEE and significantly influences reaction kinetics. This provides a new strategy to minimize the dendrite formation by designing and optimizing the 3D geometry of the electrode to control the LEE.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Probing the Behavior of Composition‐Tunable Ultrathin PtNi Nanowires for CO Oxidation and Small‐Molecule Electrocatalytic Reactions

We have successfully synthesized ultrathin nanowires of pure Pt, Pt 99 Ni 1 , Pt 9 Ni 1 , and Pt 7 Ni 3 using a modified room-temperature soft-template method. Analysis of both methanol oxidation reaction (MOR) and ethanol oxidation reaction (EOR) results found that the Pt 7 Ni 3 samples yielded the best performance with specific activities of 0.36 and 0.34 mA/cm 2 respectively. Additionally, formic acid oxidation reaction (FAOR) tests noted that both Pt and PtNi nanowires oxidize small organic molecules (SOMs) via an indirect pathway. CO oxidation data suggests little measurable performance without any pre-reduction treatment; however, after annealing in H 2 , we detected significantly improved CO 2 formation for both Pt 9 Ni 1 and Pt 7 Ni 3 motifs. These observations highlight the importance of pre-treating these nanowires under a reducing atmosphere to enhance their performance for CO oxidation. To explain these findings, we collected extended x-ray adsorption fine structure (EXAFS) spectroscopy data, consistent with the presence of partial alloying with a tendency for Pt and Ni to segregate, thereby implying the formation of a Pt-rich shell coupled with a Ni-rich core. Here, we also observed that the degree of alloying within the nanowires increased after annealing in a reducing atmosphere, a finding deduced through analysis of the coordination numbers and calculations of Cowley's short range order parameters.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Reliable machine prognostic health management in the presence of missing data

Prognostics and health management enables the prediction of future degradation and remaining useful life (RUL) for in-service systems based on historical and contemporary data, showing promise for many practical applications. One major challenge for prognostics is the common occurrence of missing values in time-series data, often caused by disruptions in sensor communication or hardware/software failures. Another major concern is that the sufficient prior knowledge of critical component degradation with a clear failure threshold is often not readily available in practice. These issues can significantly hinder the application of advanced signal and data analysis methods and consequently degrade the health management performance. In this article, we propose a novel data-driven framework that is capable of providing accurate and reliable predictions of degradation and RUL. In this approach, one-hot health state indicators are appended to the historical time series so that the model learns end-of-life automatically. A modified gate recurrent unit based variational autoencoder is employed in generative adversarial networks to model the temporal irregularity of the incomplete time series. Furthermore, experiments on multivariate time-series datasets collected from real-world aeroengines verify that significant performance improvement can be achieved using the proposed model for robust long-term prognostics.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2023

Surface and subsurface oceanographic features drive forage fish distributions and aggregations: Implications for prey availability to top predators in the US Northeast Shelf ecosystem

Abstract Forage fishes are a critical food web link in marine ecosystems, aggregating in a hierarchical patch structure over multiple spatial and temporal scales. Surface‐level forage fish aggregations (FFAs) represent a concentrated source of prey available to surface‐ and shallow‐foraging marine predators. Existing survey and analysis methods are often imperfect for studying forage fishes at scales appropriate to foraging predators, making it difficult to quantify predator–prey interactions. In many cases, general distributions of forage fish species are known; however, these may not represent surface‐level prey availability to predators. Likewise, we lack an understanding of the oceanographic drivers of spatial patterns of prey aggregation and availability or forage fish community patterns. Specifically, we applied Bayesian joint species distribution models to bottom trawl survey data to assess species‐ and community‐level forage fish distribution patterns across the US Northeast Continental Shelf (NES) ecosystem. Aerial digital surveys gathered data on surface FFAs at two project sites within the NES, which we used in a spatially explicit hierarchical Bayesian model to estimate the abundance and size of surface FFAs. We used these models to examine the oceanographic drivers of forage fish distributions and aggregations. Our results suggest that, in the NES, regions of high community species richness are spatially consistent with regions of high surface FFA abundance. Bathymetric depth drove both patterns, while subsurface features, such as mixed layer depth, primarily influenced aggregation behavior and surface features, such as sea surface temperature, sub‐mesoscale eddies, and fronts influenced forage fish diversity. In combination, these models help quantify the availability of forage fishes to marine predators and represent a novel application of spatial models to aerial digital survey data.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Continuous Counter‐Current Microfluidic Liquid–Liquid Extraction Achieved Using a Pair of Wettable Screen Meshes

Continuous counter‐current microfluidic liquid–liquid extraction performs separations by flowing immiscible liquids in opposing directions within a single flow channel. In principle, this flow arrangement enables a large number of theoretical separation units in a small footprint, without using interstage valving, pumping, and phase separation. Despite its potential for excellent separation performance, this microfluidic scheme rarely appears in literature due to the requirement for capillary forces to be greater than hydrodynamic forces for stable flow. We present a novel microfluidic device and flow approaches that overcome this force‐balance challenge, enabling stable, long‐duration continuous counter‐current flow. Additionally, we cover a suite of methodologies for quantifying the performance of the microfluidic device, revealing the number of theoretical equilibrium stages achieved. The enabling technologies include a woven mesh screen‐based microfluidic device architecture that is easily fabricated outside of a clean room, surface functionalization strategies to promote conjugate (organic/aqueous) wettability, flow approaches to eliminate bubbles and carryover, and computer‐aided flow automation with optical measurement of extraction performance. The reported experiments lasted for over 36 h, terminated only at experiment conclusion, where the device still exhibited good performance. Automated Raman spectroscopy was used for solute quantitation of the ternary system tert‐butanol in a toluene/water matrix, a ternary system that was specifically chosen to analyze the device's performance with a small solute partition ratio and to enable in‐line Raman measurements of solute concentrations in both phases. The microfluidic device possessed a 55 mm contact length and a 38.5 µL internal volume. During counter‐current flow, we observed approximately 37 equilibrium stages (37 ± 13) based on a best‐fit of the solute fraction remaining in the aqueous phase using a Kremser Group Method analysis.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Hacking Limnology Workshop and DSOS22: Creating a Community of Practice for the Nexus of Data Science, Open Science, and the Aquatic Sciences

The 2nd Aquatic Ecosystem Modeling-Junior (AEMON-J) Hacking Limnology Workshop and 3rd Virtual Summit: Incorporating Data Science and Open Science in the Aquatic Sciences (DSOS) took place on 25–29 July 2022. These virtual events were developed to bring together researchers from diverse backgrounds to share developments in data-intensive research in the aquatic sciences and train participants in cutting-edge data analysis methods related to remote sensing, data pipelines, and modeling of aquatic ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Computing Potential of the Mean Force Profiles for Ion Permeation Through Channelrhodopsin Chimera, C1C2

Umbrella sampling, coupled with a weighted histogram analysis method (US-WHAM), can be used to construct potentials of mean force (PMFs) for studying the complex ion permeation pathways of membrane transport proteins. Despite the widespread use of US-WHAM, obtaining a physically meaningful PMF can be challenging. Here, we provide a protocol to resolve that issue. Then, we apply that protocol to compute a meaningful PMF for sodium ion permeation through channelrhodopsin chimera, C1C2, for illustration.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Semi-supervised permutation invariant particle-level anomaly detection

The development of analysis methods to distinguish potential beyond the Standard Model phenomena in a model-agnostic way can significantly enhance the discovery reach in collider experiments. However, the typical machine learning (ML) algorithms employed for this task require fixed length and ordered inputs that break the natural permutation invariance in collision events. To address this, a semi-supervised anomaly detection tool is presented that takes a variable number of particle-level inputs and leverages a signal model to encode this information into a permutation invariant, event-level representation via supervised training with a Particle Flow Network (PFN). Data events are then encoded into this representation and given as input to an autoencoder for unsupervised ANomaly deTEction on particLe flOw latent sPacE (ANTELOPE), classifying anomalous events based on a low-level and permutation invariant input modeling. Performance of the ANTELOPE architecture is evaluated on simulated samples of hadronic processes in a high energy collider experiment, showing good capability to distinguish disparate models of new physics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Volcano infrasound: progress and future directions

Over the past two decades (2000–2020), volcano infrasound (acoustic waves with frequencies less than 20 Hz propagating in the atmosphere) has evolved from an area of academic research to a useful monitoring tool. As a result, infrasound is routinely used by volcano observatories around the world to detect, locate, and characterize volcanic activity. It is particularly useful in confirming subaerial activity and monitoring remote eruptions, and it has shown promise in forecasting paroxysmal activity at open-vent systems. Fundamental research on volcano infrasound is providing substantial new insights on eruption dynamics and volcanic processes and will continue to do so over the next decade. The increased availability of infrasound sensors will expand observations of varied eruption styles, and the associated increase in data volume will make machine learning workflows more feasible. More sophisticated modeling will be applied to examine infrasound source and propagation effects from local to global distances, leading to improved infrasound-derived estimates of eruption properties. Future work will use infrasound to detect, locate, and characterize moving flows, such as pyroclastic density currents, lahars, rockfalls, lava flows, and avalanches. Infrasound observations will be further integrated with other data streams, such as seismic, ground- and satellite-based thermal and visual imagery, geodetic, lightning, and gas data. The volcano infrasound community should continue efforts to make data and codes accessible and to improve diversity, equity, and inclusion in the field. In summary, the next decade of volcano infrasound research will continue to advance our understanding of complex volcano processes through increased data availability, sensor technologies, enhanced modeling capabilities, and novel data analysis methods that will improve hazard detection and mitigation.

58 GEOSCIENCES↗