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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 1,225 records · Page 68
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Atomic Physics of Shocked Plasma in Winds of Massive Stars

High resolution diffraction grating spectra of X-ray emission from massive stars obtained with Chandra and XMM-Newton have revolutionized our understanding of their powerful, radiation-driven winds. Emission line shapes and line ratios provide diagnostics on a number of key wind parameters. Modeling of resolved emission line velocity profiles allows us to derive independent constraints on stellar mass-loss rates, leading to downward revisions of a factor of a few from previous measurements. Line ratios in He-like ions strongly constrain the spatial distribution of Xray emitting plasma, confirming the expectations of radiation hydrodynamic simulations that X-ray emission begins moderately close to the stellar surface and extends throughout the wind. Some outstanding questions remain, including the possibility of large optical depths in resonance lines, which is hinted at by differences in line shapes of resonance and intercombination lines from the same ion. Resonance scattering leads to nontrivial radiative transfer effects, and modeling it allows us to place constraints on shock size, density, and velocity structure

Physics↗
NASA NTRS2017

The Pathway to a Safe and Effective Medication Formulary for Exploration Spaceflight

PURPOSE: Exploration space missions pose several challenges to providing a comprehensive medication formulary designed to accommodate the size and space limitations of the spacecraft; while addressing the individual medications needs and preferences of the Crew; the negative outcome of a degrading inventory over time, the inability to resupply before expiration dates; and the need to properly forecast the best possible medication candidates to treat conditions that will occur in the future. METHODS: The Pharmacotherapeutics Discipline has partnered with the Exploration Medical Capabilities (ExMC) Element to develop and propose a research pathway that is comprehensively focused on evidence-based models and theories, as well as on new diagnostic tools and treatments or preventive measures aimed at closure of the Med02 “Pharmacy” Gap; defined in the Human Research Program’s (HRP) risk-based research strategy. The Med02 Gap promotes the challenge to identify a strategy to ensure that medications used to treat medical conditions during exploration space missions are available, safe, and effective. It is abundantly clear that pharmaceutical intervention is an essential component of risk management planning for astronaut healthcare during exploration space. However, the quandary still remains of how to assemble a formulary that is comprehensive enough to prevent or treat anticipated medical events; and is also chemically stable, safe, and robust enough to have sufficient potency to last for the duration of an exploration space mission. In cases where that is not possible, addressing this Gap requires exploration of novel drug development techniques, dosage forms, and dosage delivery platforms that enhance chemical stability as well as therapeutic effectiveness. RESULTS: The proposed research pathway outlines the steps, processes, procedures, and a research portfolio aimed at identifying a capability that will provide a safe and effective pharmacy for any specific exploration Design Reference Mission (DRM). The proposed approach to building this research portfolio is to seek research projects that concentrate on four major focus areas; (1) Formulary selection, (2) Formulary potency and shelf life, (3) Formulary safety and toxicity, and (4) Novel technology and innovation such as portable real-time chemical analysis innovative drug therapies and dosage and delivery platforms. CONCLUSION: The research pathway has been completed and presented to the HRP. In spring 2017, it is scheduled to be reviewed by a panel of pharmaceutical and clinical experts that will evaluate the scientific merit and operational feasibility of the research pathway, as well as make suggestions for any warranted additions or improvements. Once finalized, the ExMC Element will proceed with the execution of this research pathway with the goal of gathering as much data, and learning as much as possible, to provide a safe and effective pharmaceutical formulary for use during exploration missions.

Daniels, V. R.↗
NASA NTRS2019

Considerations for Femtosecond Laser Electronic Excitation Tagging in High-Speed Flows

Femtosecond laser electronic excitation tagging (FLEET) is an unseeded method for molecular tagging which offers valuable opportunities for measurement of high-speed (transonic, supersonic or hypersonic) flows. The unique nature of high-speed testing demands certain performance from FLEET such as satisfactory signal-to-noise ratio (SNR) at depressed static conditions (i.e., low temperatures, pressures and densities), wide dynamic range for velocity determination (especially single-shot), and measurements with acceptable accuracy and precision. This dissertation strives to evaluate FLEET in those regards and provide strategies to maximize the method's capabilities. A zero-dimensional kinetics model in nitrogen explains FLEET signal changes with pressure/density and/or temperature in terms of plasma-chemical reactions. Poorly known rate coefficients are tuned by comparing model output to measurements, with temporal agreement up to several hundred nanoseconds. Modeling reveals that initial signal peaks at reduced density because of slowed temporal evolution (and decay) of excited populations. Low temperatures enhance signal by enlarging cluster ion populations which contribute to excited species via electron-ion dissociative recombination. A purpose-built free jet facility provides experimental validation of the kinetics model and assesses FLEET velocimetry in low temperature and pressure/density conditions. Signal, lifetime, accuracy and precision results are obtained from unheated subsonic through Mach 4.0 operation of the facility, with best results noted. FLEET measurements of a sweeping jet (SWJ) actuator in compressible operation showcase its advantages in a highly unsteady jet containing subsonic through supersonic velocities. FLEET velocimetry is performed in the device's internal and external flow fields, with the latter compared to hot-wire anemometry. Internal measurements reveal the absence of shockwaves theorized to occur at high pressure ratios. Simultaneous qualitative measurements of compressible jet mixing are shown as a proof-of-concept. Overall, the work demonstrates that previous understanding of SWJ incompressible operation readily extends into the compressible realm. Practical aspects of performing FLEET velocimetry are detailed, along with strategies for improving measurement quality. Determination of a fundamental precision in nitrogen and air is attempted. Experiments show that increasing time delay and/or SNR improves velocimetry precision. A comparison of five camera systems indicates sensors with larger pixels capture higher SNR data and produce more precise results.

FLEET↗
NASA NTRS2019

An Approach for Uncertainty Quantification and Management of Unmanned Aerial Vehicle Health

The increasing interest in low-altitude unmanned aerial vehicle (UAV) operations is bringing along safety concerns. Performance of small, low-cost UAVs drastically changes with type, size and controller of the vehicle. Their reliability is lower when compared to reliability of commercial aircrafts, and the availability of on-board sensors for health and state awareness is extremely limited due to their size and propulsion capabilities. Uncertainty plays a dominant role in such a scenario, where a variety of UAVs of different size, propulsion systems, dynamic performance and reliability enters the low-altitude airspace. Unexpected failures could have dangerous consequences for both equipment and humans within that same airspace. As a result, a number of research works and methodologies are being proposed in the area of UAV dynamic modeling, health and safety monitoring, but uncertainty quantification is rarely addressed. Thus, this paper pro- poses a perspective towards uncertainty quantification for autonomous systems, giving special emphasis to a UAV health monitoring application. A formal approach to classify uncertainty is presented; it is utilized to identify the uncertainty sources in UAVs health and operations, and then map uncertainty within a predictive process. To show the application of the methodology proposed here, the design of a model-based powertrain health monitoring algorithm for small-size UAVs is used as case study. The example illustrates how the uncertainty quantification approach can help the modeling strategy, as well as the assessment of diagnostic and prognostic performance.

Health Monitoring↗
DOE OSTI2014

44th Annual Anomalous Absorption Conference

Conference Grant Report July 14, 2015 Submitted to the U. S. Department of Energy Attn: Dr. Sean Finnegan By the University of California, San Diego 9500 Gilman Drive La Jolla, California 92093 On behalf of the 44th Annual Anomalous Absorption Conference 8-13 June 2014, in Estes Park, Colorado Support Requested: $10,100 Amount expended: $3,216.14 Performance Period: 1 March 20 14 to 28 February 20 15 Principal Investigator Dr. Farhat Beg Center for Energy Research University of California, San Diego 9500 Gilman Drive La Jolla, California 92093-0417 858-822-1266 (telephone) 858-534-4543 (fax) fbeg@ucsd.edu Administrative Point of Contact: Brandi Pate, 858-534-0851, blpate®ucsd.edu I. Background The forty-fourth Anomalous Absorption Conference was held in Estes Park, Colorado from June 5-8, 2014 (aac2014.ucsd.edu). The first Anomalous Absorption Conference was held in 1971 to assemble experts in the poorly understood area of laser-plasma absorption. The goal of that conference was to address the anomalously large laser absorption seen in plasma experiments with respect to the laser absorption predicted by linear plasma theory. Great progress in this research area has been made in the decades since that first meeting, due in part to the scientific interactions that have occurred annually at this conference. Specifically, this includes the development of nonlinear laser-plasma theory and the simulation of laser interactions with plasmas. Each summer since that first meeting, this week-long conference has been held at unique locations in North America as a scientific forum for intense scientific exchanges relevant to the interaction of laser radiation with plasmas. Responsibility for organizing the conference has traditional rotated each year between the major Inertial Confinement Fusion (ICF) laboratories and universities including LANL, LLNL, LLE, UCLA UC Davis and NRL. As the conference has matured over the past four decades, its technical footprint has expanded beyond ICF-related laser-plasma interactions to encompass closely related technical areas including laser particle acceleration, high-intensity laser effects, short­ pulse laser interactions, PIC and Vlasov/rad-hydro modeling, inertial and magnetic fusion plasmas, advanced plasma diagnostics, alternate ignition schemes, EOS/transport/opacity, and this year, x­ ray free-electron lasers and their applications. The conference continues to be a showcase for the presentation and discussion of the latest developments in these areas. II. Meeting Report The conference was extremely successful with more than one hundred participants. There were ninety-nine (99) abstracts submitted. There were forty-four (44) presentations including eleven (11) invited talks. The following topics were covered: a) Radiation Hydrodynamics b) Implosion Plasma Kinetic Effects c) Alternate Ignition Schemes d) Astrophysical Phenomena e) Opacity/Transport/EOS f) High Power Lasers and Facilities g) High-Intensity Laser-Matter Interactions h) Hydrodynamics and Hydro-instabilities i) Hot Dense Plasma Atomic Processes j) High Energy Density Physics k) Laser Particle Acceleration Physics l) Advanced Plasma Diagnostics m) Advanced light sources and applications Despite significant advertising, there were two students who applied for the travel grants: Charlie Jarrott and Joohwan Kim. The total funds expended were $3,216.14.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

Multiphysics approach to plasma neutron source modelling at the JET tokamak

A novel multiphysics methodology for the computation of realistic plasma neutron sources has been developed. The approach is based on state-of-the-art plasma transport and neutron spectrum calculations, coupled with a Monte Carlo neutron transport code, bridging the gap between plasma physics and neutronics. In the paper two JET neutronics tokamak models are used to show the application of the developed plasma neutron sources and validate them. Diagnostic data for the record JET D discharge 92436 are used as input for the TRANSP code, modelling neutron emission in two external plasma heating scenarios, namely using only neutral beam injection and a combination of the latter and ion cyclotron resonance heating. Neutron spectra, based on plasma transport results, are computed using the DRESS code. The developed PLANET code package is employed to generate plasma neutron source descriptions and couple them with the MCNP code. The effects of using the developed sources in neutron transport calculations on the response of JET neutron diagnostic systems is studied and compared to the results obtained with a generic plasma neutron source. It is shown that, although there are significant differences in the emissivity profiles, spectra shape and anisotropy between the neutron sources, the integral response of the time-resolved ex-vessel neutron detectors is largely insensitive to source changes, with major relative deviations of up to several percent. However it is calculated that, because of the broadening of neutron spectra as a consequence of external plasma heating, larger differences may occur in activation of materials which have threshold reactions located at DD neutron peak energies. The PLANET plasma neutron source computational methodology is demonstrated to be suitable for detailed neutron source effect studies on JET during DT experiments and can be applied to ITER analyses.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2013

THREE-DIMENSIONAL GEOMETRIES AND THE ANALYSIS OF H II REGIONS

We compare emission line intensities from photoionization models of smooth and fractal shell geometries for low density H II regions, with particular focus on the low-ionization diagnostic diagram [N II]/H{alpha} versus H{alpha}. Building on previously published models and observations of Barnard's Loop, we show that the observed range of intensities and variations in the line intensity ratios may be reproduced with a three-dimensional shell geometry. Our models adopt solar abundances throughout the model nebula, in contrast with previous one-dimensional modeling which suggested the variations in line intensity ratios could only be reproduced if the heavy element abundances were increased by a factor of {approx}1.4. For spatially resolved H II regions, the multiple sightlines that pierce and sample different ionization and temperature conditions within smooth and fractal shells produce a range of line intensities that are easily overlooked if only the total integrated intensities from the entire nebula model are computed. Our conclusion is that inference of H II region properties, such as elemental abundances, via photoionization models of one-dimensional geometries must be treated with caution and further tested through three-dimensional modeling.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2017

Twenty-First-Century Changes in U.S. Regional Heavy Precipitation Frequency Based on Resolved Atmospheric Patterns

Precipitation-gauge observations and atmospheric reanalysis are combined to develop an analogue method for detecting heavy precipitation events based on prevailing large-scale atmospheric conditions. Combinations of atmospheric variables for circulation (geopotential height and wind vector) and moisture (surface specific humidity, column and up to 500-hPa precipitable water) are examined to construct analogue schemes for the winter [December–February (DJF)] of the “Pacific Coast California” (PCCA) region and the summer [June–August (JJA)] of the Midwestern United States (MWST). The detection diagnostics of analogue schemes are calibrated with 1979–2005 and validated with 2006–14 NASA Modern-Era Retrospective Analysis for Research and Applications (MERRA). All analogue schemes are found to significantly improve upon MERRA precipitation in characterizing the occurrence and interannual variations of observed heavy precipitation events in the MWST. When evaluated with the late twentieth-century climate model simulations from phase 5 of the Coupled Model Intercomparison Project (CMIP5), all analogue schemes produce model medians of heavy precipitation frequency that are more consistent with observations and have smaller intermodel discrepancies than model-based precipitation. Under the representative concentration pathways (RCP) 4.5 and 8.5 scenarios, the CMIP5-based analogue schemes produce trends in heavy precipitation occurrence through the twenty-first century that are consistent with model-based precipitation, but with smaller intermodel disparity. The median trends in heavy precipitation frequency are positive for DJF over PCCA but are slightly negative for JJA over MWST. Overall, the analyses highlight the potential of the analogue as a powerful diagnostic tool for model deficiencies and its complementarity to an evaluation of heavy precipitation frequency based on model precipitation alone.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Feedback, physics, and forecasts: The emerging paradigm of machine learning-driven battery research

Machine learning (ML) is reshaping how we understand, predict, and optimize electrochemical systems. In batteries, ML accelerates discovery across chemistry, design, and operation by transforming massive experimental and simulated datasets into predictive, interpretable models. This review consolidates a decade of progress in ML-driven battery innovation, from early-cycle feature extraction to operando image analysis and physics-informed modeling. We categorize approaches by data domain and physical fidelity, emphasizing interpretable ML for diagnostics, reinforcement learning for control, and multi-objective optimization for lifetime extension strategies. Additionally, we demonstrate how integrated models accelerate discovery, reduce testing time, and guide sustainable design. Economic analyses furthermore illustrate how these advances can lower cost per cycle and improve circularity. Together, these developments chart a path toward self-optimizing, sustainable battery technologies.

artificial intelligence↗
NASA NTRS1995

Transmission diagnostic research at NASA Lewis Research Center

The NASA Lewis Research Center and the U.S. Army Research Laboratory are involved in a joint research program to advance the technology of aerospace transmissions. Within the last six years, a transmission diagnostics research team was formed to address current and future technology barriers in transmission diagnostics. The diagnostics team conducted a survey to determine critical needs of the diagnostics community. Survey results indicated that experimental verification of gear and bearing fault detection methods and damage magnitude assessment were considered the two most critical research areas of a highly reliable health and usage monitoring system. A plan was implemented by the diagnostics team to address these key research areas, by in-house research and university grants. A variety of transmission fault detection methods were applied to experimentally obtained fatigue data. Failure modes of the fatigue tests include a variety of gear pitting failures, tooth wear, tooth fracture, and bearing spalling failures. Accomplishments to date include verification of several specific gear diagnostic methods, verification of a new pattern recognition method to determine failure, and development of a new method to model gear tooth damage. This paper presents the results of these accomplishments in transmission diagnostics research at NASA Lewis Research Center.

Zakrajsek, J. J.↗
DOE OSTI2026

A unified large language model–based framework for heterogeneous PV image diagnosis

With advances in imaging technologies, modern photovoltaic (PV) systems generate large volumes of heterogeneous image data, including visible, electroluminescence (EL), and infrared (IR) images. Existing PV image analysis models, particularly deep learning approaches, are typically task-specific and lack cross-modality generalization. To address this limitation, this paper proposes an open-source large language model (LLM)–based unified framework for heterogeneous PV image diagnostics. Through task-aware diagnostic prompting, the framework enables analysis of visible, EL, and IR images within a single pipeline, supporting both zero-shot and few-shot inference and binary and multiclass classification. It is compatible with state-of-the-art multimodal LLMs, including ChatGPT, Gemini, Claude, Qwen, and CLIP. The framework is evaluated on PV module condition classification (clean, soiling, snow, hail, and bird droppings) using visible images, cell crack detection using EL images, and hotspot detection using IR images. GPT-5.1 in few-shot mode achieves the best performance, with classification accuracy exceeding 97.3%. Open-source models such as Qwen and CLIP also deliver competitive results on visible images (around 90% accuracy), though their performance is more limited on EL and IR modalities. On the full ELPV dataset, the framework achieves 83.5% zero-shot accuracy, within 2.8% of the supervised CNN baseline, confirming scalability to larger benchmarks. Practical aspects such as reproducibility, response latency, and confidence estimation are systematically analyzed. The framework operates across PV image modalities without modality- or task-specific training, making it well suited as a rapid pre-screening tool to support downstream detailed diagnostics. A benchmark dataset of diverse labeled PV images is also released.

Li, Baojie↗
DOE OSTI2019

Modeling of inter- and intra-edge-localized mode tungsten erosion during DIII-D H-mode discharges

The relationship between the tungsten gross erosion and the ELM characteristics is investigated for high performance (H-mode) discharges during the dedicated Metal Rings Campaign in DIII-D, using the one-dimensional ‘free-streaming’ ELM model, coupled to a simple analytical TRIM.SP sputtering model, while the OEDGE code is employed to calculate the inter-ELM impurity distribution and tungsten gross erosion. A carbon-tungsten mixed target material is used for both inter- and intra-ELM simulations. The OEDGE results reveal that the inter-ELM tungsten gross erosion rate is not sensitive to the carbon fraction on the tungsten surface layer; a wider range of carbon fractions from 0.3 to 0.6 give similar tungsten gross erosion profiles and match the diagnostic data, which is consistent with the simple analytical model. However, the intra-ELM simulation indicates that the value of surface carbon fraction can be as low as 0.3 to reproduce the measured tungsten gross erosion during ELMs, based on the effective ionizations/photon (S/XB) value of WI emissions. Finally, for both inter- and intra-ELM cases, carbon is predicted to dominate the tungsten erosion. However, in contrast to the inter-ELM tungsten erosion, which is dominated by locally redeposited C 2+ , the energetic C 6+ originating from the pedestal can contribute substantial tungsten erosion in the near-separatrix region during ELMs, and the width of this C 6+ dominated region exhibits a negative correlation with the heat flux density carried by ELMs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS2017

Investigating Sources of Ozone over California Using AJAX Airborne Measurements and Models: Assessing the Contribution from Long Range Transport

High ozone (O3) concentrations at low altitudes (1.5e4 km) were detected from airborne Alpha Jet Atmospheric eXperiment (AJAX) measurements on 30 May 2012 off the coast of California (CA). We investigate the causes of those elevated O3 concentrations using airborne measurements and various models. GEOS-Chem simulation shows that the contribution from local sources is likely small. A back trajectory model was used to determine the air mass origins and how much they contributed to the O3 over CA. Low-level potential vorticity (PV) from Modern Era Retrospective analysis for Research and Applications 2 (MERRA-2) reanalysis data appears to be a result of the diabatic heating and mixing of airs in the lower altitudes, rather than be a result of direct transport from stratospheric intrusion. The Q diagnostic, which is a measure of the mixing of the air masses, indicates that there is sufficient mixing along the trajectory to indicate that O3 from the different origins is mixed and transported to the western U.S.The back-trajectory model simulation demonstrates the air masses of interest came mostly from the mid troposphere (MT, 76), but the contribution of the lower troposphere (LT, 19) is also significant compared to those from the upper troposphere/lower stratosphere (UTLS, 5). Air coming from the LT appears to be mostly originating over Asia. The possible surface impact of the high O3 transported aloft on the surface O3 concentration through vertical and horizontal transport within a few days is substantiated by the influence maps determined from the Weather Research and Forecasting Stochastic Time Inverted Lagrangian Transport (WRF-STILT) model and the observed increases in surface ozone mixing ratios. Contrasting this complex case with a stratospheric-dominant event emphasizes the contribution of each source to the high O3 concentration in the lower altitudes over CA. Integrated analyses using models, reanalysis, and diagnostic tools, allows high ozone values detected by in-situ measurements to be attributed to multiple source processes.

Ryoo, Ju-Mee↗
DOE OSTI2025

Optimizing Simulation Fidelity in Direct-Drive Inertial Confinement Fusion with Cassio

Recently, the National Ignition Facility (NIF) demonstrated that inertial confinement fusion (ICF) is capable to achieve thermonuclear (TN) ignition in the laboratory, making it a crucial method on the path to replicate the Sun’s power production mechanism on Earth. However, the physics governing the high-energy density environments is very complex and remains a challenge to fully understand and model. For example, dopants in the TN fuel are important diagnostic tools to extract the thermodynamic conditions of the plasma. However, if their concentration is chosen too high, they can significantly degrade the performance of an ICF capsule. In this study, we use the Los Alamos National Laboratory radiation-hydrodynamics code Cassio to model ICF implosions of capsules which contain deuterium fuel with high-Z dopants like Krypton and Argon from the high-Z campaign conducted 15 years ago. We focus on how chosen computational and physics parameters influence the implosion outcomes. By systematically changing the resolution of the computational mesh and the photon energies as well as modifying settings for the laser drive and TN fuel pre-heat effects, we assess the impact on experimentally measured performance metrics like neutron production from TN burn and x-ray emission during the implosion. Our results will help to improve the fidelity of simulations and guide future numerical studies and experimental designs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

PINN surrogate of Li-ion battery models for parameter inference, Part I: Implementation and multi-fidelity hierarchies for the single-particle model

To plan and optimize energy storage demands that account for Li-ion battery aging dynamics, techniques need to be developed to diagnose battery internal states accurately and rapidly. Here, this study seeks to reduce the computational resources needed to determine a battery's internal states by replacing physics-based Li-ion battery models - such as the single-particle model (SPM) and the pseudo-2D (P2D) model - with a physics-informed neural network (PINN) surrogate. The surrogate model makes high-throughput techniques, such as Bayesian calibration, tractable to determine battery internal parameters from voltage responses. This manuscript is the first of a two-part series that introduces PINN surrogates of Li-ion battery models for parameter inference (i.e., state-of-health diagnostics). In this first part, a method is presented for constructing a PINN surrogate of the SPM. A multi-fidelity hierarchical training, where several neural nets are trained with multiple physics-loss fidelities is shown to significantly improve the surrogate accuracy when only training on the governing equation residuals. The implementation is made available in a companion repository (https://github.com/NREL/PINNSTRIPES). The techniques used to develop a PINN surrogate of the SPM are extended in Part II for the PINN surrogate for the P2D battery model, and explore the Bayesian calibration capabilities of both surrogates.

25 ENERGY STORAGE↗
NASA NTRS1993

An expanded set of brown dwarf and very low mass star models

We present in this paper updated and improved theoretical models of brown dwarfs and late M dwarfs. The evolution and characteristics of objects between 0.01 and 0.2 solar mass are exhaustively investigated and special emphasis is placed on their properties at early ages. The dependence on the helium fraction, deuterium fraction, and metallicity of the masses, effective temperature and luminosities at the edge of the hydrogen main sequence are calculated. We derive luminosity functions for representative mass functions and compare our predictions to recent cluster data. We show that there are distinctive features in the theoretical luminosity functions that can serve as diagnostics of brown dwarf physics. A zero-metallicity model is presented as a bound to or approximation of a putative extreme halo population.

Burrows, A.↗