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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 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

An introduction to neuromorphic computing and its potential impact for unattended ground sensors

Neuromorphic computers are hardware systems that mimic the brain’s computational process phenomenology. This is in contrast to neural network accelerators, such as the Google TPU or the Intel Neural Compute Stick, which seek to accelerate the fundamental computation and data flows of neural network models used in the field of machine learning. Neuromorphic computers emulate the integrate and fire neuron dynamics of the brain to achieve a spiking communication architecture for computation. While neural networks are brain-inspired, they drastically oversimplify the brain’s computation model. Neuromorphic architectures are closer to the true computation model of the brain (albeit, still simplified). Neuromorphic computing models herald a 1000x power improvement over conventional CPU architectures. Sandia National Labs is a major contributor to the research community on neuromorphic systems by performing design analysis, evaluation, and algorithm development for neuromorphic computers. Space-based remote sensing development has been a focused target of funding for exploratory research into neuromorphic systems for their potential advantage in that program area; SNL has led some of these efforts. Recently, neuromorphic application evaluation has reached the NA-22 program area. This same exploratory research and algorithm development should penetrate the unattended ground sensor space for SNL’s mission partners and program areas. Neuromorphic computing paradigms offer a distinct advantage for the SWaP-constrained embedded systems of our diverse sponsor-driven program areas.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Encoding Frequency Constraints in Preventive Unit Commitment Using Deep Learning With Region-of-Interest Active Sampling

With the increasing penetration of renewable energy, frequency response and its security are of significant concerns for reliable power system operations. Frequency-constrained unit commitment (FCUC) is proposed to address this challenge. Despite existing efforts in modeling frequency characteristics in unit commitment (UC), current strategies can only handle oversimplified low-order frequency response models and do not consider wide-range operating conditions. This paper presents a generic data-driven framework for FCUC under high renewable penetration. Here, deep neural networks (DNNs) are trained to predict the frequency response using real data or high-fidelity simulation data. Next, the DNN is reformulated as a set of mixed-integer linear constraints to be incorporated into the ordinary UC formulation. In the data generation phase, all possible power injections are considered, and a region-of-interest active sampling is proposed to include power injection samples with frequency nadirs closer to the UFLC threshold, which enhances the accuracy of frequency constraints in FCUC. The proposed FCUC is investigated on the IEEE 39-bus system. Then, a full-order dynamic model simulation using PSS/E verifies the effectiveness of FCUC in frequency-secure generator commitments.

42 ENGINEERING↗
DOE OSTI2020

A gravo-aeroelastically scaled wind turbine rotor at field-prototype scale with strict structural requirements

A new sub-scale field-prototype design solution is developed to realize the dynamics, structural response, and distributed loads (gravitational, aerodynamic, centrifugal) that are characteristic of a full-scale large, modern wind turbine rotor. Prior work in sub-scale wind turbine testing has focused on matching aerodynamic/aero-elastic characteristics of full-scale rotors at wind tunnel scale. However, large-scale rotor designs must expand beyond this limited set of scaling parameters for cost-effective prototyping and meet strict requirements for structural safety for field testing. Here, the challenge lies in producing a structural design meeting two competing objectives: novel scaling objectives that prescribe the sub-scale blade to have low mass and stiffness; and traditional structural safety objectives that drive the design to have higher stiffness and mass. A 20% gravo-aeroelastically scaled wind turbine blade is developed successfully that satisfies these competing objectives. First, it achieved close agreement for non-dimensional tip deflection and flap-wise blade frequency (both within 2.1%) with a blade mass distribution constrained to produce target gravitational and centrifugal loads. Second, the entire blade structure was optimized to ensure a safe, manufacturable solution meeting strict strength requirements for a testing site that can experience up to 45 m/s wind gusts. The prototype-scale blade was fabricated and successfully proof-load tested.

17 WIND ENERGY↗
DOE OSTI2020

TDCOSMO - IV. Hierarchical time-delay cosmography – joint inference of the Hubble constant and galaxy density profiles

The H0LiCOW collaboration inferred via strong gravitational lensing time delays a Hubble constant value of H0 = 73.3−1.8+1.7 km s−1 Mpc−1, describing deflector mass density profiles by either a power-law or stars (constant mass-to-light ratio) plus standard dark matter halos. The mass-sheet transform (MST) that leaves the lensing observables unchanged is considered the dominant source of residual uncertainty in H0. We quantify any potential effect of the MST with a flexible family of mass models, which directly encodes it, and they are hence maximally degenerate with H0. Our calculation is based on a new hierarchical Bayesian approach in which the MST is only constrained by stellar kinematics. The approach is validated on mock lenses, which are generated from hydrodynamic simulations. We first applied the inference to the TDCOSMO sample of seven lenses, six of which are from H0LiCOW, and measured H0 = 74.5−6.1+5.6 km s−1 Mpc−1. Secondly, in order to further constrain the deflector mass density profiles, we added imaging and spectroscopy for a set of 33 strong gravitational lenses from the Sloan Lens ACS (SLACS) sample. For nine of the 33 SLAC lenses, we used resolved kinematics to constrain the stellar anisotropy. From the joint hierarchical analysis of the TDCOSMO+SLACS sample, we measured H0 = 67.4−3.2+4.1 km s−1 Mpc−1. This measurement assumes that the TDCOSMO and SLACS galaxies are drawn from the same parent population. The blind H0LiCOW, TDCOSMO-only and TDCOSMO+SLACS analyses are in mutual statistical agreement. The TDCOSMO+SLACS analysis prefers marginally shallower mass profiles than H0LiCOW or TDCOSMO-only. Without relying on the form of the mass density profile used by H0LiCOW, we achieve a ∼5% measurement of H0. While our new hierarchical analysis does not statistically invalidate the mass profile assumptions by H0LiCOW – and thus the H0 measurement relying on them – it demonstrates the importance of understanding the mass density profile of elliptical galaxies. The uncertainties on H0 derived in this paper can be reduced by physical or observational priors on the form of the mass profile, or by additional data.Key words: gravitational lensing: strong / galaxies: general / galaxies: kinematics and dynamics / distance scale / cosmological parameters / cosmology: observations⋆ The full analysis is available at https://github.com/TDCOSMO/hierarchy_analysis_2020_public.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Constraining the release of Sn to the ambient melting point following shock loading using time-resolved x-ray diffraction

The formation of liquid following release from a shocked state governs the transition from spall to cavitation and the formation of ejecta in metals. In order to build physics-based models of these processes, it is necessary to critically evaluate the relative importance of kinetics and entropy generation during the release along with the accuracy of multiphase equations of state. Tin (Sn) has served as a testbed for a variety of experiments examining strength and ejecta due to its accessible melt boundary and solid–solid phase transitions. This work presents experiments examining the phase evolution of high purity Sn following the shock and release to ambient stress near the melting point. Sn is found to release to states between its ambient solidus and liquidus from approximately 19 to 33 GPa under uniaxial loading, with the two-phase region being characterized by a reduction in the intensity of the (220), (211) β -Sn doublet. Jetting experiments performed at 27–28 GPa exhibit comparable diffraction patterns with what is observed following the uniaxial release. The solid fractions of β-Sn in the ambient mixed phase region are found to decrease linearly with increasing shock stress as increasing liquid Sn is formed. Here, the results provide much needed information for interpreting measurements of dynamic strength at a high strain rate and experiments examining cavitation and shallow bubble collapse in Sn.

, spall↗
DOE OSTI2022

Spatiotemporal Metabolic Network Models Reveal Complex Autotroph-Heterotroph Biofilm Interactions Governed by Photon Incidences

Autotroph-heterotroph interactions are ubiquitous in natural environment and play a key role in controlling various essential ecosystem functions, such as production and utilization of organic matter, cycling of nitrogen, sulfur, and other chemical elements. Understanding how these biofilm metabolic interactions are constrained in space and time remains challenging because fully predictive models designed for this purpose are currently limited. Toward filling this gap, here we developed community metabolic network models for two autotroph-heterotroph biofilm consortia (termed UCC-A and UCC-O), which share a suite of common heterotrophic members but have a single distinct photoautotrophic cyanobacterium (Phormidesmis priestleyi str. ANA and Phormidium sp. OSCR) that provides organic carbon and nitrogen sources to support the growth of heterotrophic partners. After determining model parameters by data fitting using the spatiotemporal distributions of microbial abundances, we comparatively analyzed the resulting biofilm models to examine any fundamental differences in microbial interactions between the two consortia under the variation of key environmental variables: CO2 and photon levels. The UCC-A model predicted generally expected responses, i.e., the autotroph population increased in response to elevated levels of CO2 and photon, followed by increase in the heterotroph population. In contrast, the UCC-O model showed somewhat complicated dynamics, e.g., higher photon incidence rates resulted in the increase in autotroph population but decrease in heterotroph population due to the lowered provision of glucose from the autotroph. A further analysis showed that species coexistence was governed by the photon incidences rather than the carbon availability for UCC-O, which was the opposite for UCC-A.

Phalak, Poonam↗
DOE OSTI2021

Estimating the color lifetime of energetic quarks

Using a simple geometric framework with a realistic nuclear density distribution, we fit published HERMES data to determine fundamental properties of hadronization using the nuclear medium as a spatial analyzer. Our approach uses a fit to the transverse momentum broadening observable and the hadronic multiplicity ratio; the simultaneous fit to two different observables strongly constrains the outcome. Using the known sizes of the target nuclei, we extract the color lifetime, finding a z h -dependent range of values from 2 to 8 fm/c for these data. We also extract estimates for the qˆ transport coefficient characterizing the strength of the interaction between the quark and the cold nuclear medium, finding an average value of 0.035±0.011 GeV 2 /fm. With a three-parameter model we obtain satisfactory fits to the data with a goodness-of-fit parameter χ 2 /dof of 1.1 or less. In a secondary fit of the results from that model we independently find a value for the Lund String Model string tension of 1.00±0.05 GeV/fm. We evaluated the sensitivity for extracting quark energy loss and effective in-medium hadronic cross sections using four-parameter variants of the model, finding large uncertainties in both cases. Our results suggest that hadronic interaction of forming hadrons in the nuclear medium is the primary dynamical cause of meson attenuation in the HERMES data, with quark energy loss playing a more minor role.

Electron-ion collider↗
DOE OSTI2025

A new biogeochemical modelling framework (FLaMe-v1.0) for lake methane emissions on the regional scale: development and application to the European domain

This study presents a new physical-biogeochemical modelling framework for simulating lake methane (CH 4 ) emissions at regional scales. The new model, FLaMe-v1.0 (Fluxes of Lake Methane), rests on an innovative, computationally efficient lake clustering approach that enables the simulation of CH 4 emissions across a large number of lakes. Building on the Canadian Small Lake Model (CSLM) that simulates the lake physics, we develop a suite of biogeochemical modules to simulate transient dynamics of organic Carbon (C), Oxygen (O 2 ), and CH 4 . We first test the performance of FLaMe-v1.0 by analyzing physical and biogeochemical processes in two theoretical lakes with characteristics that can be considered representative for many lakes (an oligotrophic, deep lake driven by cold climate versus a eutrophic, shallow lake driven by warm climate). Next, we evaluate the model by comparing simulated and observed timeseries of CH 4 emissions in four well-surveyed lakes. We then apply FLaMe-v1.0 at the European scale to evaluate simulated diffusive and ebullitive lake CH 4 fluxes against in-situ measurements in both boreal and central European regions. Finally, we provide a first assessment of the spatio-temporal variability in CH 4 emissions from European lakes with a surface area comprised between 0.1–1000 km 2 (n= 108 407, total area = 1.33 × 105 km 2 ), indicating a total emission of 0.97 ± 0.23 Tg CH 4 yr −1 , with the uncertainty constrained by combining FLaMe-v1.0 and machine learning techniques. Moreover, 30 % and 70 % of these CH 4 emissions are through diffusive and ebullitive pathways, respectively. Annually averaged CH 4 emission rates per unit lake area during 2010–2016 have a South-to-North decreasing gradient, resulting in a mean over the European domain as 7.39 g CH 4 m −2 yr −1 . Our simulations reveal a strong seasonality (with ice-blocking effects accounted for) in European lake CH 4 emissions, with nearly ten times higher emissions during late summer than during winter. This pronounced seasonal variation highlights the importance of accounting for the sub-annual variability in CH 4 emissions to accurately constrain regional CH 4 budgets. In the future, FLaMe-v1.0 could be embedded into Earth System Models to investigate the feedback between climate warming and global lake CH 4 emissions.

Maisonnier, Manon [Free Univ. of Brussels (Belgium↗
DOE OSTI2021

Tonal Emergence: An agent-based model of tonal coordination

Humans have a remarkable capacity for coordination. Our ability to interact and act jointly in groups is crucial to our success as a species. Joint Action (JA) research has often concerned itself with simplistic behaviors in highly constrained laboratory tasks. But there has been a growing interest in understanding complex coordination in more open-ended contexts. In this regard, collective music improvisation has emerged as a fascinating model domain for studying basic JA mechanisms in an unconstrained and highly sophisticated setting. A number of empirical studies have begun to elucidate coordination mechanisms underlying joint musical improvisation, but these empirical findings have yet to be cached out in a working computational model. The present work fills this gap by presenting TonalEmergence, an idealized agent-based model of improvised musical coordination. TonalEmergence models the coordination of notes played by improvisers to generate harmony (i.e., tonality), by simulating agents that stochastically generate notes biased towards maximizing harmonic consonance given their partner’s previous notes. Here, the model replicates an interesting empirical result from a previous study of professional jazz pianists: feedback loops of mutual adaptation between interacting agents support the production of consonant harmony. The model is further explored to show how complex tonal dynamics, such as the production and dissolution of stable tonal centers, are supported by agents that are characterized by (i) a tendency to strive toward consonance, (ii) stochasticity, and (iii) a limited memory for previously played notes. TonalEmergence thus provides a grounded computational model to simulate and probe the coordination mechanisms underpinning one of the more remarkable feats of human cognition: collective music improvisation.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Collapsar Gamma-Ray Bursts Grind Their Black Hole Spins to a Halt

Abstract The spin of a newly formed black hole (BH) at the center of a massive star evolves from its natal value due to two competing processes: accretion of gas angular momentum that increases the spin and extraction of BH angular momentum by outflows that decreases the spin. Ultimately, the final, equilibrium spin is set by a balance between both processes. In order for the BH to launch relativistic jets and power aγ-ray burst (GRB), the BH magnetic field needs to be dynamically important. Thus, we consider the case of a magnetically arrested disk (MAD) driving the spin evolution of the BH. By applying the semianalytic MAD BH spin evolution model of Lowell et al. to collapsars, we show that if the BH accretes ∼20% of its initial mass, its dimensionless spin inevitably reaches small values,a≲ 0.2. For such spins, and for mass accretion rates inferred from collapsar simulations, we show that our semianalytic model reproduces the energetics of typical GRB jets,L jet ∼ 10 50 erg s −1 . We show that our semianalytic model reproduces the nearly constant power of typical GRB jets. If the MAD onset is delayed, this allows powerful jets at the high end of the GRB luminosity distribution,L jet ∼ 10 52 erg s −1 , but the final spin remains low,a≲ 0.3. These results are consistent with the low spins inferred from gravitational wave detections of binary BH mergers. In a companion paper by Gottlieb et al., we use GRB observations to constrain the natal BH spin to bea≃ 0.2.

Astronomy & Astrophysics↗
DOE OSTI2021

Testing $f(R)$ gravity with scale dependent cosmic void velocity profiles

Here, we study the impact of cosmological scale modifications to general relativity on the dynamics of halos within voids by comparing N-body simulations incorporating Hu-Sawicki f(R) gravity, with |f R0 | = 10 -6 and 10 -5 , to those of Λ CDM. By examining the radial velocity statistics within voids classified based on their size and density-profile, as “rising” (R-type) or “shell” (S-type), we find that halo motions in small R-type voids, with effective radius <15 Mpc/h, reveal distinctive differences between f(R) and Λ CDM cosmologies. To understand this observed effect, we study the linear and nonlinear fifth forces, and develop an iterative algorithm to accurately solve the nonlinear fifth force equation. We use this to characterize the Chameleon screening mechanism in voids and contrast the behavior with that observed in gravitationally collapsed objects. The force analysis underscores how smaller R-type voids exhibit the highest ratios of fifth force to Newtonian force, which source distinguishable differences in the velocity profiles and thereby provide rich environments in which to constrain gravity.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Sensitivity evaluation of the Kudryavtsev permafrost model

Modeling is an important way to assess current and future permafrost spatial distribution and dynamics, especially in data poor areas like the Arctic region. Here, we evaluate a physics-based analytical model, Kudryavtsev's active layer model, which is widely used because it has relatively few data requirements. This model was recently incorporated into a component modeling toolbox, allowing for coupled modeling of permafrost and geomorphic processes over geological timescales. However, systematic quantitative assessment of the influence of its controlling parameters on permafrost temperature and active layer thickness predictions has not been undertaken before. In this work, we investigate the sensitivity of the Kudryavtsev's active layer model by Monte Carlo simulations to generate probability distributions for input parameters and compare predictions with a comprehensive benchmark dataset of in-situ permafrost observations over entire Alaska. Predicted permafrost surface temperature is highly dependent on mean annual air temperature (r = 0.78 on average), annual temperature amplitude (–0.41), and winter-averaged snow thickness (0.30). Uncertainty of predicted permafrost temperature is relatively small (RMSE = 1 °C), when air temperature and snow depth are well constrained. Similarly, RMSE between simulated and observed ALT at stations is ~0.08 m. However, under given air temperature and snow conditions, soil water content bias can significantly affect modeled active layer thickness (RMSE = 0.1 m or 40% of the observed active layer thickness). If soil water content has a large bias, improvements in other parameters may not significantly improve the active layer predictions of the Kudryavtsev's model.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Layers Can Be Deceiving: A Hopping Model for Small Molecule Diffusion in TATB Crystal

Sorption of small molecule gases in materials can play a significant role in their long‐term stability and compatibility within multi‐material assemblies. While many material properties of the insensitive high explosive TATB (1,3,5‐triamino‐2,4,6‐trinitrobenzene) are well understood, very little is known regarding its permeability to gases. TATB crystal exhibits a graphitic‐like layered packing structure that evokes a mental schema in which the layers form nanoscopic channels, but it is unclear whether this structure promotes gas transport. Here, we use molecular dynamics (MD) simulations to predict transport of small molecules through TATB single crystal. An approach to fit classical force fields is developed to model TATB interactions with H 2 O, He, Ne, and Ar, which is then combined with steered MD to probe gas transport along selected directions in the crystal. We find that small molecule transport occurs via a hopping mechanism that exhibits distinct jumps between interstitial sites and is substantially faster normal to the layers as compared to through them. This result stems from the finding that intralayer junctions between adjacent TATB molecules are the most stable interstitial sites and that energetic barriers are lower for hopping between adjacent layers. An empirical model for diffusion rate based on the MD data shows that the rate decays exponentially with increasing molecular radius and is negligibly small for all molecules larger than He, including common atmospheric gases. These findings have implications for the interpretation of experiments that measure surface area, material response to extreme conditions, and are expected to help constrain models for material aging.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Mapping the Perseus galaxy cluster with XRISM: Gas kinematic features and their implications for turbulence

We present extended gas kinematic maps of the Perseus cluster based on a combination of five new XRISM/Resolve pointings observed in 2025 with four performance verification datasets from 2024, totaling a net exposure of 745 ks. To date, Perseus remains the only cluster that has been extensively mapped out to ≃0.7 r 2500 by XRISM/Resolve, while simultaneously offering sufficient spatial resolution to resolve gaseous substructures driven by mergers and active galactic nucleus (AGN) feedback. Our observations cover multiple radial directions and a broad range of dynamical scales, enabling us to characterize the kinematic properties of the intracluster medium up to a scale of ∼500 kpc. In the measurements, we detected high-velocity dispersions (≃300km s −1 ) in the eastern region of the cluster that are spatially coincident with the extended X-ray surface brightness excess and correspond to a nonthermal pressure fraction of ≃7 − 13%. The velocity field outside the AGN-dominant region can be effectively described by a single, large-scale kinematic driver based on the velocity structure function, which statistically favors an energy injection scale of at least a few hundred kpc. The estimated turbulent dissipation energy is comparable to the gravitational potential energy released by a recent merger, implying a significant role of turbulent cascade in the merger energy conversion. In the bulk velocity field, we observed a dipole-like pattern along the east-west direction with an amplitude of ≃ ± 200 − 300 km s −1 , indicating rotational motions induced by the recent merger event. This feature constrains the viewing direction to ≃30° −50° relative to the normal of the merger plane. Our hydrodynamic simulations suggest that Perseus has experienced at least two energetic mergers since redshift z ∼ 1, the most recent of which is associated with the radio galaxy IC310, in agreement with recent SRG/eROSITA findings. This study showcases exciting scientific opportunities for future missions with high-resolution spectroscopic capabilities (e.g., HUBS, LEM, and NewAthena).

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

H 0 = 69.8 ± 1.3 km s - 1 Mpc - 1 , Ω m 0 = 0.288 ± 0.017 , and other constraints from lower-redshift, non-CMB, expansion-rate data

Here, we use updated Type Ia Pantheon+ supernova, baryon acoustic oscillation, and Hubble parameter (now also accounting for correlations) data, as well as new reverberation-measured C $\tiny{IV}$ quasar data, and quasar angular size, H $\tiny{II}$ starburst galaxy, reverberation-measured Mg $\tiny{II}$ quasar, and Amati correlated gamma-ray burst data to constrain cosmological parameters. We show that these data sets result in mutually consistent constraints and jointly use them to constrain cosmological parameters in six different spatially-flat and non-flat cosmological models. Our analysis provides summary model independent determinations of two key cosmological parameters: the Hubble constant, H 0 = 69.8 ± 1.3 km s -1 Mpc -1 , and the current non-relativistic matter density parameter, Ω m0 = 0.288 ± 0.017. Our summary error bars are 2.4 and 2.3 times those obtained using the flat ΛCDM model and Planck TT,TE,EE + lowE + lensing cosmic microwave background (CMB) anisotropy data. Our H 0 value is very consistent with that from the local expansion rate based on the Tip of the Red Giant Branch and Type Ia supernova (SN Ia) data, is 2σ lower than that from the local expansion rate based on Cepheid and SN Ia data, and is 2σ higher than that in the flat ΛCDM model based on Planck TT,TE,EE + lowE + lensing CMB data. Our data compilation shows at most mild evidence for non-flat spatial hypersurfaces, but more significant evidence for dark energy dynamics, 2σ or larger in the spatially-flat dynamical dark energy models we study.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Lyα Observations of Comet C/2013 A1 (Siding Spring) Using MAVEN IUVS Echelle

The close approach of comet C/2013 A1 (Siding Spring) to Mars in 2014 October provided a unique opportunity to observe a dynamically new Oort cloud comet with potential for interaction with a planet’s atmosphere. The water-originating hydrogen coma of the comet extended to over 20 million km from the nucleus. Determining the properties of this coma contributes to characterizing the comet’s water content and production rate. The present study analyzes a unique data set of high spectral resolution UV observations of comet C/2013 A1 Siding Spring measured by the Mars Atmosphere and Volatile Evolution spacecraft. The Siding Spring observations capture Lyα emissions from the Martian corona, the interplanetary medium, as well as the cometary H and D reservoirs. The isolated cometary spectra are analyzed to reveal a velocity distribution of H atoms that are consistent with model estimates of H{sub 2}O photodissociated H emissions and of OH photodissociated H emissions, Doppler shifted from the main comet H emission line center by 18 km s{sup −1} and 8 km s{sup −1}, respectively. The variations in comet H brightness with distance from the nucleus are used to constrain cometary water production to a rate of 0.5 × 10{sup 28} molecules s{sup −1} at a time when Siding Spring was at 1.5 au, pre-perihelion.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Observations of a plectonemic configuration in a stable magnetized plasma jet

Astrophysical jets are collimated high-speed outflows emerging from spinning and accreting matter around celestial objects and may spontaneously result from self-organized processes. Magnetic self-organization is commonly observed in laboratory plasma physics experiments; however, they require close-fitting flux conservers to constrain and stabilize the toroidal or cylindrical structures. Here we report the first observations of a long, stable, free-boundary plasma jet far from chamber walls, embedding a double-helix magnetic structure resembling a force-free plectonemic Taylor state. The jets arise from an experimental setup that mimics an accretion disk and has no close-fitting solid flux conserver. The results support the hypothesis that self-organization could be a universal, intrinsic explanation for jet formation, collimation, and stability and may help explain double-helix features in celestial observations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Improving estimates of sub-daily gross primary production from solar-induced chlorophyll fluorescence by accounting for light distribution within canopy

Solar-induced chlorophyll fluorescence (SIF) has long been regarded as a proxy for photosynthesis and has shown superiority in estimating gross primary production (GPP) compared to traditional vegetation indices, especially in evergreen ecosystems. However, current SIF-based GPP estimations regard the canopy as a large leaf and seldom consider the impact of interactions among light, canopy structure, and leaf physiology. In this study, we proposed GPP estimation models with different descriptions of light–structure–physiology interactions (including the layered model, the two-leaf model, and the layered two-leaf model) and compared their performances with the big-leaf model using half-hourly (or hourly) observations at evergreen needleleaf forest sites. First, we found that the big-leaf model underestimated GPP, especially at noon. All models showed higher accuracy than that of the big-leaf model. Second, we investigated the diurnal dynamics of GPP estimations in each canopy layer and found that models with a two-leaf assumption captured the diurnal variations in GPP better than that with the layered assumption. Here we also deduced that the poor performance of the big-leaf model was related to its overestimation of the overall light stress on the redox state of PSII reaction centers (qL). Finally, we noticed that the qL at the canopy scale had lower sensitivity to light change than the single-leaf qL and that the light response of canopy-scale qL was influenced by the leaf area index during seasonal cycles. Overall, this study describes methods to accurately estimate sub-daily GPP from SIF in evergreen needleleaf forests and demonstrates that the interactions among light, canopy structure, and leaf physiology regulate the SIF-GPP relationship at the canopy scale. Further, it indicates the need to consider the description of light distribution within the canopy in next-generation terrestrial biosphere models, even if they incorporate SIF to constrain their parameterization. Thus, upscaling the established leaf-scale mechanistic SIF-GPP relationship or findings to canopy-scale applications still requires much work, especially when there are significant changes in environmental conditions and their within-canopy distributions.

59 BASIC BIOLOGICAL SCIENCES↗