Energetic Particles Research Articles

Kappa-tail Technique: Modeling and Application to Solar Energetic Particles Observed by Parker Solar Probe

We develop the kappa-tail fitting technique, which analyzes observations of power-law tails of distributions and energy flux spectra, and connects them to theoretical modeling of kappa distributions, to determine the thermodynamics of the examined space plasma. In particular, we (i) construct the associated mathematical formulation; (ii) prove its decisive lead for determining whether the observed power-law is associated with kappa distributions; and (iii) provide a validation of the technique using pseudo-observations of typical input plasma parameters. Then, we apply this technique to a case study by determining the thermodynamics of solar energetic particle (SEP) protons, for an SEP event observed on 2021 April 17, by the Parker Solar Probe (PSP)/Integrated Science Investigation of the Sun instrument suite on board PSP. The results show SEP temperatures and densities of the order of ∼1 MeV and ∼5 × 10−7 cm−3, respectively.

Model for plasma transport due to drift waves based on mappings including finite Larmor radius

Abstract Turbulence in plasmas is modeled by fluctuating electric fields that determine particle motion through the E × B drift velocity which can lead to chaotic behavior. When applied to an ensemble of plasma particles in the chaotic regime their transport is studied: the anomalous plasma transport. The fluctuations are modeled by a spectrum of traveling waves with a wide frequency span which converts the equations of motion into an iterative mapping. The statistical properties of transport are derived. When the waves amplitude is small the particle orbits are regular, but as it is increased the behavior becomes increasingly chaotic. The effect of finite Larmor radius and the presence of a background plasma flow is also studied. We show that when a thermal population of particles is considered, the transport becomes non-local, as evidenced by a non-Gaussian particle distribution function (PDF). We have analyzed two different kinds of sheared flows: (1) a monotonic velocity shear and (2) a non-monotonic shear. The presence of transport barriers associated with the sheared velocity is also studied. We also present the application of the same techniques to study the transport of energetic particles that are born with a monoenergetic distribution.

Flat Spectra of Energetic Particles in Interplanetary Shock Precursors

The observed energy spectra of accelerated particles at interplanetary shocks often do not match the diffusive shock acceleration (DSA) theory predictions. In some cases, the particle flux forms a plateau over a wide range of energies, extending upstream of the shock for up to seven flux e-folds before submerging into the background spectrum. Remarkably, at and downstream of the shock we have studied in detail, the flux falls off in energy as ϵ −1, consistent with the DSA prediction for a strong shock. The upstream plateau suggests a particle transport mechanism different from those traditionally employed in DSA models. We show that a standard (linear) DSA solution based on a widely accepted diffusive particle transport with an underlying resonant wave–particle interaction is inconsistent with the plateau in the particle flux. To resolve this contradiction, we modify the DSA theory in two ways. First, we include a dependence of the particle diffusivity κ on the particle flux F (nonlinear particle transport). Second, we invoke short-scale magnetic perturbations that are self-consistently generated by, but not resonant with, accelerated particles. They lead to the particle diffusivity increasing with the particle energy as ∝ϵ 3/2 that simultaneously decreases with the particle flux as 1/F. The combination of these two trends results in the flat spectrum upstream. We speculate that nonmonotonic spatial variations of the upstream spectrum, apart from being time-dependent, may also result from non-DSA acceleration mechanisms at work upstream, such as stochastic Fermi or magnetic pumping acceleration.

On the Association of Substorm Identification Methods

AbstractSubstorms are a rapid release of energy that is redistributed throughout the magnetosphere‐ionosphere system, resulting in many observable signals, such as enhancements in the aurora, energetic particle injections, and ground magnetic field perturbations. Numerous substorm identification techniques and onset lists based on each of these signals have been provided in the literature, but often with no cross‐calibration. Since the signals produced are not necessarily unique to substorms and may not be sufficiently similar to be identified for each and every substorm, individual event lists may miss or misidentify substorms, hindering our understanding and the development and validation of substorm models. To gauge the scale of this problem, we use metrics derived from contingency tables to quantify the association between lists of substorms derived from SuperMAG SML/SMU indices, midlatitude magnetometer data, particle injections, and auroral enhancements. Overall, although some degree of pairwise association is found between the lists, even lists generated by applying conceptually similar gradient‐based identification to ground magnetometer data achieve an association with less than 50% event coincidence. We discuss possible explanations of the levels of association seen from our results, as well as their implications for substorm analyses.

MEMPSEP‐II. Forecasting the Properties of Solar Energetic Particle Events Using a Multivariate Ensemble Approach

AbstractSolar Energetic Particles (SEPs) form a critical component of Space Weather. The complex, intertwined dynamics of SEP sources, acceleration, and transport make their forecasting very challenging. Yet, information about SEP arrival and their properties (e.g., peak flux) is crucial for space exploration on many fronts. We have recently introduced a novel probabilistic ensemble model called the Multivariate Ensemble of Models for Probabilistic Forecast of Solar Energetic Particles (MEMPSEP). Its primary aim is to forecast the occurrence and physical properties of SEPs. The occurrence forecasting, thoroughly discussed in a preceding paper (MEMPSEP‐I by Chatterjee et al., 2024a, https://doi.org/10.1029/2023sw003568), is complemented by the work presented here, which focuses on forecasting the physical properties of SEPs. The MEMPSEP model relies on an ensemble of Convolutional Neural Networks, which leverage a multi‐variate data set comprising full‐disc magnetogram sequences and numerous derived and in‐situ data from various sources (MEMPSEP‐III by Moreland et al., 2024, https://doi.org/10.1029/2023SW003765). Skill scores demonstrate that MEMPSEP exhibits improved predictions on SEP properties for the test set data with SEP occurrence probability above 50%, compared to those with a probability below 50%. Results present a promising approach to address the challenging task of forecasting SEP physical properties, thus improving our forecasting capabilities and advancing our understanding of the dominant parameters and processes that govern SEP production.

MEMPSEP‐III. A Machine Learning‐Oriented Multivariate Data Set for Forecasting the Occurrence and Properties of Solar Energetic Particle Events Using a Multivariate Ensemble Approach

AbstractWe introduce a new multivariate data set that utilizes multiple spacecraft collecting in‐situ and remote sensing heliospheric measurements shown to be linked to physical processes responsible for generating solar energetic particles (SEPs). Using the Geostationary Operational Environmental Satellites (GOES) flare event list from Solar Cycle (SC) 23 and part of SC 24 (1998–2013), we identify 252 solar events (>C‐class flares) that produce SEPs and 17,542 events that do not. For each identified event, we acquire the local plasma properties at 1 au, such as energetic proton and electron data, upstream solar wind conditions, and the interplanetary magnetic field vector quantities using various instruments onboard GOES and the Advanced Composition Explorer spacecraft. We also collect remote sensing data from instruments onboard the Solar Dynamic Observatory, Solar and Heliospheric Observatory, and the Wind solar radio instrument WAVES. The data set is designed to allow for variations of the inputs and feature sets for machine learning (ML) in heliophysics and has a specific purpose for forecasting the occurrence of SEP events and their subsequent properties. This paper describes a data set created from multiple publicly available observation sources that is validated, cleaned, and carefully curated for our ML pipeline. The data set has been used to drive the newly‐developed Multivariate Ensemble of Models for Probabilistic Forecast of SEPs (MEMPSEP; see MEMPSEP‐I (Chatterjee et al., 2024, https://doi.org/10.1029/2023SW003568) and MEMPSEP‐II (Dayeh et al., 2024, https://doi.org/10.1029/2023SW003697) for accompanying papers).

Structural and phonon transport analysis of surface-activated bonded SiC-SiC homogenous interfaces

To avoid the interfacial thermal stress problem caused by high temperature, room temperature bonding techniques such as surface-activated bonding (SAB) are currently receiving widespread attention. However, the thermal boundary resistance (TBR) is challenging in reaching the theoretical value because the bombardment of the surface by energetic particle beams causes the formation of amorphous layers. In this paper, we have prepared SiC/SiC interfaces by surface-activated bonding and tried to explain the effect of the interfacial amorphous layer on the thermal properties. The results show that an amorphous layer of about 9 nm was formed at the SiC/SiC interface, mainly composed of carbon atoms. Molecular dynamics simulations derive an effective thermal boundary resistance (TBReff) of 4.78 m2K/GW for this interface, where the TBR of SiC/a-C is only approximately 0.50 m2K/GW. The TBReff with 30 % Fe after modification increased to 6.74 m2K/GW. The lower TBR between SiC/a-C can be attributed to coupling extended modes (EMs) and localized modes (LMs) at the interface and acting as a phonon bridge. In addition, the bulk thermal resistance of the amorphous layer accounts for 79.3 % of the TBReff. Besides, the molecular dynamics results show that the decrease in the thickness of the amorphous layer can significantly reduce the TBReff. As the thickness of the amorphous layer tends to zero, the TBReff is almost close to zero. The above conclusions will be beneficial to understanding the main factors influencing the thermal properties in the SiC/SiC interface, which point out the way for the subsequent improvement of the interfacial thermal conductivity.

MEMPSEP‐I. Forecasting the Probability of Solar Energetic Particle Event Occurrence Using a Multivariate Ensemble of Convolutional Neural Networks

AbstractThe Sun continuously affects the interplanetary environment through a host of interconnected and dynamic physical processes. Solar flares, Coronal Mass Ejections (CMEs), and Solar Energetic Particles (SEPs) are among the key drivers of space weather in the near‐Earth environment and beyond. While some CMEs and flares are associated with intense SEPs, some show little to no SEP association. To date, robust long‐term (hours‐days) forecasting of SEP occurrence and associated properties (e.g., onset, peak intensities) does not effectively exist and the search for such development continues. Through an Operations‐2‐Research support, we developed a self‐contained model that utilizes a comprehensive data set and provides a probabilistic forecast for SEP event occurrence and its properties. The model is named Multivariate Ensemble of Models for Probabilistic Forecast of Solar Energetic Particles (MEMPSEP). MEMPSEP workhorse is an ensemble of Convolutional Neural Networks that ingests a comprehensive data set (MEMPSEP‐III by Moreland et al. (2024, https://doi.org/10.1029/2023SW003765)) of full‐disc magnetogram‐sequences and in situ data from different sources to forecast the occurrence (MEMPSEP‐I—this work) and properties (MEMPSEP‐II by Dayeh et al. (2024, https://doi.org/10.1029/2023SW003697)) of a SEP event. This work focuses on estimating true SEP occurrence probabilities achieving a 2.5% improvement in reliability and a Brier score of 0.14. The outcome provides flexibility for the end‐users to determine their own acceptable level of risk, rather than imposing a detection threshold that optimizes an arbitrary binary classification metric. Furthermore, the model‐ensemble, trained to utilize the large class‐imbalance between events and non‐events, provides a clear measure of uncertainty in our forecast.

Numerical simulation of deuterium retention in tungsten under ELM-like conditions

Retention of hydrogen isotopes (HI) in plasma-facing components (PFCs) is a crucial process influencing the operation of a fusion device. The dynamics of HI retention is mainly determined by irradiation conditions of PFCs. These conditions can change due to the onset of fast transient events, such as edge-localised modes (ELMs). The development of ELMs results in repetitive short-term plasma bursts on PFCs, affecting the exposure regime. In this work, the effect of ELM-like loads on the fuel retention is numerically analysed using a one-dimensional diffusion model, implemented in the FESTIM code. As a representative simulation case, the deuterium (D) retention in tungsten (W) is considered with the geometry and inter-ELM exposure conditions relevant for large fusion devices. Temporal dependencies of heat and particle fluxes during intra-ELM stages are accounted for by applying the free-streaming model for an ELM filament transport. The simulations were conducted for three inter-ELM exposure regimes with various properties of transient loads, D trapping sites, and D recombination rates. Compared to the ELM-free irradiation, the onset of transients is shown to mainly reduce the D retention rate because of significant material heating induced by the arrival of energetic ELMy particles. This relative difference can decrease if the material is characterised by strong trapping sites or limited desorption from a surface. The findings also demonstrate that additional heating during transients provides conditions for a faster D migration into the bulk. In addition, we discuss the possibility of using ELM-average loads to obtain quick assessments of the D content. The approach is shown to be applicable for the case of small ELMs and is used to derive the analytical expressions for the D distribution in W within the steady-state approximation.

Overview of recent results from the ST40 compact high-field spherical tokamak

Abstract ST40 is a compact, high-field (BT0 ≤ 2.1T) spherical tokamak (ST) with a mission to expand the physics and technology basis for the ST route to commercial fusion. The ST40 research programme covers confinement and stability; solenoid-free start-up; high-performance operating scenarios; and plasma exhaust. In 2022, ST40 obtained a central deuterium ion temperatures of 9.6 ± 0.4 keV, demonstrating for the first time that pilot plant relevant ion temperatures can be reached in a compact, high-field ST. Analysis of these high-ion temperature plasmas is presented, including a summary of confinement, transport and microstability characteristics and energetic particle instabilities. Recent scenario development activities have focused on establishing diverted H-mode plasma discharges across a range of toroidal fields and plasma currents, along with scenarios with high non-inductive current fractions. In future operations, beginning in 2025, a 1MW dual frequency (104/137 GHz) electron cyclotron (EC) system will be installed to enable the study of EC and electron Bernstein wave plasma start-up and current drive. Predictive modelling of the potential performance of these systems is presented.

Solar Wind With Field Lines and Energetic Particles (SOFIE) Model: Application to Historical Solar Energetic Particle Events

AbstractIn this paper, we demonstrate the applicability of the data‐driven solar energetic particle (SEP) model, SOlar‐wind with FIeld‐lines and Energetic‐particles (SOFIE), to simulate the acceleration and transport processes of SEPs and make forecast of the energetic proton flux at energies ≥10 MeV that will be observed near 1 AU. The SOFIE model is built upon the Space Weather Modeling Framework developed at the University of Michigan. In SOFIE, the background solar wind plasma in the solar corona and interplanetary space is calculated by the Stream‐Aligned Aflvén Wave Solar‐atmosphere Model(‐Realtime) driven by the near‐real‐time hourly updated Global Oscillation Network Group solar magnetograms. In the background solar wind, coronal mass ejections (CMEs) are launched by placing an force‐imbalanced magnetic flux rope on top of the parent active region, using the Eruptive Event Generator using Gibson‐Low model. The acceleration and transport processes are modeled by the Multiple‐Field‐Line Advection Model for Particle Acceleration. In this work, nine SEP events (Solar Heliospheric and INterplanetary Environment challenge/campaign events) are modeled. The three modules in SOFIE are validated and evaluated by comparing with observations, including the steady‐state background solar wind properties, the white‐light image of the CMEs, and the flux of solar energetic protons, at energies of ≥10 MeV.

Ripple-induced neoclassical toroidal viscous torque in Augmented-First Plasma operation phase in ITER

Abstract A systematic calculation is performed on the ripple-induced neoclassical toroidal viscous (NTV) torque for new ITER scenarios designed for the Augmented-First Plasma (A-FP) operation phase with the full tungsten wall, where the plasma-wall gap is varied in view of mitigating the impact of tungsten wall-plasma interactions. The torque calculation includes drift kinetic response of the plasma thermal and energetic particles to the n = 18 (n is the toroidal harmonic number) ripple field. For the plasma scenario with ~45 cm plasma-wall gap at the outboard mid-plane and considering the corrected ripple level of 0.17% by the ferritic steel inserts, the computed net NTV torque acting on the plasma column is in the sub-Nm level. However, with decreasing the plasma-wall gap, the computed net NTV torque can reach a level comparable to that produced by the neutral-beam momentum injection in ITER. Ripple correction by ferritic inserts reduces the net torque by a factor of 3.3 for all the three A-FP scenarios considered. The n ω d = l ω b (with ω d and ω b being the toroidal precession and bounce frequencies of trapped particles, respectively, and l an integer number) type of resonance-enhancement of the NTV torque, due to thermal particles, is found to be weak in ITER despite high-n of 18. The same also holds for the ITER 10 MA steady state scenario from the D-T operation phase, where the aforementioned resonance associated with fusion-born alphas is also included. The ripple-induced NTV torque is well below that produced by the resonant magnetic perturbation applied for controlling the type-I edge-localized mode in ITER.

Validation study of RWM stability in DIII-D high-βN plasmas

Abstract The n = 1 (n is the toroidal mode number) resistive wall mode (RWM) stability is numerically investigated for two DIII-D high-β N discharges 176440 and 172461, utilizing the MARS-F (Liu et al 2000 Phys. Plasmas 7 3681) and MARS-K (Liu et al 2008 Phys. Plasmas 15 112503) codes. Systematic validation efforts are attempted, for the first time, for discharges with very slow or vanishing toroidal flow for a large fraction of the plasma volume. While gaining physics insights in accessing stable operation regime at β N exceeding the Troyon no-wall limit in these slow-rotation experiments, the predictive capability of fluid and non-perturbative magnetohydrodynamic-kinetic hybrid models for the RWM is further confirmed. The MARS-F fluid model, with a strong but numerically tunable viscosity mimicking ion Landau damping of parallel sound waves, finds complete stabilization of the n = 1 RWM in the considered DIII-D plasmas under the experimental flow conditions. Similarly, either full stabilization (for discharge 176440) or marginal stability (for discharge 172461) of the mode is computed by the MARS-K hybrid model, which is first-principle based without free model parameters. In particular, all drift kinetic resonances, including those of thermal and energetic particles, are found to synergistically act to marginally stabilize the RWM in discharge 172461. These MARS-F/K modeling results explain the experimentally observed stable operational regime in DIII-D, as far as the RWM stability is concerned. Extensive numerical sensitivity studies, with respect to the plasma toroidal flow speed as well as the radial location of the resistive wall, are also carried out to further support the validation study.

Unusual Forbush Decreases and Geomagnetic Storms on 24 March, 2024 and 11 May, 2024

As the current solar cycle 25 progresses and moves towards solar maxima, solar activity is increasing and extreme space weather events are taking place. Two severe geomagnetic storms accompanied by two large Forbush decreases in galactic cosmic ray intensity were recorded in March and May, 2024. More precisely, on 24 March 2024, a G4 (according to the NOAA Space Weather Scale for Geomagnetic Storms) geomagnetic storm was registered, with the corresponding geomagnetic indices Kp and Dst equal to 8 and −130 nT, respectively. On the same day, the majority of ground-based neutron monitor stations recorded an unusual Forbush decrease. This event stands out from a typical Forbush decrease because of its high amplitude decrease phase and rapid recovery phase, i.e., 15% decrease and an extremely rapid recovery of 10% within 1.5 h, as recorded at the Oulu neutron monitor station. Furthermore, on 10–13 May 2024, an unusual G5 geomagnetic storm (geomagnetic indices Kp = 9 and Dst = −412 nT) was registered (the last G5 storm had been observed in 2003). In addition, the polar neutron monitor stations recorded a Ground Level Enhancement (GLE74) during the recovery phase of a large Forbush decrease of 15%, which started on 10 May 2024. In this study, a detailed analysis of these two severe events in regard to the accompanying solar activity, interplanetary conditions and solar energetic particle events is provided. Moreover, the results of the NKUA “GLE Alert++ system”, the NKUA/IZMIRAN “FD Precursory Signals” method and the NKUA “ap Prediction tool” concerning these events are presented.

The timing of the ca-660 BCE Miyake solar-proton event constrained to between 664 and 663 BCE

Extreme solar energetic particle events, known as Miyake events, are rare phenomena observed by cosmogenic isotopes, with only six documented. The timing of the ca. 660 BCE Miyake event remains undefined until now. Here, we assign its occurrence to 664–663 BCE through new radiocarbon measurements in gymnosperm larch tree rings from arctic-alpine biomes (Yamal and Altai). Using a 22-box carbon cycle model and Bayesian statistics, we calculate the radiocarbon production rate during the event that is 3.2–4.8 times higher than the average solar modulation, and comparable to the 774–775 CE solar-proton event. The prolonged radiocarbon signature manifests a 12‰ rise over two years. The non-uniform signal in the tree rings is likely driven by the low rate of CO2 gas exchange between the trees and the ambient atmosphere, and the high residence time of radiocarbon in the post-event stratosphere. We caution about using the event’s pronounced signature for precise single-year-dating.

Unraveling the Origins of an Extreme Solar Eruptive Event with Hard X-Ray Imaging Spectroscopy

Hard X-ray (HXR) observations are crucial for understanding the initiation and evolution of solar eruptive events, as they provide a key signature of flare-accelerated electrons and heated plasma. The potential of high-cadence HXR imaging for deciphering the erupting structure, however, has not received adequate attention in an era of extreme ultraviolet (EUV) imaging abundance. An extreme solar eruptive event on 2022 September 5 observed on the solar far side by both Parker Solar Probe and Solar Orbiter provides the opportunity to showcase the power of HXR imaging in the absence of high-cadence EUV imaging. We investigate the evolution of flare energy release through HXR timing, imaging, and spectral analyses using data from the Spectrometer/Telescope for Imaging X-rays (STIX) on board Solar Orbiter. STIX provides the highest cadence imaging of the energy release sites for this far-side event and offers crucial insight into the nature of energy release, timing of flare particle acceleration, and evolution of the acceleration efficiency. We find that this is a two-phase eruptive event, rather than two distinct eruptions, as has been previously suggested. The eruption begins with an initial peak in flare emission on one side of the active region (AR), marking the rise/destabilization of a loop system followed by notable episodes of energy release across the AR and an eruptive phase associated with a very fast coronal mass ejection, type III radio bursts, and solar energetic particles. We demonstrate that high-cadence HXR imaging spectroscopy is indispensable for understanding the formation of powerful, space-weather relevant eruptions.

Polar lights optimizer: Algorithm and applications in image segmentation and feature selection

This study introduces Polar Lights Optimization (PLO), an algorithm based on the aurora phenomenon or polar lights. The aurora is a unique natural spectacle that occurs when energetic particles from the solar wind converge at the Earth's poles, influenced by the geomagnetic field and the Earth's atmosphere. By analyzing the motion of high-energy particles and delving into the underlying principles of physics, we propose a unique model for mimicking particle motion. This model integrates gyration motion and aurora oval walk, with the former facilitating local exploitation, while the latter enabling global exploration. By synergistically combining these two strategies, the proposed PLO achieves a balanced approach to local exploitation and global exploration. Additionally, a particle collision strategy is introduced to enhance the efficiency of escaping local optima. To evaluate the performance of PLO, a qualitative analysis experiment is designed to assess its ability to explore the problem space and search for solutions. PLO is compared against 9 classic algorithms and 8 high-performance algorithms using 30 benchmark functions from IEEE CEC2014. Furthermore, we compare and analyze PLO with the current state-of-the-art methods in the field, utilizing 12 benchmark functions from IEEE CEC2022. Subsequently, PLO is successfully applied to multi-threshold image segmentation and feature selection. Specifically, a PLO-based multi-threshold segmentation model and a binary PLO-based feature selection method are developed. The performance of PLO is also evaluated using 10 images from the Invasive Ductal Carcinoma (IDC) medical dataset, while the overall adaptability and accuracy of the feature selection model are tested using 8 medical datasets. These results affirm the emergence of PLO as an effective optimization tool ready for solving real-world problems, including those in the medical field. The source codes of PLO are available at https://aliasgharheidari.com/PLO.html and other websites.

Statistical Distributions of Plasma Density and Pressure in the Jovian Plasma Sheet

The Jovian plasma sheet is a key region of the Jovian magnetosphere populated by a mix of warm and hot plasma. It is the main channel for radial transport of mass and energy in the Jovian magnetosphere and provides a favorable environment for magnetic reconnection and wave–particle interactions although the understanding of its plasma properties is incomplete. This study combines observations from the Jovian Auroral Distributions Experiment and Juno Energetic Particle Detector Instrument on board the Juno spacecraft during its first 31 orbits to analyze the plasma properties of the Jovian plasma sheet from 20 R J to 100 R J. Our results indicate that the plasma number density decreases from 1 cm−3 at 20 R J to 0.005 cm−3 at 100 R J, while the plasma pressure decreases from 2 nPa at 20 R J to 0.02 nPa at 100 R J. The plasma pressure inside the plasma sheet is comparable to the magnetic pressure in the lobe region, suggesting a rough balance between the two. In the plasma sheet with r > 70 R J, the H+ density and pressure remain relatively constant, likely due to other plasma sources such as the solar wind. Additionally, we find that the pressure (density) ratios for heavy ions between the center and the edge of the plasma sheet are generally an order of magnitude, while that for H+ decreases with radial distance. These findings contribute to a more comprehensive understanding of the plasma properties of the Jovian plasma sheet.

Damage analysis of solid propellants with default defects based on macro-microscopic approach

Solid Rocket Motors (SRMs) rely on solid propellants, directly impacting the energy capacity of launch vehicles. High energy density material (HEDM) propellant exhibits superior energy density owing to the incorporation of a substantial quantity of energetic particles. However, the elevated particle fill ratio makes the formation of pores more prevalent during the manufacturing process of propellants. These pores, representing default defects, are indispensable factors in the investigation of mechanical properties of propellants. This study investigated default defects effects on HEDM propellants, analyzing both microscopic and macroscopic perspectives. Utilizing micro-CT imaging, the microstructure and default defects were characterized. Subsequently, using the cohesive zone model (CZM), microscopic damage evolution was depicted with the representative volume element (RVE) model, allowing in-depth analysis. Furthermore, a damage constitutive model, based on microscopic damage, was developed, with its softening function calibrated using microscopic damage evolution characteristics. Implemented into ABAQUS via user-defined material subroutine (UMAT), this model enabled the prediction of the mechanical response of HEDM propellants with different defects. The results demonstrate that the developed model accurately predicts the mechanical responses of HEDM propellants with different defects, showcasing the potential of macro-microscopic approaches in analyzing propellants with default defects.

Specularly reflected whistler: A low-latitude channel to couple lightning energy to the magnetosphere.

Lightning-generated whistlers profoundly affect the energetic particle population in Earth's radiation belts, influencing space weather and endangering astronauts and satellites. We report the discovery of specularly reflected (SR) whistler in which the lightning energy injected into the ionosphere at low latitudes reaches the magnetosphere after undergoing a specular reflection in the conjugate ionosphere, contradicting previous claims that lightning energy injected at low latitudes cannot escape the ionosphere. SR whistlers provide a low-latitude channel to transport lightning energy to the magnetosphere. We calculate the relative contributions of SR, magnetospherically reflected, subprotonospheric, and ducted whistlers to the lightning energy reaching the magnetosphere. When SR whistlers are considered, the global lightning energy contribution to the magnetosphere doubles, implying that the previous estimates of the impact of lightning energy on radiation belts may need substantial revisions. Whistler dispersion and intensity analyses quantitatively confirm our results and suggest new remote-sensing methods of the magnetosphere, ionosphere, Earth-ionosphere waveguide, and lightning flashes.