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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 919 records · Page 51
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Machine learning from RANS and LES to inform coarse grid simulations

Nuclear system thermal hydraulic analysis has historically relied on computationally inexpensive 1D codes. However, such tools are unable to capture multiscale multidimensional effects in large nuclear reactor enclosures. On the other hand, simulations with higher fidelity can be too expensive for such purposes. One of the ways to reduce computational cost is to perform simulations on a coarse grid, which, unfortunately, introduces large discretization errors. In this paper, two high-to-low data-driven approaches are investigated: (1) a coarse grid turbulence model to predict eddy viscosity and (2) correction of errors in coarse grid velocity fields. The approaches aim to reduce grid- and turbulence model-induced errors in coarse grid Reynolds-averaged Navier–Stokes (RANS) simulations. Two sources of high-fidelity data, RANS and large eddy simulations (LES), are explored. To extract the eddy viscosity from the LES data, an inverse optimization problem is solved. However, the LES eddy viscosity is shown to be comparable to the RANS eddy viscosity in terms of error reduction. Therefore, the directly available RANS eddy viscosity was used to develop a coarse grid data-driven turbulence model. Additionally, error correction in velocity is used to reduce the remaining uncertainties and bring the results closer to reality. In conclusion, the performance of the frameworks is demonstrated for a scaled upper plenum of a gas-cooled reactor facility.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Metasurface holographic optical traps for ultracold atoms

We propose metasurface holograms as a novel platform to generate optical trap arrays for cold atoms with high quality, efficiency, and thermal stability. We developed design and fabrication methods to create dielectric, phase-only metasurface holograms based on titanium dioxide. We experimentally demonstrated optical trap arrays of various geometries, including periodic and aperiodic configurations with dimensions ranging from 1D to 3D and up to a few hundred trap sites. We characterized the performance of the holographic metasurfaces in terms of the positioning accuracy, size and intensity uniformity of the generated traps, and power handling capability of the dielectric metasurfaces. Our proposed platform has great potential for enabling fundamental studies of quantum many-body physics, and quantum simulation and computation tasks. The compact form factor, passive nature, good power handling capability, and scalability of generating high-quality, large-scale arrays also make the metasurface platform uniquely suitable for realizing field-deployable devices and systems based on cold atoms.

42 ENGINEERING↗
DOE OSTI2024

Modern deep neural networks for Direct Normal Irradiance forecasting: A classification approach

The escalating energy demand and the adverse environmental impacts of fossil-fuel use necessitate a shift towards cleaner and renewable alternatives. Concentrated Solar Power (CSP) technology emerges as a promising solution, offering a carbon-free alternative for power generation. The efficiency and profitability of CSP depend on the Direct Normal Irradiance (DNI) component of solar radiation; hence, accurate DNI forecasting can help optimize CSP plants’ operations and performance. The unpredictable nature of weather phenomena, particularly cloud cover, introduces uncertainty into DNI projections. Existing DNI forecasting models use meteorological factors, which are both challenging to estimate numerically over short prediction windows and expensive to model through data at a sufficiently high spatial and temporal resolution. This research addresses the challenge by presenting a novel approach that formulates DNI prediction as a multi-class classification problem, departing from conventional regression-based methods. The primary objective of this classification framework is to identify optimal periods aligning with specific operational thresholds for CSP plants, contributing to enhanced dispatch optimization strategies. We model the DNI classification problem using four advanced deep neural networks – rectified linear unit (ReLU) networks, 1D residual networks (ResNets), bidirectional long short-term memory (BiLSTM) networks, and transformers – achieving accuracies up to 93.5% without requiring meteorological parameters.

14 SOLAR ENERGY↗
DOE OSTI2020

Characterization of multi-regime reaction zones in a piloted inhomogeneous jet flame with local extinction

In this study, gradient free regime identification (GFRI) is applied to 1D Raman/Rayleigh/LIF measurements of temperature and major species from the intermediate velocity case of the Sydney piloted inhomogeneous jet flame series to better understand the structure of reaction zones and the downstream evolution of multi-regime characteristics. The GFRI approach allows local reaction zones to be detected and characterized as premixed, dominantly premixed, multi-regime, dominantly non-premixed, or non-premixed flame structures, based on flame markers (mixture fraction, chemical mode, and heat release rate) derived from the experimental data. The statistics of chemical mode zero-crossings, which mark premixed reaction zones, and the relative populations of flame structures are shown to be sensitive to the state of mixing in the near field of the flame and to the level of local extinction farther downstream. Multi-regime structures, where premixed and non-premixed reaction zones occur in close proximity and both contribute to overall heat release, account for nearly half the total population at streamwise locations within the first several jet diameters. There is a rapid transition within the near field whereby the relative population of non-premixed and dominantly non-premixed structures grows from 0.05 to nearly 0.5, and the population of premixed and dominantly premixed structures decreases correspondingly as fluid entering the reaction zone becomes progressively fuel-rich. Local extinction and re-ignition bring a resurgence in premixed-type structures, many of which occur at fuel-lean conditions. There are also modest populations of multi-regime structures, having chemical mode zero-crossings at lean conditions, which would not exist in a fully burning jet flame.

42 ENGINEERING↗
DOE OSTI2026

Pressure-dependent kinetics of cyclopentene consumption

Recent experiments have uncovered deficiencies in the ability of current kinetic models for cyclopentane combustion to predict species profiles as a function of O2 concentration. One likely source of these discrepancies flows from the limited availability of relevant kinetic data for key functionalized intermediates, requiring the use of distant analogies to estimate their rates. This work fills this gap for cyclopentene, the most prominent C5 intermediate in low-temperature cyclopentane combustion. Ab initio transition-state-theory based master equation methods are used to calculate pressure-dependent rate constants across four potential energy surfaces (C5H8 + OH, C5H8 + HO2, C5H7, and C5H7 + O2). Potential energy surfaces are characterized at the CCSD(T)-F12/cc-pVDZ-F12//revDSD-PBEP86-D3BJ/def2-TZVPP level of theory. Pressure-dependent rate constants and branching fractions are determined via 1D master equation calculations. The results are used to analyze the competition for radicals between cyclopentene and cyclopentane in the intermediate temperature region, and to identify the dominant pathways flowing from these initiation channels. On the OH initiation surface, we find good agreement with recently published experimental rate constants at high temperature, and we elucidate the complex temperature dependence below 800 K, where 𝜋𝜋 addition becomes prominent. On the HO2 initiation surface, we find an interesting alternative route to bicyclic ether formation via well-skipping over the HO2 adduct well. On the cyclopentenyl radical surface, the major product is cyclopentadiene plus H. On the cyclopentenyl + O2 surface, we find that resonance stabilization largely prevents the allylic radical from undergoing oxidation, whereas the alkylic radical has a somewhat elevated propensity for oxidation pathways relative to cyclopentyl.

ab initio calculations↗
DOE OSTI2026

Climate-eutrophication-anoxia interactions in Late Glacial Soppensee, Switzerland: Forcings, non-linear responses and recovery

Combined effects of climate warming and anthropogenic nutrient loadings lead to lake eutrophication and anoxia globally. Because of chemical feedbacks, lakes under multiple stressors often respond in non-linear ways. However, it remains unclear whether climate change alone can lead to non-linear lake responses in the absence of anthropogenic nutrient disturbances. Here, we investigate the interactions between climate variability, nutrient cycling and trophic state changes, mixing regimes, anoxia and related chemical feedback in a small kettle-hole lake in Switzerland during Late Glacial times (15.2–12.6 cal ka BP), a period known for high-amplitude climate change in pre-anthropogenic times. After its formation during Heinrich Stadial 1 (>15 cal ka BP), Soppensee was oligotrophic and well-mixed. Soppensee became eutrophic and developed anoxia at 14.25 cal ka BP. Phosphorus (P) was released from sediments through the reductive dissolution of Fe-oxyhydroxides, fuelling eutrophication. Eutrophication lagged the Bølling warming (14.65 cal ka BP) by 400 years, suggesting that rising temperatures were not the trigger for eutrophication. Instead, eutrophication responded non-linearly to forest closure (threshold at 76 % arboreal pollen AP), which shielded Soppensee from wind mixing, enhancing lake stratification, anoxia and P release, intensifying eutrophication. These conditions ended during the 200-years cold period of the Aegelsee Oscillation (GI-1d, ca. 14.0 cal ka BP) when the landscape regionally opened (AP<76 %); the lake became well-mixed, oxygenated and P was efficiently sequestered. Throughout the Allerød (13.9–12.8 cal ka BP), enhanced Fe input prompted diagenetic vivianite formation, sequestering P in sediments, naturally remediating lake eutrophication despite closed forests, warm temperatures, lake stratification and anoxia.

Environmental sciences↗
DOE OSTI2025

The influence of ambient light spectrum (LED, INC, CFL, Xenon…) on the efficiency of perovskite indoor photovoltaic solar cells for Internet of Things (IoT) applications

This record provides a numerical investigation of a MAGeI₃-based perovskite solar cell with the structure FTO/TiO₂/MAGeI₃/Spiro-OMeTAD, evaluated for both outdoor and indoor light-harvesting applications using the SCAPS-1D simulator. Device performance is analyzed under AM 1.5G sunlight and several artificial light sources, including LED, incandescent, compact fluorescent lamp (CFL), flashlight, and xenon illumination. The study reports initial and optimized power conversion efficiencies and examines the influence of absorber layer thickness and bandgap on device performance under different lighting conditions. The results highlight the potential of MAGeI₃-based perovskite solar cells for indoor energy harvesting and low-power Internet of Things (IoT) applications.

14 SOLAR ENERGY↗
DOE OSTI2025

Finite domain solution of a hydraulic fracture in a permeable rock

In this work, we present a domain-based algorithm to simulate the propagation of a plane-strain hydraulic fracture in a zero-toughness permeable elastic medium. The algorithm utilizes a domain-based method to solve the elasticity equation and integrates a multi-scale tip asymptote, which is particular to hydraulic fractures, into this framework. This integration is key to accurately model the energy dissipation and the fluid leak-off in the fracture tip region. The algorithm combines a 2D finite volume method (FVM) for solving the elasticity equation with a 1D FVM for solving the nonlinear lubrication equation. Incorporating the far-field asymptotics and using a moving-mesh scheme reduces the computational burden while improving the accuracy of the scheme. The paper concludes with an analysis of the numerical results. This study demonstrates the potential of this domain-based approach for modeling hydraulic fractures in poroelastic media.

Domain-based method↗
DOE OSTI2020

A radiative transfer model for solar induced fluorescence using spectral invariants theory

Solar Induced chlorophyll Fluorescence (SIF) shows promise as an approach for estimating gross primary production (GPP) remotely. However, sun-target-sensor geometry and within-canopy absorption of SIF can alter the relationship between measured SIF and GPP, because sensors can only retrieve some unknown fraction of the total emitted SIF. Radiative transfer models that allow for variation in canopy structure and sensor angles are therefore needed to properly interpret SIF measurements. Spectral invariants allow decoupling of the wavelength-independent canopy structure and the wavelength-dependent leaf and soil spectrum in the radiative transfer process. Here we develop a simple analytical Fluorescence Radiative Transfer model based on Escape and Recollision probability (FluorRTER) to investigate the impact of canopy structure and sun-target-sensor geometry on SIF emissions. SIF simulations using the FluorRTER model agreed well the one-dimensional Soil-Canopy Observation of Photochemistry and Energy balance (SCOPE) model and the three-dimensional Fluorescence model with Weighted Photon Spread (FluorWPS) model. The fractional vegetation cover (FVC) and clumping effect have a large influence the SIF emission of 3D discontinuous canopies. For a moderate solar zenith angle (30°) and a clumped canopy (FVC?=?0.6), the difference between the directional observed SIF of a 3D discontinuous canopy and a 1D homogeneous canopy was as large as 43.2% and 38.4% for Photosystem I?+?II fluorescence at 685?nm and at 740?nm, respectively. By bridging the gap between observed SIF and total emitted SIF over 3D heterogeneous vegetation canopies, the FluorRTER model can assist with the angular normalization of SIF measurements and enable the more robust interpretation of how variations in SIF from directional and hemispherical in-situ, airborne and satellite observations relate to leaf and whole-canopy physiological processes.

Zeng, Yelu↗
DOE OSTI2025

Combining geometric-optical and spectral invariants theories for modeling canopy fluorescence anisotropy

The spectral invariants theory ( p -theory) has received much attention in the field of quantitative remote sensing over the past few decades and has been adopted for modeling of canopy solar-induced chlorophyll fluorescence (SIF). However, the spectral invariant properties (SIP) in simple analytical formulae have not been applied for modeling canopy fluorescence anisotropy primarily because they are parameterized in terms of leaf total scattering, which precludes the differentiation between forward and backward leaf SIF emissions. In this study, we have developed the canopy-SIP SIF model by combining geometric-optical (GO) theory to account for asymmetric leaf SIF forward and backward emissions at the first-order scattering and by modeling multiple scattering based on the p-theory, thus avoiding the dependence on radiative transfer models. The applicability of the model simulations especially over 3D heterogeneous canopies was improved by incorporating canopy structure through multi-angular clumping index, and by modeling single scattering from the four components of the scene in view according to the GO approach. The results show good consistency with both the state-of-the-art SIF models and multi-angular field SIF observations over grass and chickpea canopies. Further, the coefficient of determination (R²) between the simulated SIF and field measurements was 0.75 (red) and 0.74 (far-red) for chickpea, and 0.65 (both red and far-red) for grass. The average relative error was approximately 3% for 1D homogeneous scenes when comparing the canopy-SIP SIF model simulations to the SCOPE model simulations, and around 4% for the 3D heterogeneous scene when comparing to the LESS model simulations. The results indicate that the proposed approach for separating asymmetric leaf SIF emissions is a robust way to keep a balance between satisfactory simulation accuracy and efficiency. Model simulations suggest that neglecting the leaf SIF asymmetry can lead to an underestimation of canopy red SIF by 6.3% to 42.6% for various leaf biochemical and canopy structural parameters. This study presents a simple but efficient analytical approach for canopy fluorescence modeling, with potential for large-scale canopy fluorescence simulations.

3D heterogeneous structure↗
DOE OSTI2020

Crystal chemistry and phase equilibria of the CaO-½Ho 2 O 3 -CoO z system at 885 °C in air

Ini this work, the phase equilibrium diagram of the CaO-½Ho 2 O 3 -CoO z system was determined at 885 °C in air. This diagram offers compatibility relationships in the ternary oxide system that are essential for processing and for the understanding of properties of several thermoelectric phases in the system. Four three-phase regions and three solid solution tie-line regions were determined in the CaO-½Ho 2 O 3 -CoO z system. In the CaO-Ho 2 O 3 system, while a small solid solution region was identified for (Ho 1-x Ca x )O (3-z)/2 (0 ≤x ≤ 0.14), Ho was not present in the Ca site of CaO. Neither the reported Ho2CoO4 phase in the Ho 2 O-CoO z system nor the Ca-doped (Ho 1+x Ca1-x)CoO 4-z phase was present at 885 °C. No solid solution of the distorted perovskite, (Ho 1-x Cax)CoO 3-z , was established at this temperature. The CaO-CoO z system consists of two calcium cobaltate thermoelectric compounds. The 2D thermoelectric oxide, (Ca 3-x Ho x )Co 4 O 9-z (0 ≤x ≤ 0.5), has a misfit layered structure, and the 1D Ca 3 Co 2 O 6 consists of chains of alternating CoO 6 trigonal prisms and CoO 6 octahedra. Ca 3 Co 2 O 6 was found to be a stoichiometric compound. A comparison of the phase diagrams of the CaO -½ R 2 O 3 -CoO z (R = La, Nd, Eu, and Ho) systems is given.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

GaAs Thermophotovoltaic Patterned Dielectric Back Contact Devices with Improved Sub-Bandgap Reflectance

We demonstrate GaAs thermophotovoltaic (TPV) devices with a patterned dielectric back contact (PDBC) architecture, featuring a dielectric spacer between the semiconductor and back metal contact over most of the back surface for high reflectance, and metal point contacts over a smaller area for electrical conduction. In the TPV application, high sub-bandgap reflectance is needed to reflect unused sub-bandgap photons to the thermal emitter to minimize energy losses in this portion of the thermal spectrum. We explore different PDBC fabrication processes with SU-8 and SiO2 dielectric spacer layers to maximize sub-bandgap reflectance while minimizing series resistance to increase TPV conversion efficiency. We successfully demonstrate GaAs SU-8 PDBC TPV devices with 2200 degrees C blackbody-weighted sub-bandgap reflectance of 94.9% and 96.5% with and without a front metal grid, respectively. This is 0.7% and 2.3% (absolute) higher than the mean sub-bandgap reflectance of 94.2% for GaAs baseline TPV devices with 100% Au back contact with front metal grid. Lower sub-bandgap reflectance in TPV devices with front grids indicates the front grid induces light scattering leading to additional parasitic absorption in the TPV device. We also show that for higher contact coverage fractions, the PDBC reflectance cannot in general be treated by a linear interpolation using simple 1D transfer matrix method modeling and should be treated instead as a diffraction grating by solving Maxwell's equations in 3D.

energy storage↗
DOE OSTI2022

Effects of Absorber Near-Interface Compensation on Cd(Se,Te) Solar Cell Performance

Arsenic (As) has been shown to be an effective p-type dopant for CdTe, although high performance in As-doped devices remains difficult to achieve. Arsenic is prone to self-compensation in CdTe, as evidenced by the accumulation of dopant atoms in CdTe/Cd(Se,Te) near the interface with MgxZn1-xO (MZO). In this study, we use SCAPS 1D modeling software to investigate the effect of near-interface compensation, helping elucidate loss pathways in present-day As-doped devices and informing future growth directions. We consider three possible results of As accumulation: shallow donors, deep recombination centers, and a thin layer of excess acceptor accumulation. The reduction in near-interface carrier concentration caused by shallow donors is shown to improve open-circuit voltages (VOC), whereas deep levels are detrimental to all performance parameters. The thin charge layer affects capacitance-voltage (CV) measurements by reducing the depletion width while maintaining the same carrier concentration, replicating CV behavior that has been observed in actual devices. These results illustrate the importance of monitoring dopant accumulation within 100 nm of the interface, and suggest that reducing or eliminating the As concentration in this region would be beneficial. An undoped Cd(Se,Te) layer at the interface is suggested as a possible device structure to boost performance.

absorber↗
DOE OSTI2020

Combining fast magic angle spinning dynamic nuclear polarization with indirect detection to further enhance the sensitivity of solid-state NMR spectroscopy

Dynamic nuclear polarization (DNP) and indirect detection are two commonly applied approaches for enhancing the sensitivity of solid-state NMR spectroscopy. However, their use in tandem has not yet been investigated. With the advent of low-temperature fast magic angle spinning (MAS) probes with 1.3-mm diameter rotors capable of MAS at 40 kHz it becomes feasible to combine these two techniques. In this study, we performed DNP-enhanced 2D indirectly detected heteronuclear correlation (idHETCOR) experiments on 13 C, 15 N, 113 Cd and 89 Y nuclei in functionalized mesoporous silica, CdS nanoparticles, and Y 2 O 3 nanoparticles. The sensitivity of the 2D idHETCOR experiments was compared with those of DNP-enhanced directly-detected 1D cross polarization (CP) and 2D HETCOR experiments performed with a standard 3.2-mm rotor. Due to low CP polarization transfer efficiencies and large proton linewidth, the sensitivity gains achieved by indirect detection alone were lower than in conventional (non-DNP) experiments. Nevertheless, despite the smaller sample volume the 2D idHETCOR experiments showed better absolute sensitivities than 2D HETCOR experiments for nuclei with the lowest gyromagnetic ratios. Finally, for 89 Y, 2D idHETCOR provided 8.2 times better sensitivity than the 1 D 89 Y-detected CP experiment performed with a 3.2-mm rotor.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

On the instrument-dependent appearance of ion dissociation events in atom probe tomography mass spectra

The successful application of atom probe tomography (APT) relies on the accurate interpretation of the mass spectrum (i.e. m/z histogram) from a sample. Some materials yield mass spectra that are amenable to a straightforward peak assignment/ranging, however, there are many materials that produce mass spectra with features that defy simple interpretation. One such example is Ga 2 O 3 which yields mass spectra containing several broad and difficult to interpret features. Herein, we study the GaO 2+ → O 1+ + Ga 1+ dissociation and we explain how this dissociation process gives rise to broad and previously unassigned features in the mass spectrum. Trajectory simulations are performed for the dissociation reaction utilizing realistic electrostatic models and compared to experiments using commercially available straight flight and reflectron based local electrode (LE) APT instruments. It is shown that the appearance of these features is strongly dependent on the specific design of the time-of-flight (ToF) mass analyzer. Additionally, we explore how various experimental parameters can affect the appearance of the dissociation process in the one-dimensional (1D) mass spectrum and in the two-dimensional (2D) correlation histogram. While the focus of this work is on a particular dissociation process related to Ga 2 O 3 , the understanding gained in the course of these simulations and experiments should be applicable to the interpretation of dissociation processes in other materials.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

A comparative study on deep learning models for condition monitoring of advanced reactor piping systems

Advanced nuclear reactors offer innovative applications due to their portability, reliability, resiliency, and high capacity factors. To operate them on a wider scale, reducing maintenance life-cycle costs while ensuring their integrity is essential. Autonomous operations in advanced nuclear reactors using augmented Digital Twin (DT) technology can serve as a cost-effective solution by increasing awareness about the system’s health. A key component of nuclear DT frameworks is the condition monitoring of safety systems, such as piping-equipment systems, which involves acquiring and monitoring the plant’s sensor data. Here, this research proposes a condition monitoring methodology utilizing deep learning algorithms, such as multilayer perceptions (MLP) and convolutional neural networks (CNNs), to detect degradation and its severity in nuclear piping-equipment systems. Sensor signals are processed to obtain the power spectral density and the Short-Time Fourier transform, and feature extraction methodologies are proposed to develop degradation-sensitive data repositories. The performance of MLP, one-dimensional (1D) CNN, and 2D CNN within the proposed condition monitoring framework is compared using a finite element model of a 3D piping system subjected to seismic loads as the application case study. Various approaches, such as dropout, k-Fold validation, regularization, and early stopping of training the network, are investigated to avoid overfitting the models to the input sensor data. The predictive capability and computational capacity of the deep learning algorithms are also compared to detect degradation in the Z-pipe system of the Experimental Breeder Reactor II (EBRII). The Z-pipe system is subjected to harmonic excitations that represent normal operating loads, such as pump-induced vibrations. The findings of the study indicate that the proposed artificial intelligence (AI)-driven condition monitoring framework demonstrates superior prediction accuracies with a 2D CNN, whereas the MLP exhibits higher computational efficiency.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Automated control and optimization of laser-driven ion acceleration

The interaction of relativistically intense lasers with opaque targets represents a highly non-linear, multi-dimensional parameter space. This limits the utility of sequential 1D scanning of experimental parameters for the optimization of secondary radiation, although to-date this has been the accepted methodology due to low data acquisition rates. High repetition-rate (HRR) lasers augmented by machine learning present a valuable opportunity for efficient source optimization. Here, an automated, HRR-compatible system produced high-fidelity parameter scans, revealing the influence of laser intensity on target pre-heating and proton generation. A closed-loop Bayesian optimization of maximum proton energy, through control of the laser wavefront and target position, produced proton beams with equivalent maximum energy to manually optimized laser pulses but using only 60% of the laser energy. This demonstration of automated optimization of laser-driven proton beams is a crucial step towards deeper physical insight and the construction of future radiation sources.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

A field–particle correlation analysis of a perpendicular magnetized collisionless shock

Using the field–particle correlation technique, we examine the particle energization in a three-dimensional (one spatial dimension and two velocity dimensions; 1D-2V) continuum Vlasov–Maxwell simulation of a perpendicular magnetized collisionless shock. The combination of the field–particle correlation technique with the high-fidelity representation of the particle distribution function provided by a direct discretization of the Vlasov equation allows us to ascertain the details of the exchange of energy between the electromagnetic fields and the particles in phase space. We identify the velocity-space signatures of shock-drift acceleration of the ions and adiabatic heating of the electrons arising from the perpendicular collisionless shock by constructing a simplified model with the minimum ingredients necessary to produce the observed energization signatures in the self-consistent Vlasov–Maxwell simulation. We are thus able to completely characterize the energy transfer in the perpendicular collisionless shock considered here and provide predictions for the application of the field–particle correlation technique to spacecraft measurements of collisionless shocks.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗