Radiative Model Research Articles

The Modeling of Pulsar Magnetosphere and Radiation

We review the recent advances in the pulsar high-energy γ-ray observation and the electrodynamics of the pulsar magnetospheres from the early vacuum model to the recent plasma-filled models by numerical simulations. The numerical simulations have made significant progress toward the self-consistent modeling of the plasma-filled magnetosphere by including the particle acceleration and radiation. The current numerical simulations confirm a near force-free magnetosphere with the particle acceleration in the separatrix near the light cylinder and the current sheet outside the light cylinder, which can provide a good match to the recent high-energy γ-ray observations. The modeling of the combined multi-wavelength light curves, spectra, and polarization are expected to provide a stronger constrain on the geometry of the magnetic field lines, the location of the particle acceleration and the emission region, and the emission mechanism in the pulsar magnetospheres.

Characterization of human extreme heat exposure using an outdoor thermal manikin

Extreme heat is a current and growing global health concern. Current heat exposure models include meteorological and human factors that dictate heat stress, comfort, and risk of illness. However, radiation models simplify the human body to a cylinder, while convection ones provide conflicting predictions. To address these issues, we introduce a new method to characterize human exposure to extreme heat with unprecedented detail. We measure heat loads on 35 body surface zones using an outdoor thermal manikin (“ANDI”) alongside an ultrasonic anemometer array and integral radiation measurements (IRM). We show that regardless of body orientation, IRM and ANDI agree even under high solar conditions. Further, body parts can be treated as cylinders, even in highly turbulent flow. This geometry-rooted insight yields a whole-body convection correlation that resolves prior conflicts and is valid for diverse indoor and outdoor wind flows. Results will inform decision-making around heat protection, adaptation, and mitigation.

Radiation and heat transport in divergent shock–bubble interactions

Shock–bubble interactions (SBIs) are important across a wide range of physical systems. In inertial confinement fusion, interactions between laser-driven shocks and micro-voids in both ablators and foam targets generate instabilities that are a major obstacle in achieving ignition. Experiments imaging the collapse of such voids at high energy densities (HED) are constrained by spatial and temporal resolution, making simulations a vital tool in understanding these systems. In this study, we benchmark several radiation and thermal transport models in the xRAGE hydrodynamic code against experimental images of a collapsing mesoscale void during the passage of a 300 GPa shock. We also quantitatively examine the role of transport physics in the evolution of the SBI. This allows us to understand the dynamics of the interaction at timescales shorter than experimental imaging framerates. We find that all radiation models examined reproduce empirical shock velocities within experimental error. Radiation transport is found to reduce shock pressures by providing an additional energy pathway in the ablation region, but this effect is small (∼1% of total shock pressure). Employing a flux-limited Spitzer model for heat conduction, we find that flux limiters between 0.03 and 0.10 produce agreement with experimental velocities, suggesting that the system is well-within the Spitzer regime. Higher heat conduction is found to lower temperatures in the ablated plasma and to prevent secondary shocks at the ablation front, resulting in weaker primary shocks. Finally, we confirm that the SBI-driven instabilities observed in the HED regime are baroclinically driven, as in the low energy case.

Global Solar Radiation and Its Interactions with Atmospheric Substances and Their Effects on Air Temperature Change in Ankara Province

On the analysis of solar radiation and meteorological variables measured in Ankara province in Türkiye from 2017 to 2018, an empirical model of global solar radiation was developed. The global solar radiation at the ground and at the top of the atmosphere (TOA) was calculated and in good agreement with the observations. This model was applied to compute the losses of global solar radiation in the atmosphere and the contributions by atmospheric absorbing and scattering substances. The loss of global solar radiation in the atmosphere was dominated by the absorbing substances. The sensitivity test showed that global solar radiation was more sensitive to changes in scattering (described by a scattering factor S/G, S and G are diffuse and global solar radiation, respectively) than to changes in absorption. This empirical model was applied to calculate the albedos at the TOA and the surface. In 2017, 2018, and 2019, the computed albedos were 28.8%, 27.8%, and 28.2% at the TOA and 21.6%, 22.1%, and 21.9% at the surface, which were in reasonable agreement with satellite retrievals. The empirical model is a useful tool for studying global solar radiation and the multiple interactions between solar energy and atmospheric substances. The comparisons of global solar radiation and its loss in the atmosphere, as well as meteorological parameters, were made at some representative sites on the Earth. Some internal relationships (between G and the absorbing and scattering substances, air temperature and atmospheric substances, air temperature increase and latitude, etc.) were found. Thus, it is suggested to thoroughly study solar radiation, atmospheric substances, and climate change as a whole system and reduce the direct emissions of all atmospheric substances and, subsequently, secondary products (e.g., CO2 and non-CO2) in the atmosphere for the achievement of slowing down climate warming.

A Machine Learning Parameterization of Clouds in a Coarse‐Resolution Climate Model for Unbiased Radiation

AbstractCoarse‐grid weather and climate models rely particularly on parameterizations of cloud fields, and coarse‐grained cloud fields from a fine‐grid reference model are a natural target for a machine‐learned parameterization. We machine‐learn the coarsened‐fine cloud properties as a function of coarse‐grid model state in each grid cell of NOAA's FV3GFS global atmosphere model with 200 km grid spacing, trained using a 3 km fine‐grid reference simulation with a modified version of FV3GFS. The ML outputs are coarsened‐fine fractional cloud cover and liquid and ice cloud condensate mixing ratios, and the inputs are coarse model temperature, pressure, relative humidity, and ice cloud condensate. The predicted fields are skillful and unbiased, but somewhat under‐dispersed, resulting in too many partially cloudy model columns. When the predicted fields are applied diagnostically (offline) in FV3GFS's radiation scheme, they lead to small biases in global‐mean top‐of‐atmosphere (TOA) and surface radiative fluxes. An unbiased global‐mean TOA net radiative flux is obtained by setting to zero any predicted cloud with grid‐cell mean cloud fraction less than a threshold of 6.5%; this does not significantly degrade the ML prediction of cloud properties. The diagnostic, ML‐derived radiative fluxes are far more accurate than those obtained with the existing cloud parameterization in the nudged coarse‐grid model, as they leverage the accuracy of the fine‐grid reference simulation's cloud properties.

Temperature and density dependence of Kr L-shell spectrum in hot dense plasmas

Kr L-shell spectroscopy modeling results are discussed in this paper, focusing on the n = 4 to n = 2 line transitions of Be- and Li-like Kr ions. Collisional radiative atomic kinetic and Stark-broadened spectral line shape calculations show electron temperature Te and density ne sensitivity in the spectrum. The combination of the Te dependence due to the relative intensity of Be-like to Li-like line emissions in the range from 1.5 to 3 keV and the ne sensitivity from the Stark broadening effect on the line shapes in the range from 5×1023 to 2×1024/ cc results in a spectrum that can be employed to diagnose Te and ne. Two different collisional radiative atomic kinetic models i.e., Prismspect [J. J. MacFarlane, et al., Int. Fusion Sci. Appl. Conf. Proc. 457 (2003)] and ABAKO [Florido, et al., PRE, 80, 056402 (2009)] produce similar results in level populations and spectra. In x-ray spectroscopy of implosion cores, this Kr L-shell spectrum may prove useful in an intermediate Te range in which Ar is too ionized for its K-shell to be of diagnostic value and Kr is not ionized enough for its K-shell emission to be useful.

LeHaMoC: A versatile time-dependent lepto-hadronic modeling code for high-energy astrophysical sources

Context. Recent associations of high-energy neutrinos with active galactic nuclei (AGN) have revived the interest in leptohadronic models of radiation from astrophysical sources. The rapid increase in the amount of acquired multi-messenger data will require fast numerical models that may be applied to large source samples. Aims. We develop a time-dependent leptohadronic code, LeHaMoC, that offers several notable benefits compared to other existing codes, such as versatility and speed. Methods. LeHaMoC solves the Fokker-Planck equations of photons and relativistic particles (i.e. electrons, positrons, protons, and neutrinos) produced in a homogeneous magnetized source that may also be expanding. The code utilizes a fully implicit difference scheme that allows fast computation of steady-state and dynamically evolving physical problems. Results. We first present test cases where we compare the numerical results obtained with LeHaMoC against exact analytical solutions and numerical results computed with ATHEvA, a well-tested code of similar philosophy but a different numerical implementation. We find a good agreement (within 10–30%) with the numerical results obtained with ATHEvA without evidence of systematic differences. We then demonstrate the capabilities of the code through illustrative examples. First, we fit the spectral energy distribution from a jetted AGN in the context of a synchrotron-self Compton model and a proton-synchrotron model using Bayesian inference. Second, we compute the high-energy neutrino signal and the electromagnetic cascade induced by hadronic interactions in the corona of NGC 1068. Conclusions. LeHaMoC is easily customized to model a variety of high-energy astrophysical sources and has the potential to become a widely utilized tool in multi-messenger astrophysics.

Application of neural networks to synchro-Compton blazar emission models

Context. Jets from supermassive black holes at the centers of active galaxies are the most powerful and persistent sources of electromagnetic radiation in the Universe. To infer the physical conditions in the otherwise out-of-reach regions of extragalactic jets, we usually rely on fitting their spectral energy distributions (SEDs). The calculation of radiative models for the jet’s non-thermal emission usually relies on numerical solvers of coupled partial differential equations. Aims. In this work, we use machine learning to tackle the problem of high computational complexity to significantly reduce the SED model evaluation time, which is necessary for SED fittings carried out with Bayesian inference methods. Methods. We computed the SEDs based on the synchrotron self-Compton model for blazar emission using the radiation code ATHEvA. We used them to train neural networks (NNs) to explore whether they can replace the original code, which is computationally expensive. Results. We find that a NN with gated recurrent unit neurons (GRUN) can effectively replace the ATHEvA leptonic code for this application, while it can be efficiently coupled with Markov chain Monte Carlo (MCMC) and nested sampling algorithms for fitting purposes. We demonstrate this approach through an application to simulated data sets, as well as a subsequent application to observational data. Conclusions. We present a proof-of-concept application of NNs to blazar science as the first step in a list of future applications involving hadronic processes and even larger parameter spaces. We offer this tool to the community through a public repository.

SPH code development for X-pinch plasma simulation

We have developed the first smoothed particle hydrodynamics code for investigating X-pinch plasmas driven by pulsed power generators. To achieve the required code performance, we incorporated and discussed appropriate physics models capable of simulating the X-pinch phenomenon across various domains, encompassing equation of state, plasma transport, and radiation effects. The simulations were conducted in full three dimensions using our newly developed code, and we have compared and evaluated the results with experimental data obtained from the X-pinch device at Seoul National University. As a result, our simulations effectively captured the implosion behavior of X-pinch plasma, faithfully reproducing the four-step evolution process commonly observed in typical X-pinch configurations. Furthermore, it provided comprehensive spatiotemporal data on various plasma parameters, including density, temperature, velocity field, and radiated power. Notably, the electron temperature and density at the hot spot well agree with the experimental measurements, validating the accuracy and reliability of the developed simulation code. Additionally, the radiation data exhibited significantly improved accuracy compared to previous simulation results, confirming the effectiveness of the proposed radiation model, and it provides valuable insights into the X-pinch hot spot formation.

Full-radius integrated modelling of ASDEX Upgrade L-modes including impurity transport and radiation

An integrated framework that demonstrates multi-species, multi-channel modelling capabilities for the prediction of impurity density profiles and their feedback on the main plasma through radiative cooling and fuel dilution is presented. It combines all presently known theoretical elements in the local description of quasilinear turbulent and neoclassical impurity transport, using the models TGLF-SAT2 and FACIT. These are coupled to the STRAHL code for impurity sources and radiation inside the ASTRA transport solver. The workflow is shown to reproduce experimental results in full-radius L-mode modelling. In particular, a set of ASDEX Upgrade L-modes with differing heating power mixtures and plasma currents are simulated, including boron (B) and tungsten (W) as intrinsic impurities. The increase of predicted confinement with higher current and the reduction of core W peaking with higher central wave heating are demonstrated. Furthermore, a highly radiative L-mode scenario featuring an X-point radiator (XPR) with two intrinsic (B, W) and one seeded argon (Ar) species is simulated, and its measured radiated power and high confinement are recovered by the modelling. The stabilizing effect of impurities on turbulence is analysed and a simple model for the peripheral X-point radiation is introduced. A preliminary full-radius simulation of an H-mode phase of this same discharge, leveraging recent work on the role of the E×B shearing at the edge, shows promising results.

Influence of detailed in-depth radiation modeling on the computational predictions of liquid pool burning rates

Since thermal radiation substantially contributes to the flame heat feedback, a significant impact is anticipated for the in-depth radiation absorption in pool fires. This research focuses on investigating the influence of a detailed in-depth radiation absorption model on the accurate prediction of the flammability characteristics (i.e., ignition time and burning rate) of liquids in using computational fluid dynamics. First, we determined the radiative properties of hydrogenated tetrapropylene (TPH) (i.e., fuel used in the OECD PRISME project) using UV–Vis–NIR and FTIR spectroscopy and derived an expression for the depth-dependent absorption coefficient and average surface reflectivity. Then, a new approach was introduced for the modeling of in-depth radiation absorption. Subsequently, simulations were conducted for three test cases: heptane evaporation, pool fire, and spill fire scenarios involving both heptane and TPH. Results indicated mild effects of in-depth absorption modeling on heptane evaporation, negligible changes in heptane pool fires, and significant alterations in spill fires compared to the predictions with gray calculations. For all the studied cases except heptane pool fire, the ignition times decreased significantly. Sensitivity analysis revealed that the assumed source temperature had negligible influence on the mass loss rate predictions. The importance of the liquid’s Nusselt number (Nul) calculation varied between the studied scenarios.

Using of the Weibull distribution in developing global solar radiation forecasting models

AbstractIn this study, a solar radiation prediction model was developed using the Weibull distribution function (WDF). The main purpose of this study is to develop a new model for solar radiation (SR) estimation using the WDF and to bring this model to the literature. Although the WDF is widely used in wind energy forecasting due to its compatibility with wind speed data, it has not been used before in solar radiation forecasting model development. In this study, it is aimed to make SR estimation with the WDF for the first time. SR data for all regions where this new model was developed and its performance was examined were obtained from the General Directorate of Meteorology. In order to decide the success of these developed models, five different statistical metrics (RPE, MPE, MAPE, SSRE, and t‐stat) were discussed in the study. When the results are evaluated in general, it is seen that the new developed model has an acceptable performance. According to all test results in the region where the model was developed, it is seen that the new developed model showed the best performance with 0.0353, 0.4068, 7.1851, 0.1144, and 0.0162 values, respectively. The performance of this new developed model was observed in three different regions. When the statistical test results in these regions were examined, it was seen that the new model developed had a similar performance to the popular solar forecasting models widely used in the literature.

Combustion in a chamber furnace with a tangentially swirling vortex

Relevance. The need to analyze the furnace processes in boiler units with vertical vortex when arranging pulverized coal combustion with the enhancement of environmental parameters through the installation of tertiary blast nozzles. Despite the carbon-free policy in modern power engineering coal remains one of the main sources of energy, so the reconstruction of boiler units in order to reduce harmful emissions is very relevant. Aim. To study aerodynamics and combustion processes of pulverized coal fuel in the furnace chamber of a boiler unit with a tangential arrangement of burner devices using a combustion scheme with tertiary air blowing. Methods. The Eulerian–Lagrangian approach was applied to numerical study of flow characteristics, heat transfer and combustion in a furnace with a tangential burner arrangement. Also, k-ε model of gas turbulence, particle-turbulence interaction, diffusion model of particle dispersion, P-1 radiation modeling method and pulverized coal particle combustion model based on global particle kinetics and experimental data were used for numerical calculations. Results. Based on numerical calculations and analysis, the dependences of combustion product concentrations, temperature, hydrodynamics at combustion of Kuznetsky coal grade D in the furnace chamber with tangential arrangement of burners for brown coal, as well as at installation of tertiary blast nozzles have been obtained. Insufficient redistribution of air between burners and tertiary nozzles is revealed, as for maintenance of stable twist of vertical vortex and accordingly presence of high values of velocities at the outlet of burner devices it is not possible to increase the portion of tertiary air without reconstruction of burners. It is also established that the volume of the furnace chamber below the burners is poorly involved in heat exchange.

Heat Transfer through Double-Chamber Glass Unit with Low-Emission Coating

The numerical modeling of radiation and convective heat transfer through a double-chamber glass unit was carried out to substantiate the increase in the heat transfer resistance of this unit via the application of low-emission coatings to glass surfaces. In the space between the panes of a window without low-emission coatings, the amount of heat transferred via radiation exceeds the amount of heat transferred via thermal conductivity and convection. The question of the effect of low-emissivity coatings on reducing heat loss through a window has not yet been sufficiently studied. This problem is also not sufficiently reflected in the literature. In this regard, this paper presents the results of numerical simulation aimed at studying the effect of low-emissivity coatings on heat transfer through a double-chamber glass unit. Simulation is carried out by numerically solving a system of equations of fluid dynamics and energy for the air gap and glass. Boundary conditions of the fourth kind are set on the internal surfaces of the chambers, taking into account the radiation and conduction components of the total heat flux emanating from the glass. The results of modeling heat transfer through a glass unit with ordinary glass show that about 60% of the heat is transferred by radiation. Therefore, an effective measure to reduce heat loss through windows is to reduce the radiation component of the total heat flux by applying a low-emissivity coating to the internal surfaces of the glass unit. This allows for the reduction of the overall heat flux (and, accordingly, heat loss to the environment) by 20–34%, depending on the number of glass surfaces with such a coating.

Composite embedded track structure considering temperature dependent characteristics for rolling noise reduction of inter-city railway system

Intercity railway will generate strong noise when passing through the surrounding residents, among which rolling noise is the main noise source and is difficult to control. A composite embedded track structure containing polymer material was fabricated to analyze its damping and rolling noise reduction characteristics. The damping characteristics of polymer materials of embedded track were tested by dynamic thermo-mechanical analyzer (DMA Q800). The frequency response function (FRF) of the embedded track system is tested by force hammer percussion method. The vibration of the embedded track is simulated by the the 2.5-dimensional finite element method (2.5D FEM) considering damping characteristics obtained by material test of DMA Q800. The sound radiation model of embedded track is developed by using 2.5-dimensional sound boundary element method (2.5D BEM). The model is verified by the test. The FRF, track decay rate, and wheel-rail force at different temperatures are analyzed. With the decrease of temperature, the elastic modulus and loss factor of polymer material of embedded track increase, which will affect the above results. Sound directivity and effect on wheel-rail noise reduction of embedded track have been studied. The results show that the composite embedded track has good damping characteristics and noise reduction performance. Sound sensitivity analysis of loss factors of the three polymer materials of embedded track is carried out to improve embedded track noise reduction capability.

Radiative‐Recombination Thermodynamics in Boron‐Doped Diamond

AbstractBoron‐doped diamond is a wide‐bandgap semiconductor with excellent semiconductor properties, which is widely utilized in various applications. Till now, the thermodynamic rules governing the carrier transitions in this material have not been fully understood. In this research, the different luminescence behaviors of boron‐doped diamond under 193 nm pulse laser with high‐ and low‐ power density excitation are analyzed. Under high‐power density excitation (@≈63 kW cm−2), the emission intensity of excitons is nearly ten times higher than that of defect luminescence. Conversely, under low‐power density excitation (@≈1.4 kW cm−2, different emission peaks exhibit similar intensities, indicating a competitive relationship among them. Based on experimental and theoretical analyses, the difference is attributed to the thermodynamic distribution of carriers at varying excitation powers. Specifically, high excitation power brings an independent behavior of each emission peak, and the exciton emission is described by a phonon‐assisted radiation model; different from that, the competition among different emission centers under the condition of low excitation power cannot be neglected, and now the thermodynamic evolution of each emission peak is described by a carrier trapping‐dissociation model.

Dynamic simulation of a space lithium-cooled reactor system coupled with a He–Xe closed Brayton cycle

The lithium-cooled reactor with Brayton conversion power system mainly consists of fast reactor, intermediate heat exchanger, closed Brayton cycle (CBC) loops filled with Helium–Xenon (He–Xe) binary gas mixtures and heat rejection loop which radiate residual heat through heat pipes to outer space. In this study, a dynamic model of 100-kWe lithium-cooled reactor with Brayton conversion power system was established based on RESYS code, which include reactor core thermal-hydraulic model, six-group neutron kinetics model and decay heat model, heat exchanger model, Closed Brayton cycle model including turbine, compressor and rotating shaft, heat pipe radiator model etc. The nominal steady-state simulation is carried out to verify the correctness and accuracy of individual component model the integrated system model. Four typical transient conditions including accidental reactivity insertion, loss of coolant flow of primary loop, partial and total external load loss and a step reduction in the mass flow rate of heat rejection loop are simulated to analysis the transient characteristics and prove the safety features for those simulated scenarios. The results are helpful for the design, evaluation and operation of space liquid-lithium-cooled reactor power system with He–Xe closed Brayton cycle.

Forecasting first-year student mobility using explainable machine learning techniques

In the context of regional sciences and migration studies, gravity and radiation models are typically used to estimate human spatial mobility of all kinds. These formal models are incorporated as part of regression models along with co-variates, to better represent regional specific aspects. Often, the correlations between dependent and independent variables are of non-linear type and follow complex spatial interactions and multicollinearity. To address some of the model-related obstacles and to arrive at better predictions, we introduce machine learning algorithm class XGBoost to the estimation of spatial interactions and provide useful statistics and visual representations for the model evaluation and the evaluation and interpretation of the independent variables. The methods suggested are used to study the case of the spatial mobility of high-school graduates to the enrolment in higher education institutions in Germany at the county-level. We show that machine learning techniques can deliver explainable results that compare to traditional regression modeling. In addition to typically high model fits, variable-based indicators such as the Shapley Additive Explanations value (SHAP) provide significant additional information on the differentiated and non-linear effect of the variable values. For instance, we provide evidence that the initial study location choice is not related to the quality of local labor-markets in general, as there are both, strong positive and strong negative effects of the local academic employment rates on the migration decision. When controlling for about 28 co-variates, the attractiveness of the study location itself is the most important single factor of influence, followed by the classical distance-related variables travel time (gravitation) and regional opportunities (radiation). We show that machine learning methods can be transparent, interpretable, and explainable, when employed with adequate domain-knowledge and flanked by additional calculations and visualizations related to the model evaluation.

Analysis of seasonal variations and their impact on the microclimate of soilless glass greenhouses: Numerical and experimental investigations

This article presents a comprehensive examination of the interior environments in a soilless Greenhouse located in Tunis and their response to seasonal variations. The research employs a numerical model in conjunction with an experimental setup to achieve this objective. The model considers various elements, including glass, air, crops, and concrete in combination, to assess their impact on the indoor climate. Rigorous comparisons with experimental data collected from a greenhouse prototype, particularly regarding parameters like air velocity and temperature profiles, confirm the validity of the numerical findings. To closely replicate real conditions, the numerical model underwent optimization, incorporating turbulence and radiation models and undergoing a grid independence analysis. This article provides a thorough analysis of how seasonal fluctuations directly influence the microclimate within a soilless glass greenhouse, utilizing a combination of numerical and experimental data. Additionally, a series of numerical simulations were conducted to evaluate the potential impact of crop quantity on static indoor temperature. The comparative analysis revealed that the temperature difference at the roof level between scenarios with tomato and basil cultivation and those without cultivation was narrowed down to 3.5 K. Consequently, this study sheds light on the implications of seasonal fluctuations on soilless greenhouse climates and emphasizes the importance of accurate modeling and control to optimize agricultural practices in the northern regions of Tunisia.

Spin period evolution of Vela pulsar based on the wind emission: Application to the long period radio pulsars GPM J1839‐10 (P = 21 min) and GLEAM‐X J1627 (P = 18 min)

AbstractThe Vela pulsar is a young neutron star with spin period of P = 89 ms and a measured low braking index (˜1.4) that is much less than the standard value of 3 predicted by the magnetic dipole radiation (MDR) model; however, its spin period evolution has been a mystery. In this article, we assume that the spin‐down of the Vela pulsar is attributed to both MDR and wind flow (hereafter MDRW), and find that the ratio of wind flow to the magnetic dipole radiation is about 80%, which is higher than that of the Crab pulsar (25%). In other words, the spin‐down torque of the Vela pulsar is dominated by the wind flow. The spin period (P) evolution of the Vela pulsar depends on its real age, where its supernova remnant age is assumed to be an indicator of its true age, estimated from 10 to 20 kyr, and then we obtain their initial spin periods of ˜53.89 and ˜20.90 ms, respectively, which are consistent with the observed initial spin period ranges of young pulsars. Furthermore, we find that the Vela‐like pulsar by MDRW can evolve to the long spin period of a thousand of seconds in less than million years, which can conveniently help the astronomers understand the recently observed ultra‐long period radio pulsars like GPM J1839‐10 (P = 21 min), GLEAM‐X J1627 (P = 18 min), as well as PSR J0901+4046 (P = 76 s).