Flux Distribution Research Articles

AGN-201K educational and research reactor benchmark analyses by McCARD Monte Carlo calculations

In this study, a benchmark model for the AGN-201K educational and research reactor was newly developed based on its Final Safety Analysis Report data, with any unclear or missing specifications obtained from different AGN-201 reactors. The AGN-201K benchmark model was verified for criticality problems at various critical rod positions, the approach-to-criticality experiment problem, the fine rod worth measurement problem, and the flux distribution problem. The model was evaluated by comparing experimental values with calculated results by the McCARD Monte Carlo neutronic transport code, with the McCARD results of the AGN-201K benchmark showing good agreement with the experimental results. The most noteworthy point is that the recently developed McCARD TDMC (Time-Dependent Monte Carlo) transient module was successfully demonstrated through AGN-201K transient benchmark analyses. It is also noted that the reactor periods from McCARD results were very similar to the experimental results, confirming the suitability of TDMC analysis for realistic applications. Furthermore, the new AGN-201K benchmark model is expected to serve as a practical and useful tool for verifying and validating newly developed neutronic codes through various steady-state and transient analyses.

Heat flux partition based on onset of significant void

The thermal log-law Θ+(y+)=β+2.12log(y+) is valid in flow boiling with a value of β that evolves as the flow develops. Using a multiphase flow cross-literature database, this constant is shown to be βOSV=−7 at the point of onset of significant void (OSV). This means that at the OSV the liquid is at saturation temperature up to y+≃30. The OSV predictions using this model have a similar mean average error as the Saha and Zuber 1974 correlation for one less fitted constant for channel, pipe and annular flows for pressure from 1 to 147 bar and Peclet numbers from 3.5⋅103 to 4⋅105. This model is used to build a heat flux partitioning (HFP) inspired from system-scale codes (Lahey 1978). It predicts the distribution of the heat flux between the liquid phase and the evaporation term when the total heat flux is known. It does not give information on the total heat flux as a function of wall temperature and cannot be used to draw a boiling curve. In imposed flux conditions, this partition provides more coherent flux distribution between the evaporation and liquid terms than Kurul and Podowski (1990) based approaches and improves void fraction predictions in high-subcooling regions on the DEBORA database (Garnier et al. 2001) and on experiments by Bartolomei and Chanturiya (1967) and Bartolomei et al. (1982). When the wall temperature is imposed, it must be coupled with an empirical boiling total heat flux correlation to replace a traditional HFP. The prediction of the total heat flux is then as good as that of the correlation.

PERFORMANCE OF WATER COOLING FOR RADIATION HEAT FLUX FUEL STORAGE TANK

Full-surface fire on fuel storage tank emits high radiation heat transfer. As a fire protection strategy, the water curtain cooling system is activated to reduce the temperature on the adjacent tank surface. Therefore, the present work predicts and analyses the radiation heat flux and the maximum flame temperature of different types of fuels. Further, this analyses the effect of fuel total mass on radiation heat flux and maximum flame temperature and observes the effect of distance between two tanks on radiation heat flux distribution. The relationship between water cooling flow rate and outlet water temperature that absorbed radiation heat flux has been studied. The study has been conducted by using the Consequence modeling software trial version. The modeling setup of the tank is 17 m in height with 65 m inner diameter, and the meteorological data used are 5.4 m/s wind speed with north wind direction at atmospheric pressure in order to imitate the worst-case fire scenario. The results reveal that the gasoline fuel emitted the highest heat flux value of 11.03 kW/m2 and the raw gasoline sample emits the lowest heat flux value of 9.14 kW/m2. Furthermore, the total mass of the fuel shows no effect on the maximum flame temperature of 958.51°C. According to the findings, the critical tank distancing is 36 m and thus the appropriate tank distancing of 40 m is highly recommended by the standard. The result shows that the water cooling rate of 4.1 lpm/m2 is an excellent practice of water cooling to cool down the temperature of the fuel tank which is exposed to radiation heat flux.

Effect of the inclination angles of the capillary tube on the natural evaporation of absolute ethanol

Microchannel heat transfer plays an important role in microelectronics technology for heat dissipation, due to its high efficiency and low heat transfer temperature difference and flow resistance. To underpin the fundamental understanding of this technology, the natural evaporation process of absolute ethanol in a capillary tube at inclination angles ranging from 0° to 90° was investigated experimentally by exploring a spectrum of properties, such as Marangoni flow patterns, evaporation rate, heat flux, and temperature distribution. We found that the morphology of the meniscus is similar under different inclination angles, but the liquid and the tube wall slip to varying degrees due to the pressure difference at the liquid–vapor interface during evaporation. Therefore, the force distribution of the meniscus interface is different, and the resultant force is Fmax(60°) > Fmax(0°) > Fmax(30°) > Fmax(90°). We found that the morphology of the meniscus is independent of the inclination angle when absolute ethanol evaporates naturally. And the evaporation rate, heat flux and temperature distribution of meniscus at the initial stage of evaporation follow the law of resultant force distribution. That is, when the inclination angle is 60°, the evaporation rate and heat flux reach the maximum, i.e. 1.64 μm/s and 10.96 W/cm2, respectively, and the temperature between the center of the meniscus and the wedge region reaches 1.5 ℃. We used μ-PIV to observe the Marangoni vortex morphology of the vertical section of the meniscus, and found that there are different degrees of deformation at different inclination angles. When the inclination angle is 90°, the Marangoni vortex structure is destroyed.

Evaluation of effective kinetic parameters and adjoint flux distribution using iterated fission probability in the iMC Monte Carlo code

The iterated fission probability (IFP) method enables assessment of adjoint flux-weighted kinetic parameters, i.e., effective kinetic parameters, in Monte Carlo (MC) simulation, an essential capability in modern MC codes. This method can be extended to calculate adjoint flux-weighted quantities within a prescribed phase-space, enabling the estimation of adjoint flux distributions. The iMC Monte Carlo code, developed at the Korea Advanced Institute of Science and Technology (KAIST), is proficient in both calculating effective kinetic parameters and adjoint flux distributions. This paper presents benchmark results verifying the code’s capabilities. Critical device configurations are considered for evaluating kinetic parameters, compared with the Serpent2 code results. Both multi-group and continuous-energy benchmarks are solved to assess IFP-based spatial- and energy-wise adjoint flux distributions, and comparison is made against deterministic transport calculations. Results show that effective kinetic parameters can be accurately estimated, and acceptable adjoint flux distributions can be obtained using the iMC code.

Steady and transient analysis on thermal hydraulic characteristic of helical coiled once-through steam generator of liquid metal fast reactor

A transient model for thermal–hydraulic characteristics of helical coiled once-through steam generator (HCOTSG) of liquid metal fast reactor was established based on global discrete grid method. The model meshed the liquid metal circuit and water-steam circuit. Meanwhile, unsteady heat conduction equations were built to accurately simulate coupled heat transfer between two sides. Four-equation drift-flux method was adopt for water-steam flow. Taking lead–bismuth fast reactor as example, thermal–hydraulic characteristics of HCOTSG were first calculated under steady conditions. It was found that heat flux distribution along steam generator is extremely uneven, and the difference between maximum and minimum wall heat flux reaches hundreds of times. Then, the transient response was simulated when inlet conditions of primary side were perturbed by step changes, and it was found that maximum wall heat flux increases from 1175.5 kW/m2 to 1365 kW/m2, increasing by nearly 16 %, when inlet lead–bismuth temperature step increases from 450°C to 480 °C.

Insights into yeast response to chemotherapeutic agent through time series genome-scale metabolic models.

Organism-specific genome-scale metabolic models (GSMMs) can unveil molecular mechanisms within cells and are commonly used in diverse applications, from synthetic biology, biotechnology, and systems biology to metabolic engineering. There are limited studies incorporating time-series transcriptomics in GSMM simulations. Yeast is an easy-to-manipulate model organism for tumor research.Here, a novel approach (TS-GSMM) was proposed to integrate time-series transcriptomics with GSMMs to narrow down the feasible solution space of all possible flux distributions and attain time-series flux samples. The flux samples were clustered using machine learning techniques, and the clusters' functional analysis was performed using reaction set enrichment analysis.A time series transcriptomics response of Yeast cells to a chemotherapeutic reagent-doxorubicin-was mapped onto a Yeast GSMM. Eleven flux clusters were obtained with our approach, and pathway dynamics were displayed. Induction of fluxes related to bicarbonate formation and transport, ergosterol and spermidine transport, and ATP production were captured.Integrating time-series transcriptomics data with GSMMs is a promising approach to reveal pathway dynamics without any kinetic modeling and detects pathways that cannot be identified through transcriptomics-only analysis. The codes are available at https://github.com/karabekmez/TS-GSMM.

The Density and Ionization Profiles of Optically Dark and High-Redshift GRBs Probed by X-ray Absorption

The X-ray column density (NHX) of gamma-ray bursts (GRBs) can probe the local environment of their progenitors over a wide redshift range. Previous work has suggested an increasing trend as a function of redshift. The relevance of this current analysis relies on investigating the selection bias method, such as the effect of the X-ray spectrum in high-redshift GRBs, which complicates the measurement of small NHX; this has yet to be fully evaluated or discussed elsewhere. In this work, we evaluated these effects through simulations to define appropriate observational limits in the NHX versus redshift plane. We then applied a one-sided nonparametric method developed by Efron and Petrosian. Within the framework of this method, we investigated the redshift dependence of NHX and the local distribution function. Our results show that the evolution of NHX with redshift firmly exists with a significance of more than four sigma and follows a power law of (1+z)1.39(+0.22,−0.27). Based on these analyses and previous studies, the GRB progenitor mass varies but is more massive in the high-redshift environment and has a higher gas column density. This suggests that part of the luminosity evolution of GRBs, which has been widely reported, may be due to the evolution of the progenitor’s mass. Using the same method, we demonstrate that optically dark GRBs show a consistent evolution: (1+z)1.15(+0.67,−0.83). By applying the Kolmogorov–Smirnov (KS) test, it is shown that optically dark GRBs have statistically identical flux and photon index distributions compared to normal GRBs, but the NHX is systematically larger. This result suggests that the darkness of some GRB populations is not due to an intrinsic mechanism, but rather because a higher density surrounds them.

AA5754 aluminium alloy springback reduction by post forming electro plastic effect (PFEPE)

Post Forming Electro Plastic Effect (PFEPE) has been proposed as a promising technology for mitigating forming forces and addressing springback challenges in the metal forming industry. However, several research gaps remain unaddressed for the industrialization of this technology. Firstly, there is a lack of experimental validation regarding the impact of stress reduction on springback. Secondly, the potential effect of the skin-effect on the current metrics of stress reduction needs to be evaluated. Additionally, a post-forming electrically assisted elastoplastic material model is necessary for further technology development in stamping processes. This study tackles these challenges by utilizing AA5754H22 as a reference material and integrating a comprehensive experimental campaign with finite element numerical models and empirical material model developments. Our findings confirm that PFEPE facilitates a significant reduction in springback, achieving approximately a 100% reduction. Although the skin-effect introduces non-uniform current flux density distribution, its impact at the macroscopic level is negligible for the studied thin samples. While the numerical results of springback fails to accurately replicate experimental results, the developed material model aligns well with experimental trends.

On-load magnetic field calculation for linear permanent-magnet actuators using hybrid 2-D finite-element method and Maxwell–Fourier analysis

PurposeThe purpose of this study is to present a novel extended hybrid analytical method (HAM) that leverages a two-dimensional (2-D) coupling between the semi-analytical Maxwell–Fourier analysis and the finite element method (FEM) in Cartesian coordinates.Design/methodology/approachThe proposed model is applied to flat permanent-magnet linear electrical machines with rotor-dual. The magnetic field solution across the entire machine is established by coupling an exact analytical model (AM), designed for regions with relative magnetic permeability equal to unity, with a FEM in ferromagnetic regions. The coupling between AM and FEM occurs bidirectionally (x, y) along the edges separating teeth regions and their adjacent regions through applied boundary conditions.FindingsThe developed HAM yields accurate results concerning the magnetic flux density distribution, cogging force and induced voltage under various operating conditions, including magnetic or geometric parameters. A comparison with hybrid finite-difference and hybrid reluctance network methods demonstrates very satisfactory agreement with 2-D FEM.Originality/valueThe original contribution of this paper lies in establishing a direct coupling between the semi-analytical Maxwell–Fourier analysis and the FEM, particularly at the interface between adjacent regions with differing magnetic parameters.

Equal heat flux loading optimization approach for uniform wear of the wet brake

Due to their exceptional ability to endure heavy loads, cam-lobe radial-piston hydraulic motors are extensively utilized in heavy machinery. The wet brake is a key part capable of providing highly braking torque, which has numerous friction pairs and a compact structure. However, there exists a challenge in solving the issue of irrational pressure distribution which leads to non-uniform heat flux distribution and severe wear failure of the brake discs. For this, an innovative method to optimize the wet brake's loading structure has been developed to address the issue of non-uniform heat flux distribution. A thermomechanical coupling finite element (FE) model was established to establish a clear correlation between loading structure parameters and contact pressure distribution on the brake disc. An innovative equal heat flux criterion was introduced to guide the optimization process. Simulation results confirmed that the optimized loading structure achieved a brake disc contact pressure distribution aligned with the ideal heat flux density criteria. Experimental validation further demonstrated a notable reduction of up to 44.39 % in maximum wear depth (hmax) across different radii of the brake disc compared to the unoptimized structure. These findings underscore the efficacy of our approach in reducing wear rates and enhancing durability of the wet brakes.

Numerical modeling of alkali metal heat pipes

Heat pipe cooled reactors passively transfer heat from the core to the energy conversion system through alkali metal heat pipes. Further studies of the heat transfer characteristics of alkali metal heat pipes are needed to develop heat pipe cooled reactors. This work used a two-dimensional heat and mass transfer model of an alkali metal heat pipe. The flow field was validated against CFD predictions which showed that the model has less than 10 % errors in the velocity distribution and less than 5 % errors in the pressure distribution. A comparison of the predictions with experimental data in the literature indicated that the predicted wall temperature error was within 30 °C. This model was then used to analyze four factors that affect heat transfer in sodium heat pipes. The simulations show that higher heat fluxes shorten the startup time by approximately 70 % but significantly increase the operating temperature. The heat flux distribution significantly affects the evaporator temperature distribution. The heat transfer boundary condition on the condenser’s outer surface mainly affects the operating temperature and startup time. Increasing the heat pipe length-to-diameter ratio with a fixed heat flux increases the operating temperature with the increase proportional to the heat flux. This model provides accurate simulations of sodium heat pipes for various heat transfer boundary conditions. The simulations provide a reference for the selection of working conditions for heat pipe operation instability experiments.

Spatial Mapping of Soil CO2 Flux in the Yellow River Delta Farmland of China Using Multi-Source OpticalRemote Sensing Data

The spatial prediction of soil CO2 flux is of great significance for assessing regional climate change and high-quality agricultural development. Using a single satellite to predict soil CO2 flux is limited by climatic conditions and land cover, resulting in low prediction accuracy. To this end, this study proposed a strategy of multi-source spectral satellite coordination and selected seven optical satellite remote sensing data sources (i.e., GF1-WFV, GF6-WFV, GF4-PMI, CB04-MUX, HJ2A-CCD, Sentinel 2-L2A, and Landsat 8-OLI) to extract auxiliary variables (i.e., vegetation indices and soil texture features). We developed a tree-structured Parzen estimator (TPE)-optimized extreme gradient boosting (XGBoost) model for the prediction and spatial mapping of soil CO2 flux. SHapley additive explanation (SHAP) was used to analyze the driving effects of auxiliary variables on soil CO2 flux. A scatter matrix correlation analysis showed that the distributions of auxiliary variables and soil CO2 flux were skewed, and the linear correlations between them (r < 0.2) were generally weak. Compared with single-satellite variables, the TPE-XGBoost model based on multiple-satellite variables significantly improved the prediction accuracy (RMSE = 3.23 kg C ha−1 d−1, R2 = 0.73), showing a stronger fitting ability for the spatial variability of soil CO2 flux. The spatial mapping results of soil CO2 flux based on the TPE-XGBoost model revealed that the high-flux areas were mainly concentrated in eastern and northern farmlands. The SHAP analysis revealed that PC2 and the TCARI of Sentinel 2-L2A and the TVI of HJ2A-CCD had significant positive driving effects on the prediction accuracy of soil CO2 flux. The above results indicate that the integration of multiple-satellite data can enhance the reliability and accuracy of spatial predictions of soil CO2 flux, thereby supporting regional agricultural sustainable development and climate change response strategies.

Inverse problem for thermal radiation distribution on turbine blade under quartz lamp irradiation

Due to the strong time-varying characteristics and complex geometry of aerospace components, rapid changes in the distribution of radiative heat flux on the test surface are often required during non-uniform aerodynamic heating tests. However, it takes time to adjust the geometric parameters of the lamp array, which cannot meet the requirement for rapidly changing radiative heat flux distribution. To address this issue, a new method for calculating radiant heat flux and a fast linear analysis method of quartz lamp power are proposed which can calculate radiant heat flux distribution of complex surface and meet the need of timeliness and rapidity in radiant heat flux distribution, making it more suitable for engineering applications. Through numerical verification under single lamp and quartz lamp array, the maximum difference between the theoretical analysis method and the Monte Carlo method is less than 2.25% under single lamp, and less than 5% under quartz lamp array. Finally, turbine blade model and plane model are taken as research objects to verify the feasibility and reliability of the fast linear analysis method of quartz lamp power. The results show that the relative average error of the calculated quartz lamp power is 5.86% and 14.83%, respectively, compared with the actual power. This provides a reference and basis for the rapid simulation design of thermal radiation environment during the experiment.

Neutronic analysis of new generation TVS-2M fuel assemblies in VVER-1000 reactor type

The Russian fuel assembly TVS-2M is a newly proposed fuel configuration that contains gadolinium-oxide at different concentrations mixed with enriched UO2 at different U-235 enrichment values. The purpose of this study is to investigate the neutronic behavior of the Bushehr VVER-1000 reactor core by replacing the current standard Fuel Assemblies (FAs) called TVS with the new generation of TVS-2M FAs. In such manner, the reactor core was simulated under both modes of TVS-2M and TVS FAs arrangement using the WIMS, CITATION, MCNPX, and SuperMC codes in equal terms. Neutronic parameters of the reactor core such as effective multiplication factor, excess reactivity, neutron flux distribution, power peaking factor, and control rod worth are calculated and discussed within a comparative framework of both configurations of FAs; TVS and TVS-2M.

Tracing the physical signatures among the calculated global clear-sky spectral shortwave radiative flux distribution

This study utilized the high-spectral resolution radiative transfer model (MODerate resolution atmospheric TRANsmission, MODTRAN6.0.2.5) to compute global clear-sky shortwave (SW) radiative flux and compared it with NASA’s Clouds and the Earth’s Radiant Energy System (CERES) Synoptic Radiative Fluxes and Clouds (SYN1deg) product. The comparison revealed that the global distributions of clear-sky downwelling SW fluxes at the surface from the M6.0 calculations and SYN1 results are similar, with annual means of 246.51 Wm-2 and 242.42 Wm-2, respectively. Analysis further showed that most of the M6.0 calculations are slightly higher from low to mid-latitudes, particularly in the Northern Hemisphere (NH), but lower in higher latitudes compared to SYN1 results. However, these differences mostly fall within the CERES estimated uncertainty (6 Wm-2) of monthly mean clear-sky downwelling SW flux at the surface. The sensitivity of clear-sky SW/μ0 fluxes to changes in Precipitable Water Vapor (PWV), represented by the clear-sky water vapor radiative kernel, is about -0.7 Wm-2/(kgm-2) over oceans for both M6.0 and CERES SYN1 products, except for SYN1 results over the Southern Hemisphere (SH) ocean. Additionally, the zonal means of land coverage and SW/VIS/NIR albedos from M6.0 calculations indicate that VIS albedos are highest in polar regions (>60°), followed by SW and NIR albedos, while NIR albedos become highest from low to mid-latitudes (<60°). Generally, SW/VIS/NIR albedos and their differences increase monotonically with increased land coverage from 60°S to 60°N. The consistent clear-sky water vapor radiative kernels derived from both products exceeded our expectations, suggesting their potential use to trace physical signatures in climate model calculations. It is recommended that these model-derived radiative kernels should be validated by the long-term global and regional surface observations in order to enhance confidence to implement these radiative kernels in climate models.

Curvature-induced strain to realize differential lithiophilicity for selective lithium deposition and stable lithium anode

Regulating the lithiophilicity of three-dimensional (3D) lithium hosts is crucial for improving lithium deposition and suppressing dendrite growth. However, previous research has mainly focused on varying lithiophilic components, and the impact of geometric structures induced strain remains poorly understood. Herein, we present a novel curvature-induced strain engineering approach to regulate lithiophilicity and deposition kinetics of lithium in lightweight 3D tubular carbon hosts. A hollow carbon fiber with bilateral growth of MnO2 nanosheet arrays both inside and outside the tubes (MnO2@HCFC) have been successfully synthesized. Theoretical calculations and experiments confirm that the MnO2 layers inside and outside the hollow carbon fiber tube undergo compressive and tensile strain, respectively. The curvatures induced strain modifies the O2p band center of the lithiophilic MnO2 layer, enabling the regulation of lithiophilicity and preferential and uniform lithium deposition within the carbon fiber tubes. The MnO2@HCFC framework exhibits excellent lithium affinity and uniform Li+ flux distribution, as evidenced by visualization techniques and COMSOL simulations, enabling dendrite-free lithium deposition. The Li-MnO2@HCFC||LiCoO2 full cell retains 85.7 % of its capacity after 400 cycles at 0.5 C with a high LiCoO2 loading of 10.3 mg cm-2. The optimized lithium anode pouch cell exhibits robust cycle stability under harsh conditions. This work offers new insight into the design of 3D lithium hosts to enhance the performance of lithium anodes through curvature-induced strain engineering.

Light footprint of microalgae cultivation system addressed by modified Cornet model

The cultivation of microalgae is significantly influenced by light intensity and utilization efficiency. This study developed a modified Cornet (M−Cornet) model to assess the distribution of light intensity and flux in microalgae cultivation systems. Algal biofilm cultivation represents a more concentrated approach of algal suspension cultivation. Both follow the M−Cornet model and exhibit the same growth rates when cultured under identical conditions. Algal pigments and morphologies greatly impact the light absorption and scattering, resulting in light attenuation in intensity, penetration distance and light flux distribution. Algae varieties exhibit diverse light flux characteristics. 37% − 90% of the incident light is absorbed, of which, 80% to 90% is dissipated as heat. 10% to 63% of the incident light is scattered off the photobioreactor. The overall light utilization efficiency ranges 6% to 13%. The light footprint using the M−Cornet model offers valuable insights for photobioreactors designing and cultivation operating.

A Double Legendre Polynomial Order N Benchmark Solution for the 1D Monoenergetic Neutron Transport Equation in Plane Geometry

As more and more numerical and analytical solutions to the linear neutron transport equation become available, verification of the numerical results becomes increasingly important. This presentation concerns the development of another benchmark for the linear neutron transport equation in a benchmark series, each employing a different method of solution. In 1D, there are numerous ways of analytically solving the monoenergetic transport equation, such as the Wiener–Hopf method, based on the analyticity of the solution, the method of singular eigenfunctions, inversion of the Laplace and Fourier transform solution, and analytical discrete ordinates in the limit, which is arguably one of the most straightforward, to name a few. Another potential method is the PN (Legendre polynomial order N) method, where one expands the solution in terms of full-range orthogonal Legendre polynomials, and with orthogonality and series truncation, the moments form an open set of first-order ODEs. Because of the half-range boundary conditions for incoming particles, however, full-range Legendre expansions are inaccurate near material discontinuities. For this reason, a double PN (DPN) expansion in half-range Legendre polynomials is more appropriate, where one separately expands incoming and exiting flux distributions to preserve the discontinuity at material interfaces. Here, we propose and demonstrate a new method of solution for the DPN equations for an isotropically scattering medium. In comparison to a well-established fully analytical response matrix/discrete ordinate solution (RM/DOM) benchmark using an entirely different method of solution for a non-absorbing 1 mfp thick slab with both isotropic and beam sources, the DPN algorithm achieves nearly 8- and 7-place precision, respectively.

Gravity Wave Momentum Fluxes from 1 km Global ECMWF Integrated Forecast System

Progress in understanding the impact of mesoscale variability, including gravity waves (GWs), on atmospheric circulation is often limited by the availability of global fine-resolution observations and simulated data. This study presents momentum fluxes due to atmospheric GWs extracted from four months of an experimental “nature run", integrated at a 1 km resolution (XNR1K) using the Integrated Forecast System (IFS) model. Helmholtz decomposition is used to compute zonal and meridional flux of vertical momentum from ~1.5 petabytes of data; quantities often emulated by climate model parameterization of GWs. The fluxes are validated using ERA5 reanalysis, both during the first week after initialization and over the boreal winter period from November 2018 to February 2019. The agreement between reanalysis and IFS demonstrates its capability to generate reliable flux distributions and capture mesoscale dynamic variability in the atmosphere. The dataset could be valuable in advancing our understanding of GW-planetary wave interactions, GW evolution around atmospheric extremes, and as high-quality training data for machine learning (ML) simulation of GWs.