Simulated Heat Flux Research Articles

Research on background heat flux of the thermal balance test system based on solar simulator

Abstract In the thermal balance test system based on the solar simulator, the background heat flux of the test system can cause additional heating to the spacecraft, reducing the effectiveness of the thermal test. Hence, it is necessary to conduct in-depth research on the impact of background heat flux through experimental and numerical methods. This paper first measures the background heat flux of the thermal test system based on the KM6 large-scale solar simulator experimentally, which is 35W/m2. Then, a simulation model of the thermal balance test system is established to clarify that the background heat flux originates from the cone chamber and collimating reflector of the solar simulator system. The result provides technical support for achieving a high-precision simulation of the space external heat flux based on the solar simulator.

Simulation of winter heat fluxes through a clay wall with added wheat straw using the finite element method

Simulation of winter heat fluxes through a clay wall with added wheat straw using the finite element method

Comprehensive comparative study of experimental and simulated critical heat flux in special high-flux cooling devices: The Short Helical Minichannel-Evaporators

Short Helical Minichannel Evaporators are compact heat exchangers characterized by small, helical channels that allow high heat flux dissipation by means of direct cooling. It is a promising cooling solution in applications requiring high heat transfer rates in a limited space, such as power electronics, machining processes, injection molding among others. Optimal and safe operation of these devices is critically dependent on accurate determination of the critical heat flux (CHF) when nucleate boiling changes to filmwise regime. Misestimation of the CHF could lead to system burnout or suboptimal performance, highlighting the need for reliable theoretical models. In this study, the performance of a theoretical model was compared with a series of experiments carried out on a custom-built test rig. The results show a strong correlation between the experimental data and the adapted Groeneveld model, with a Mean Absolute Error (MAE) of 8.51kWm−2, a Mean Error (ME) of −4.71kWm−2, and a Deviation (Dev) of 8.77kWm−2. Notably, 96.8% of the simulated values were within a 15% error band. The validated model is also applied to increase knowledge about design parameters beyond the experimental data. The study emphasizes the practicality of the Groeneveld model in accurately calculating the CHF for these specific heat exchangers, encouraging improvements for performance and operational safety.

Numerical Simulation of Passenger Evacuation and Heat Fluxes in the Waiting Hall of an Ultralarge Railway Station Hub

The resurgence of passenger flows after the pandemic poses a significant challenge to the safe operation of rail transit. Therefore, adopting the waiting hall of an ultralarge railway station hub as an example, thermal radiation and evacuation simulations were conducted by the Fire Dynamics Simulator and Pathfinder, respectively. Island-style shops, known for their high crowd density and fire load, were defined as fire sources, and the effectiveness of a 6 m wide fire isolation zone was validated via the adoption of the dual-validation model. By comparing the relationships between the total evacuation population after passenger flow recovery and various evacuation parameters, it was shown that passengers were not evenly distributed among the exits in the waiting hall during an emergency, leading to uneven utilization. Furthermore, to gain a comprehensive understanding of the evacuation process under simulated fire conditions, an evacuation simulation involving 10,000 evacuees over a duration of 324.8 s was conducted. This study provides a theoretical basis for optimizing fire emergency evacuation plans for ultralarge railway station hubs.

An Assessment of the Coupled Weather Research and Forecasting Hydrological Model on Streamflow Simulations over the Source Region of the Yellow River

The Source Region of the Yellow River (SRYR), renowned as the “Water Tower of the Yellow River”, serves as an important water conservation domain in the upper reaches of the Yellow River, significantly influencing water resources within the basin. Based on the Weather Research and Forecasting (WRF) Model Hydrological modeling system (WRF-Hydro), the key variables of the atmosphere–land–hydrology coupling processes over the SRYR during the 2013 rainy season are analyzed. The investigation involves a comparative analysis between the coupled WRF-Hydro and the standalone WRF simulations, focusing on the hydrological response to the atmosphere. The results reveal the WRF-Hydro model’s proficiency in depicting streamflow variations over the SRYR, yielding Nash Efficiency Coefficient (NSE) values of 0.44 and 0.61 during the calibration and validation periods, respectively. Compared to the standalone WRF simulations, the coupled WRF-Hydro model demonstrates enhanced performance in soil heat flux simulations, reducing the Root Mean Square Error (RMSE) of surface soil temperature by 0.96 K and of soil moisture by 0.01 m3/m3. Furthermore, the coupled model adeptly captures the streamflow variation characteristics with an NSE of 0.33. This underscores the significant potential of the coupled WRF-Hydro model for describing atmosphere–land–hydrology coupling processes in regions characterized by cold climates and intricate topography.

Evaluation of surface urban energy and water balance scheme (SUEWS) using scaled 2D model experiments under various seasons and sky conditions

Urban energy balance models are essential for better understanding of urban climate processes and mitigating urban heat island intensity. In this study, the Surface Urban Energy and Water Balance Scheme (SUEWS) is evaluated using scaled outdoor experiments of idealized city models consisting of street canyons (aspect ratio H/W = 2, H = 0.5) and hollow concrete building models, under various seasonal and sky conditions in a humid subtropical climate in 2020, using three evaluation approaches. The results indicate that the model effectively simulates net all-wave radiation (Q∗), with the coefficient of determination (R2) exceeding 0.970. Storage heat flux (ΔQS) derived from the Objective Hysteresis Model (OHM) is compared to those obtained from the residual term method (RTM) and element surface temperature method (ESTM), revealing the RTM tend to overestimate ΔQS compared to the observation-based ESTM. Compared to using default OHM coefficients, applying fitted OHM coefficients obtained under seasons and sky conditions improves the simulations of ΔQS and sensible heat flux (QH), reducing statistical errors by approximately 50% for ΔQS and increasing R2 in rainy summer from 0.353 to 0.793 for QH, respectively. Additionally, the improved available energy simulation suggests the importance of accurately partitioning between QH and latent heat flux (QE) for the future development of SUEWS.

Multi-decadal pacemaker simulations with an intermediate-complexity climate model

Abstract. In this paper, we first describe the main features of a new version of the International Centre for Theoretical Physics global atmospheric model (SPEEDY) with improved simulation of surface fluxes and the formulation of a three-layer thermodynamic ocean model (TOM3) suitable to explore the coupled extratropical response to tropical ocean variability. Then, we present results on the atmospheric model climatology, highlighting the impact of the modifications introduced in the model code, and show how important features of interdecadal and interannual variability are simulated in a “pacemaker” coupled ensemble of 70-year runs, where portions of the tropical Indo-Pacific are constrained to follow the observed variability. Despite the very basic representation of variations in greenhouse forcing and heat transport to the deep ocean (below the 300 m domain of the TOM3 model), the coupled ensemble reproduces the variations in surface temperature over land and sea with very good accuracy, confirming the role of the Indo-Pacific as a “pacemaker” for the natural fluctuations of global-mean surface temperatures found in earlier studies. Atmospheric zonal-mean temperature trends over 50 years are also realistically simulated in the extratropical lower troposphere and up to 100 hPa in the tropics. On the interannual scale, sea-surface temperature (SST) variability in sub-tropical and tropical regions not affected by SST relaxation is underestimated (mostly because of the absence of dynamically induced variability), while extratropical SST variability during the cold seasons is comparable to that observed. Atmospheric teleconnection patterns and their connections with SST are reproduced with high fidelity, although with local differences in the amplitude of regional features (such as a larger-than-observed response of extratropical SST to North Atlantic Oscillation variability). The SPEEDY-TOM3 model also reproduces the observed connection between averages of surface heat fluxes over the oceans and land surface air temperature in the wintertime northern extratropics. Overall, as in earlier versions of SPEEDY, the fidelity of the simulations (both in terms of climatological means and variability) is higher near the surface and in the lower troposphere, while the negative impacts of the coarse vertical resolution and simplified parameterizations are mostly felt in the stratosphere. However, the improved simulation of surface heat fluxes and their impact on extratropical SST variability in this model version (obtained at a very modest computational cost) make the SPEEDY-TOM3 model a suitable tool to investigate the coupled response of the extratropical circulation to interannual and inter-decadal changes of tropical SST in ensemble experiments.

Integrating artificial intelligence with numerical simulations of Cattaneo-Christov heat flux on thermosolutal convection of nano-enhanced phase change materials in Bézier-annulus

The numerical analysis based on incompressible smoothed particle hydrodynamics (ISPH) is introduced to examine the impacts of Cattaneo-Christov (Ca-Ch) heat flux and exothermic chemical reaction on thermosolutal convection of nano-enhanced phase change materials (NEPCM) in Bézier-annulus. The used annulus is formed between inner connected Bézier curves and outer connected spline-Bézier curves. The inner shape of connected Bézier curves is maintained at Th&Ch, left/right walls of spline-Bézier curves are kept at Tc&Cc and other walls are adiabatic. The governing equations, after being converted into non-dimensional form, have been solved by ISPH which is an accurate meshless algorithm the treatment of internal flows inside complex geometries. The simulations are executed for Frank-Kamenetskii number FK, Ca-Ch heat flux δC, buoyancy ratio parameter N, Soret-Dufour numbers SrDu, Rayleigh number Ra, and nanoparticle parameter φ on thermosolutal convection of a suspension fluid. From the numerical simulation values for the average Nusselt and Sherwood numbers (Nu¯, Sh¯) were obtained for some fluid flow scenarios. Then, based on those values an artificial neural network (ANN) model was developed to predict the values of Nu¯, and Sh¯ without the need to perform the ordinary simulations again for the new cases which is a high cost compared to ANN. From the obtained simulations, it was concluded that the ANN model is an accurate tool to be used to predict the needed values. Also, the Frank-Kamenetskii number significantly influences the enhancement process of the temperature distributions and velocity field as well as phase change material in Bézier-annulus.

On the importance of the humidity flux for the surface mass balance in the accumulation zone of the Greenland Ice Sheet

Abstract. It is highly uncertain how the humidity flux between the snow surface and the atmosphere contributes to the surface mass balance (SMB) of the interior Greenland Ice Sheet (GrIS). Due to sparse observations, evaluations of the simulated humidity flux are limited. Model-based estimates of the humidity flux contribution to the SMB are, therefore, unconstrained and even disagree in magnitude and sign. In this study, we evaluate the regional climate model MAR at the EGRIP (East Greenland Ice-Core Project) site in the accumulation zone of the GrIS. We use a combined dataset of continuous one-level bulk estimates of the humidity flux covering the period of May 2016–August 2019 and eddy-resolving eddy-covariance humidity flux measurements from all four summer seasons. In summer, we document a bias of too little sublimation (−1.3 W m−2, −1.65 mm w.e.) caused by a cold bias in both air and surface temperature, leading to a reduced humidity gradient. In winter, MAR overestimates vapor deposition by about 1 order of magnitude. This is a consequence of an overestimated temperature gradient in too stable atmospheric conditions compared to observations. Both systematic errors cause a large discrepancy in the annual net humidity flux between the model and observations of −9 mm w.e. yr−1. Remarkably, the simulated net annual humidity flux contributes positively to the SMB, contrary to observations documenting a net sublimation flux. We correct the systematic errors by applying a simple but effective correction function to the simulated latent heat flux. Using this correction, we find that 5.1 % of the annual mass gain at the EGRIP site sublimates again, and 4.3 % of the total mass gain is deposited vapor from the near-surface air. The estimated net humidity flux contribution to the annual SMB is about −1 % (net sublimation) compared to +5.6 % for the uncorrected simulation. In summer, the corrected MAR simulation shows that vapor deposition accounts for 9.6 % of the total mass gain and that 31 % of the total mass gain at the EGRIP site sublimates again. The net fluxes contribute to −32 % of the summer SMB. These results demonstrate that the humidity flux is a major driver of the summer SMB in the accumulation zone of the GrIS and highlight that even small changes could increase its importance for the annual SMB in a warming climate.

Particle-in-Cell Simulations of Sunward and Anti-sunward Whistler Waves in the Solar Wind

We present particle-in-cell simulations of a combined whistler heat flux and temperature anisotropy instability that is potentially operating in the solar wind. The simulations are performed in a uniform plasma and initialized with core and halo electron populations typical of the solar wind beyond about 0.3 au. We demonstrate that the instability produces whistler-mode waves propagating both along (anti-sunward) and opposite (sunward) to the electron heat flux. The saturated amplitudes of both sunward and anti-sunward whistler waves are strongly correlated with their initial linear growth rates, , where for typical electron betas we have 0.6 ≲ ν ≲ 0.9. We show that because of the relatively large spectral width of the whistler waves, the instability saturates through the formation of quasi-linear plateaus around the resonant velocities. The revealed correlations of whistler wave amplitudes and spectral widths with electron beta and temperature anisotropy are consistent with solar wind observations. We show that anti-sunward whistler waves result in an electron heat flux decrease, while sunward whistler waves actually lead to an electron heat flux increase. The net effect is the electron heat flux suppression, whose efficiency is larger for larger electron betas and temperature anisotropies. The electron heat flux suppression can be up to 10%–60% provided that the saturated whistler wave amplitudes exceed about 1% of the background magnetic field. The experimental applications of the presented results are discussed.

The Destructive Sir Ivan Fire in New South Wales, Australia; Simulations Using a Coupled Fire—Atmosphere Model

The destructive Sir Ivan Dougherty fire burned 55,000 hectares around 250 km northwest of Sydney in New South Wales on 12 February 2017. Record hot temperatures were recorded in the area during the lead-in days and the fire conditions at the time were described as the ‘worst ever seen in NSW’. The observed weather conditions were hot, dry and very windy ahead of a synoptic frontal wind change during the afternoon. ‘Extreme’ to ‘catastrophic’ fire weather was predicted, and the potential for extreme fire behaviour was identified several days in advance. The Australian coupled fire–atmosphere model ACCESS-Fire has been run to explore the characteristics of the Sir Ivan fire. Several features resulting from fire–atmosphere interaction are produced in the simulations. Simulated heat flux along the fire perimeter shows increased intensity on the northern fire flank in response to gradual backing winds ahead of the main frontal wind change. Temporal and spatial variability in fire activity, seen as pulses in fire intensity and fireline wind speed, develop in response to boundary layer rolls in the wind fields. Deep moist convection consistent with the observed pyrocumulonimbus (pyroCb) cloud is simulated over the fire at around the time of the frontal wind change, and matches guidance from the ‘PyroCb Firepower Threshold’ tool, which showed transient favourable conditions. After the wind change, short-lived near-surface and elevated vortices suggest organised rotating features on the northern flank of the fire. The coupled model captures processes that cannot be produced in uncoupled fire predictions and that are not captured in current operational meteorological forecast products provided to Australian fire agencies. This paper links the features from coupled simulations to available observations and suggests pathways to embed the learnings in operational practice.

Mechanical properties and simulated thermal conductivity of biomimetic structured PS-PVD (Gd0.9Yb0.1)2Zr2O7 thermal barrier coatings

Plasma spray physical vapor deposition (PS-PVD) (Gd0.9Yb0.1)2Zr2O7 (GYbZ) thermal barrier coatings (TBCs) exhibited better silicate-phobicity than coatings produced by electron beam physical vapor deposition. In combination with PS-PVD and ultrafast laser direct writing technology, biomimetic structured GYbZ TBCs, with a triple-scale micro/nano surface microstructure, were obtained. Laser ablating on the PS-PVD GYbZ coating enhanced the surface roughness, improving its wear resistance without increasing the surface hardness. Furthermore, during the laser ablation processing, numerous nanoparticles were deposited in-situ in the gaps between columns of the coating, reducing the coating Young's modulus. The simulated temperature field and heat flux field demonstrated that the presence of numerous interfaces between small columns of the PS-PVD coatings is beneficial to thermal insulation. However, laser ablation decreased the coating thickness, reducing the thermal insulation by around 20%–30% as compared to its PS-PVD counterpart, suggesting that a moderate increase in the coating thickness should be considered when designing an efficient TBC system.

Laser surface texturing and numerical simulation of heat flux on Cr2AlC MAX phase heat exchangers

The energetic worldwide emergency demands a significant drop in fossil energy to renewable energies as part of the sustainable solutions for global energy consumption. MAX phase materials, such as Cr2AlC, are potential candidates for heat exchanger applications due to their excellent oxidation and corrosion resistance, good thermal shock response and relatively high thermal conductivity. This study uses laser surface texturing (LST) technology to design plate heat exchanger patterns on the Cr2AlC MAX phase. Furthermore, performing numerical simulations on textured plate models under molten salt conduction and convection conditions, accessing temperature gradient and heat transfer behaviour were conducted on Cr2AlC, as well as on 316 L stainless steel and alumina for comparison. As a result, combined microtextures with a corrugated surface and spaced V-shape channels were obtained using LST in a single step. The parametric study indicated that the optimal channels (groves) were found for 25 W in air and 20 s laser conditions, with approximately 145 µm width and 340 µm depth. Furthermore, the numerical simulation showed that ceramics materials present better heat transfer conditions than 316 L stainless steel, where Cr2AlC and alumina only differ in 1.9% heat flux. In addition, the corrugated surface plate with 2.6% width of the total thickness increases heat transfer by 9.8%.

Impact of Updating Vegetation Information on Land Surface Model Performance

AbstractVegetation plays a fundamental role in modulating the exchange of water, energy, and carbon fluxes between the land and the atmosphere. These exchanges are modeled by Land Surface Models (LSMs), which are an essential part of numerical weather prediction and data assimilation. However, most current LSMs implemented specifically in weather forecasting systems use climatological vegetation indices, and land use/land cover data sets in these models are often outdated. In this study, we update land surface data in the European Centre for Medium‐range Weather Forecast (ECMWF) land surface modeling system (ECLand) using Earth observation‐based time varying leaf area index and land use/land cover data, and evaluate the impact of vegetation dynamics on model performance. The performance of the simulated latent heat flux and soil moisture is then evaluated against global gridded observation‐based data sets. Updating the vegetation information does not always yield better model performances because the model's parameters are adapted to the previously employed land surface information. Therefore we recalibrate key soil and vegetation‐related parameters at individual grid cells to adjust the model parameterizations to the new land surface information. This substantially improves model performance and demonstrates the benefits of updated vegetation information. Interestingly, we find that a regional parameter calibration outperforms a globally uniform adjustment of parameters, indicating that parameters should sufficiently reflect spatial variability in the land surface. Our results highlight that newly available Earth‐observation products of vegetation dynamics and land cover changes can improve land surface model performances, which in turn can contribute to more accurate weather forecasts.

Monolithic AM façade: multi-objective parametric design optimization of additively manufactured insulating wall elements

Additive Manufacturing (AM) offers transformative opportunities to create functionally hybridized, insulating, monolithic AM wall elements. The novel fabrication methods of AM allow for the production of highly differentiated building components with intricate internal and external geometries, aiming for reduced material use while integrating and enhancing building performance features including thermal insulation performance. This study focuses on integrating such thermal insulation performance by leveraging the individual features of three distinct AM processes: Selective Paste Intrusion (SPI), Selective Cement Activation (SCA), and Extrusion 3D Concrete Printing (E3DCP). Using a simulation-based parametric design approach, this research investigates 4,500 variations of monolithic AM façade elements derived from a generative hexagonal cell layout with differing wall widths, the three respective AM processes, different material compositions with and without lightweight aggregates, and three different insulation strategies, namely, air-filled cells, encapsulated lightweight aggregates, and additional insulation material within the cavities. Thermal performance feedback is realized via 2D heat flux simulations embedded into a parametric design workflow, and structural performance is considered in a simplified way via geometric and material-specific evaluation. The overall research goal is a multi-objective design optimization, particularly identifying façade configurations that achieve a U-value of less than 0.28 W/m2K and a theoretical compressive strength exceeding 2.70 MN per meter wall length. The results of this study detect 7% of all generated variations in line with these thermal and structural requirements, validating the feasibility of monolithic, thermally insulating AM wall elements. The presented workflow contributes to exploiting the potential of a new design of functionally hybridized AM components.

Study on Ground Experimental Method of Stagnation Point Large Heat Flux of Typical Sharp Wedge Leading Edge Structure

In this paper, aimed at the problem of large temperature gradient thermal testing with the typical sharp wedge leading edge structure of a hypersonic vehicle, a subsonic high-temperature combustion gas heating (SHCH) test device is used to conduct a series of experiments on the heat flux simulation ability of subsonic high-temperature combustion gas in the stagnation point region. Firstly, for a hypersonic vehicle with a flying height of 24 km and Mach number range of 4~6.5, the stagnation point heat flux in the head area is obtained by numerical calculation of a typical leading edge structure, which is used as the experimental target of the thermal structure test. Secondly, an experimental specimen with a Gardon heat flux meter is designed with the same shape and size as the specimen in the numerical simulations to prepare for the subsequent SHCH test. Thirdly, a method to determine the combustion gas temperature based on a Kriging surrogate model is proposed. CFD numerical simulation is conducted using the SHCH test model, and the numerical calculation results are used as the training dataset. The Kriging surrogate model is used to establish an approximate fitting relationship between the stagnation point heat flux and experimental parameters under SHCH conditions. The corresponding combustion gas temperature values are found, respectively, with the hypersonic aerodynamic heat flux at Mach 5.0~5.4 as the target value. Finally, stagnation point heat flux testing of low-speed and high-temperature combustion gas is performed at different combustion gas temperatures. The experimental and target values obtained from hypersonic aerodynamic thermal simulations are compared and analyzed to verify the heating capacity of SHCH and the feasibility of hypersonic aerothermal simulation testing.

Error correction method for heat flux and a new algorithm employed in inverting wall thermal resistance using an artificial neural network: Based on IN-SITU heat flux measurements

The heat-flux meter is affected by various uncertain factors in practical applications, which brings some difficulties to scholars in postprocessing data. Therefore, a modified method for calculating the heat flux of the building surface is proposed. It can make the simulated heat flux value consistent with the experimental heat flux value, thus verifying the accuracy of the model with the heat flux value. On this basis, through artificial neural network (ANN) training, the heat conduction flux inside the wall is predicted by using the measured heat flux and temperature of inner surfaces. The results show that the root mean square errors obtained by the heat flux error correction method are all less than 1.12 W·m−2. The ANN fitting coefficients are also greater than 0.9. The error correction method proposed in this work comprehensively considers the influence of solar radiation and the total heat transfer coefficient and is also applicable to passive buildings and buildings with PCM in the envelope. The well-performing network built by ANN can predict the thermal conductivity heat flux inside the wall more accurately, providing a new method to measure or check whether the thermal resistance of the wall is qualified in the field.

Improvement of 3D-Active Thermography by using Artificial Intelligence

For the one-dimensional case of heat propagation in active thermography the thickness of the investigated specimen can be directly reconstructed using known evaluation methods such as laser flash analysis or thermographic signal reconstruction and observation of a characteristic time. Concerning the multidimensional case diffusive effects have a strong impact on the heat propagation of the thermal wave, which leads to misinterpretations when evaluating the thickness especially at deep-lying edges and inhomogeneities in a specimen. The deeper a defect is located in the component, the more diffuse it is perceived in a change in surface temperature. Within this paper, heat flux simulations and real measurements of pulse thermography of different defect geometries are used to train a neural network for depth-resolved defect interpretation. The defect geometries are based on geometries of real impact damages in composites and were realistically obtained from a micromechanical fracture simulation. The neural network is based on an encoder-decoder approach where the temperature values of the cooling curve after a pulse-shaped excitation serve as input information. Segmentation is performed as a function of the backwall geometry. By training several thousand defect geometries using an encoder-decoder network, it was possible for the first time to directly infer the backwall geometry of a component without additional information about the component. Finally, it is shown how simulations can support the inversion of thermal waves for 3D-thermography of real measurements by an artificial intelligence system.

Carbon and Water Fluxes of the Boreal Evergreen Needleleaf Forest Biome Constrained by Assimilating Ecosystem Carbonyl Sulfide Flux Observations

AbstractGross primary production (GPP) by boreal forests is highly sensitive to environmental changes. However, GPP simulated by land surface models (LSMs) remains highly uncertain due to the lack of direct photosynthesis observations at large scales. Carbonyl sulfide (COS) has emerged as a promising proxy to improve the representation of GPP in LSMs. Because COS is absorbed by vegetation following the same diffusion pathway as CO2 during photosynthesis and not emitted back to the atmosphere, incorporating a mechanistic representation of vegetation COS uptake in LSMs allows using COS observations to refine GPP representation. Here, we perform ecosystem COS flux and GPP data assimilations to constrain the COS‐ and GPP‐related parameters in the ORCHIDEE LSM for boreal evergreen needleleaf forests (BorENF). Assimilating ecosystem COS fluxes at Hyytiälä forest increases the simulated net ecosystem COS uptake by 14%. This increase largely results from changes in the internal conductance to COS, highlighting the need to improve the representation of COS internal diffusion and consumption. Moreover, joint assimilation of ecosystem COS flux and GPP at Hyytiälä improves the simulated latent heat flux, contrary to the GPP‐only data assimilation, which fails to do so. Finally, we scaled this assimilation framework up to the boreal region and find that the joint assimilation of COS at Hyytiälä and GPP fluxes at 10 BorENF sites increases the modeled vegetation COS uptake up to 18%, but not GPP. Therefore, this study encourages the use of COS flux observations to inform GPP and latent heat flux representations in LSMs.

Low thermal conductivity and thermal radiation of La2Zr2O7 ceramics with hierarchical structure above 1000 K

The hierarchically porous La2Zr2O7 (LZO) microsphere fabricated by the electro-spraying assisted phase inversion (ESP) method is a promising feedstock for thermal barrier coatings (TBCs), due to its low thermal conductivity, quite high near-infrared reflectivity and high temperature structure stability. However, the thermal properties of hierarchically porous LZO ceramics above 1000 K are still unclear, limiting its application in TBCs. The effect of hierarchical structure on thermal conduction and thermal radiation was investigated in comparison with mono-sized pores, using the ESP microspheres (LZO-ESP) and other two carbon fillers to modulate the pores. The results showed that LZO-ESP samples exhibited ultra-low thermal conductivity (1.28 W m−1 K−1 at 1173 K), which was 30% lower than that of the reference samples of similar porosity. Heat flux simulation revealed that hierarchical structure can induce more disorder domains than the randomly distributed mono-sized pores. The disorder domains with high tortuosity of heat flux played a predominant role in the reduction of thermal conductivity. Additionally, the hierarchical structure significantly reduced thermal radiation by 36% compared with dense sample due to the decrease in transmissivity.