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At least 163 records · Page 9

Experimental and Numerical Investigation of a Miniature Additively Manufactured Vortex Tube

Ranque–Hilsch vortex tubes are simple devices that can produce a cooling effect using compressed air. A key advantage of vortex tubes is the lack of moving solid parts; however, their efficiencies are relatively low. The present study focuses on the development of a miniature variable-diameter tube using additive manufacturing. A metal-based 3D printing technique was utilized to fabricate this vortex tube monolithically. Computational fluid dynamics simulations employing software STAR-CCM + with a compressible Reynolds-Averaged Navier–Stokes (RANS) approach and the elliptic-blending lag k-epsilon turbulence model have been applied to model thermofluid processes inside the vortex tube, to good agreement with the experiment. In conclusion, a temperature decrease of 13.3 °C and a cooling power of approximately 4 W were experimentally achieved with a pressure ratio of 4 in the air at normal conditions. This result shows promise for the goal of utilizing additive manufacturing to design and build complex-geometry vortex tubes intended for use with cryogenic fluids.

08 HYDROGEN↗

CFD Simulations of Lower Plenum Mixing

Review of model development and validation performed in the Advanced Reactor Technologies (ART) program for thermal mixing at the outlet of High Temperature Gas Reactors (HTGRs). Understanding the mixing that occurs in the lower plenum in an HTGR is necessary to facilitate design improvements and to perform reactor safety analysis. Numerical models are one possible approach to gain a better understanding of mixing in the lower plenum. Given the complexity of the geometry and the intense mixing present, it is important to perform validation of numerical models. Three models have been developed during FY2025: a porous media with Pronghorn, a Reynolds Averaged Navier Stokes (RANS) with STAR-CCM+, and a Large Eddy Simulation (LES) with NekRS. The reference facility is a scaled-down version of the lower plenum of the High Temperature Gas-Cooled Reactor - Pebble-bed Module (HTR-PM) demonstration reactor. Preliminary results of the porous media and the RANS shows general good agreement against experimental benchmark data. Future work will leverage high-fidelity results obtained through LES to guide model selection and improvements to the lower-fidelity models, with particular attention to the Pronghorn porous media.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Highly Accurate Experimental Heave Decay Tests with a Floating Sphere: A Public Benchmark Dataset for Model Validation of Fluid–Structure Interaction

Highly accurate and precise heave decay tests on a sphere with a diameter of 300 mm were completed in a meticulously designed test setup in the wave basin in the Ocean and Coastal Engineering Laboratory at Aalborg University, Denmark. The tests were dedicated to providing a rigorous benchmark dataset for numerical model validation. The sphere was ballasted to half submergence, thereby floating with the waterline at the equator when at rest in calm water. Heave decay tests were conducted, wherein the sphere was held stationary and dropped from three drop heights: a small drop height, which can be considered a linear case, a moderately nonlinear case, and a highly nonlinear case with a drop height from a position where the whole sphere was initially above the water. The precision of the heave decay time series was calculated from random and systematic standard uncertainties. At a 95% confidence level, uncertainties were found to be very low—on average only about 0.3% of the respective drop heights. Physical parameters of the test setup and associated uncertainties were quantified. A test case was formulated that closely represents the physical tests, enabling the reader to do his/her own numerical tests. The paper includes a comparison of the physical test results to the results from several independent numerical models based on linear potential flow, fully nonlinear potential flow, and the Reynolds-averaged Navier–Stokes (RANS) equations. A high correlation between physical and numerical test results is shown. The physical test results are very suitable for numerical model validation and are public as a benchmark dataset.

42 ENGINEERING↗

Detecting damaged buildings using real-time crowdsourced images and transfer learning

After significant earthquakes, we can see images posted on social media platforms by individuals and media agencies owing to the mass usage of smartphones these days. These images can be utilized to provide information about the shaking damage in the earthquake region both to the public and research community, and potentially to guide rescue work. This paper presents an automated way to extract the damaged buildings images after earthquakes from social media platforms such as Twitter and thus identify the particular user posts containing such images. Using transfer learning and ~ 6500 manually labelled images, we trained a deep learning model to recognize images with damaged buildings in the scene. The trained model achieved good performance when tested on newly acquired images of earthquakes at different locations and when ran in near real-time on Twitter feed after the 2020 M7.0 earthquake in Turkey. Furthermore, to better understand how the model makes decisions, we also implemented the Grad-CAM method to visualize the important regions on the images that facilitate the decision.

58 GEOSCIENCES↗

A Study of Propane Combustion in a Spark-Ignited Cooperative Fuel Research (CFR) Engine

Liquefied petroleum gas (LPG), whose primary composition is propane, is a promising candidate for heavy-duty vehicle applications as a diesel fuel alternative due to its CO 2 reduction potential and high knock resistance. To realize diesel-like efficiencies, spark-ignited LPG engines are proposed to operate near knock-limit over a wide range of operating conditions, which necessitates an investigation of fuel-engine interactions that leads to end-gas autoignition with propane combustion. This work presents both experimental and numerical studies of stoichiometric propane combustion in a sparkignited (SI) cooperative fuel research (CFR) engine. Engine experiments are initially conducted at different compression ratio (CR) values, and the effects of CR on engine combustion are characterized. A three-pressure analysis (TPA) model based on the two-zone combustion concept is developed in GT-Power and validated using test results to estimate in-cylinder wall temperatures, residual gas fraction, etc. This model is further utilized to examine end-gas chemistry by enabling the SI turbulent flame combustion and unburned gas chemical kinetics modules. Finally, a three-dimensional (3D) computational fluid dynamic (CFD) model of the CFR engine is developed in CONVERGE, where the G-equation and SAGE detailed chemical kinetics models are implemented for combustion modeling. Here, a 153 species reduced chemical kinetics mechanism derived from the detailed NUIGMech1.1 mechanism based on the ignition delay and laminar flame speed (LFS) studies is used to generate an LFS lookup table and to describe end-gas autoignition chemistry. Multi-cycle Reynolds-averaged Navier-Stokes (RANS) simulations are then performed for the tested CRs, and the numerical model is shown to be capable of predicting the propane combustion characteristics, particularly the end-gas autoignition behavior.

20 FOSSIL-FUELED POWER PLANTS↗

A physics-informed data-driven low order model for the wind velocity deficit at the wake of isolated buildings

Detailed simulations of the Atmospheric boundary layer (ABL) provides information on wind velocity, direction and turbulence for optimizing the design of wind turbines and wind farms and their operations. Distributed wind turbines have been considered for use in urban or suburban areas for covering energy needs using a sustainable energy solution. Simulations of high Reynolds number turbulent ABL flows past obstacles can be used for the prediction of the velocity deficit and turbulence characteristics in the leeward side of building-like obstacles, allowing for the estimation of power losses and fatigue loads in wind turbines. However, fully three-dimensional simulations of high Reynolds number ABL flows using Large Eddy Simulation (LES) or Reynolds Average Navier-Stokes Simulations (RANS) continue to require large computational/ execution times. As a result, these 3D simulations may not be ideal tools for the rapid assessment of wind energy potential. In the present study, 3D numerical results from wall resolved RANS simulations were used for the development of a low order model that allows the rapid assessment of wind velocity and turbulence in the leeward side of an isolated building.

17 WIND ENERGY↗

Formulation, Implementation and Validation of a 1D Boundary Layer Inflow Scheme for the QUIC Modeling System

Recent studies have highlighted the importance of accurate meteorological conditions for urban transport and dispersion calculations. In this work, we present a novel scheme to compute the meteorological input in the Quick Urban & Industrial Complex () diagnostic urban wind solver to improve the characterization of upstream wind veer and shear in the Atmospheric Boundary Layer (ABL). The new formulation is based on a coupled set of Ordinary Differential Equations (ODEs) derived from the Reynolds Averaged Navier–Stokes (RANS) equations, and is fast to compute. Building upon recent progress in modeling the idealized ABL, we include effects from surface roughness, turbulent stress, Coriolis force, buoyancy and baroclinicity. We verify the performance of the new scheme with canonical Large Eddy Simulation (LES) tests with the GPU-accelerated FastEddy"Equation missing" solver in neutral, stable, unstable and baroclinic conditions with different surface roughness. Furthermore, we evaluate QUIC calculations with and without the new inflow scheme with real data from the Urban Threat Dispersion (UTD) field experiment, which includes Lidar-based wind measurements as well as concentration observations from multiple outdoor releases of a non-reactive tracer in downtown New York City. Compared to previous inflow capabilities that were limited to a constant wind direction with height, we show that the new scheme can model wind veer in the ABL and enhance the prediction of the surface cross-isobaric angle, improving evaluation statistics of simulated concentrations paired in time and space with UTD measurements.

54 ENVIRONMENTAL SCIENCES↗

Computational and Experimental Study of Film-Cooling Effectiveness With and Without Downstream Vortex Generators

Downstream vortex generators that involve a pair of rectangular plates arranged in an open V-shape placed just downstream of each film-cooling hole were shown to create flow and vortical structures that entrain lifted film-cooling flow back to the surface and increase its lateral spreading on the surface (GT2020–14317). In this study, computations and measurements were performed to examine the flow mechanisms this vortex generator induces to improve film-cooling effectiveness of a flat plate with the cooling flow emanating from one row of inclined holes. Parameters studied include blowing ratio (BR = 0.75 and 1.0) and temperature ratio (TR = 1.07 and 1.9). Here, the computational study is based on steady Reynolds-averaged Navier–Stokes (RANS) closed by the shear-stress transport (SST) turbulence model with and without conjugate analysis. The experimental study was conducted by using a conjugate heat transfer test rig with a plenum, where cooling flow is introduced. Measurements made include velocity and temperature profiles upstream and downstream of the film-cooling holes as well as the temperature at several locations on the hot and cold sides of the film-cooled flat plate. The computational study was validated by comparing computed results with those from measurements at BR = 0.75 and 1.0 and TR = 1.9. Computational and experimental results are presented to show the effects of BR and TR on the flow structures and how those structures improve the effectiveness of film cooling with and without the downstream vortex generators and with and without conjugate heat transfer.

42 ENGINEERING↗

Review and Analysis of Heat Transfer Correlations For Horizontal Pseudocritical CO 2 Heat Exchanger Applications

There is significant interest in the development of supercritical carbon dioxide (sCO 2 ) power cycles because of the potential for smaller and more energy efficient systems than a steam Rankine cycle. Heat exchanger designs typically use empirical correlations, but the applicability of these correlations near the CO 2 critical point is a potential issue. Though numerous correlations have been proposed in the literature, there are some disagreements when it comes to the accuracy. The current work recognizes the role of thermophysical properties, and its impacts on the heat transfer correlations and cycle efficiency. Heat transfer correlations proposed for horizontal flow inside circular pipes were analyzed with the help of numerical simulations. Steady state RANS simulations were performed using SST k-w turbulence model to evaluate the Nusselt number empirical correlations. It was found that the most of correlations (except Yoon) produced a Nusselt number that differed significantly with the one predicted numerically. Some of the correlations were developed for pure forced convection regime and as mentioned in Lin et al. do not account for mixed convection or free convection effects. Based on the limited observation, it appears that Yoon et al. predictions match well with the numerically predicted Nusselt Numbers. However, further analysis is required understand the applicability of various correlations and is contingent on accurate measurements or predictions of wall temperature profiles in the axial and the circumferential directions.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

CFD simulations of electric motor end ring cooling for improved thermal management

Proper thermal management of an electric motor for vehicle applications extends its operating range. One cooling approach is to impinge Automatic Transmission Fluid (ATF) onto the rotor end ring. Increased ATF coverage correlates to enhanced heat transfer. Computational Fluid Dynamics (CFD) analytical tools provide a mechanism to assess motor thermal management prior to hardware fabrication. The complexity of the fluid flow (e.g., jet atomization, interface tracking, wall impingement) and heat transfer makes these simulations challenging. Computational costs are high when solving these flows on high-speed rotating meshes. Typically, a Volume-of Fluid (VOF) technique (i.e., two-fluid system) is used to resolve ATF dynamics within this rotating framework. Suitable numerical resolution of the relevant physics for thin films under strong inertial forces at high rotor speeds is computationally expensive, further increasing the run times. In this work, a numerical study of rotor-ring cooling by ATF is presented using a patent automated Cartesian cut-cell based method coupled with Automatic Mesh Refinement (AMR). This approach automatically creates the Cartesian mesh on-the-fly and can effectively handle complex rotating geometries by adaptively refining the mesh based on local gradients in the flow field which results in better resolution of the air-ATF interface. A Single non-inertial Reference Frame (SRF) approach is used to account for the rotating geometry and to further improve the overall computational efficiency. Quasi-steady state conditions are targeted in the analysis of the results. Important physics such as ATF jet structure, velocity detail near the air-jet interface, ATF coverage/accumulation on the ring surface, and cooling capacity are presented for a low-resolution Reynolds averaged Navier-Stokes (RANS), high-resolution RANS, and high-resolution Large-Eddy Simulation (LES) models. Computations are scaled over hundreds of cores on a supercomputer to maximize turnaround time. Each numerical approach is shown to capture the general trajectory of the oil jet prior to surface impingement. The high-resolution LES simulation, however, is superior in capturing small scale details and heat transfer between the free jet and surrounding air.

42 ENGINEERING↗

Weak influence of anthropogenic emissions on aerosol, cloud, and rain in the wet season of the Amazon rainforest

Anthropogenic emissions have been shown to affect new particle formation, aerosol concentrations, and clouds. Such effects vary with region, environmental conditions, and cloud types. In the wet season of Amazonia, anthropogenic emissions emitted from Manaus, Brazil, can significantly increase the cloud condensation nuclei (CCN) concentrations compared to the background of mainly natural aerosols. However, the regional response of cloud and rain to anthropogenic emissions in Amazonia remains very uncertain. Here, we aim to quantify how aerosol concentration, cloud, and rain respond to changes in anthropogenic emissions through parameterized new particle formation and primary aerosol emission in the Manaus region and to understand the underlying mechanisms. We ran the atmosphere-only configuration of the HadGEM3 climate model with a nested regional domain that covers most of the rainforest region (720 km by 1200 km with 3 km resolution) under scaled regional emissions. The 7 d simulations show that, in the areas that are affected by anthropogenic emissions, when aerosol and precursor gas emissions are doubled from the baseline emission inventories, aerosol number concentrations increase by 13 %. The nucleation rate that involves sulfuric acid and biogenic compounds generally increases with pollution levels. However, nucleation is suppressed very close to the pollution source, resulting in lower nucleation and soluble Aitken mode aerosol number concentrations. We also found that doubling the anthropogenic emission can increase the cloud droplet number concentrations ( N d ) by 9 %, but cloud water and rain mass mixing ratios do not change significantly. Even very strong reductions in aerosol number concentrations by a factor of 4, which is an unrealistic condition, cause only a 4 % increase in rain over the domain. If we assume our simulation has a fine enough grid resolution and an accurate representation of the relevant atmospheric processes, the simulated weak and non-linear response of cloud and rain properties to linearly scaled anthropogenic emissions suggests that the interactions among aerosol, cloud, and precipitation in the Amazonian convective environment are buffered by microphysical processes. It also implies that the convective environment is resilient to the changes in Nd that occur in response to localized anthropogenic aerosol perturbations.

Wang, Xuemei [University of Leeds (United Kingdom)↗

Computational Fluid Dynamics and Heat Transfer Modeling of a Dimpled Heat Exchanger

Multiphysics and analytical calculations were conducted for a heat exchanger with passive, natural circulation flow. A glycol/water working fluid convects the heat to a dimpled heat exchanger shell, which subsequently transfers the heat to the soil, which acts as the ultimate heat sink. Because the system is fully-passive, it is not subject to the expenses, maintenance, and mechanical breakdowns associated with moving parts. Density, heat capacity, and thermal conductivity material properties were measured for various soil samples, and subsequently included as input for the soil heat conduction model. The soil model was coupled to a computational fluid dynamics (CFD) heat exchanger model that included the dynamic Smagorinsky large eddy simulation and k- omega turbulence models. The analysis showed that the fluid dynamics and heat transfer models worked properly, albeit at a slow pace. Nevertheless, the coupled CFD/heat conduction simulation ran long enough to determine a key parameter—the amount of heat conducted from the heat exchanger to the ground. This unique performance value, along with experimental data, was used as input for stand-alone, fast-running CFD models, as well as boundaries to obtain solutions to partial differential equations for soil heat conduction.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Multidimensional Modeling of Mixture Formation in a Hydrogen-Fueled Heavy-Duty Optical Engine With Direct Injection

Hydrogen (H 2 ), as a carbon-free fuel, is considered as one of the most promising solutions to reduce the carbon footprint of hard-to-decarbonize energy and transportation sectors. As such, hydrogen-fueled internal combustion engines (H 2 ICEs) have recently been receiving increasing attention, particularly in applications such as on-road/off-road heavy-duty transport and combined heat and power. The direct injection (DI) of gaseous hydrogen into the combustion chamber offers great potential for achieving high power density and high engine efficiency, while mitigating the risk of backfire and reducing pre-ignition. However, the numerical simulation of H 2 DI system remains a formidable challenge associated with the high computational cost of reproducing compressible supersonic flow and shocks in narrow injector passages and in near-nozzle regions. In general, there is a lack of well-established and validated practices for the modeling of high-pressure H 2 DI in large-bore engines. Here, to this end, this study focuses on computational fluid dynamics (CFD) modeling of the mixture formation process in a heavy-duty optical engine employing a medium-pressure H 2 DI system. Both large eddy simulations (LES) and Reynolds Averaged Navier–Stokes (RANS) simulations are performed and evaluated against optical data. Gaseous hydrogen is injected into the combustion chamber via a centrally located outward opening hollow-cone injector at a pressure of 40 bar. Simulations are carried out for two injection timings, namely, −120 and −60 °CA. The numerical predictions for H 2 distribution in different horizontal and vertical planes during the compression stroke are systematically compared against optical data obtained through planar laser-induced fluorescence (PLIF) measurements. Overall, the LES approach using the Dynamic Structure model is found to have good predictive capabilities for the early jet penetration in terms of length and shape, as well as the later H 2 distributions. However, the unsteady RANS approach with the renormalization group $k - ϵ$ model, which is widely used by industry to model heavy-duty ICEs, significantly underpredicts the H 2 mixing, even at similar mesh resolution to that used in LES. These results indicate that there is a need for the improvement of mixing submodels within the RANS approach when applied to H 2 DI simulations.

LES↗

The suitability of differentiable, physics-informed machine learning hydrologic models for ungauged regions and climate change impact assessment

As a genre of physics-informed machine learning, differentiable process-based hydrologic models (abbreviated as δ or delta models) with regionalized deep-network-based parameterization pipelines were recently shown to provide daily streamflow prediction performance closely approaching that of state-of-the-art long short-term memory (LSTM) deep networks. Meanwhile, δ models provide a full suite of diagnostic physical variables and guaranteed mass conservation. Here, we ran experiments to test (1) their ability to extrapolate to regions far from streamflow gauges and (2) their ability to make credible predictions of long-term (decadal-scale) change trends. We evaluated the models based on daily hydrograph metrics (Nash–Sutcliffe model efficiency coefficient, etc.) and predicted decadal streamflow trends. For prediction in ungauged basins (PUB; randomly sampled ungauged basins representing spatial interpolation), δ models either approached or surpassed the performance of LSTM in daily hydrograph metrics, depending on the meteorological forcing data used. They presented a comparable trend performance to LSTM for annual mean flow and high flow but worse trends for low flow. For prediction in ungauged regions (PUR; regional holdout test representing spatial extrapolation in a highly data-sparse scenario), δ models surpassed LSTM in daily hydrograph metrics, and their advantages in mean and high flow trends became prominent. In addition, an untrained variable, evapotranspiration, retained good seasonality even for extrapolated cases. The δ models' deep-network-based parameterization pipeline produced parameter fields that maintain remarkably stable spatial patterns even in highly data-scarce scenarios, which explains their robustness. Combined with their interpretability and ability to assimilate multi-source observations, the δ models are strong candidates for regional and global-scale hydrologic simulations and climate change impact assessment.

54 ENVIRONMENTAL SCIENCES↗

The curled wake model: a three-dimensional and extremely fast steady-state wake solver for wind plant flows

Abstract. Wind turbine wake models typically require approximations, such as wake superposition and deflection models, to accurately describe wake physics. However, capturing the phenomena of interest, such as the curled wake and interaction of multiple wakes, in wind power plant flows comes with an increased computational cost. To address this, we propose a new hybrid method that uses analytical solutions with an approximate form of the Reynolds-averaged Navier–Stokes equations to solve the time-averaged flow over a wind plant. We compare results from the solver to supervisory control and data acquisition data from the Lillgrund wind plant obtaining wake model predictions which are generally within 1 standard deviation of the mean power data. We perform simulations of flow over the Columbia River Gorge to demonstrate the capabilities of the model in complex terrain. We also apply the solver to a case with wake steering, which agreed well with large-eddy simulations. This new solver reduces the time – and therefore the related cost – it takes to simulate a steady-state wind plant flow (on the order of seconds using one core). Because the model is computationally efficient, it can also be used for different applications including wake steering for wind power plants and layout optimization.

17 WIND ENERGY↗

SANDWake3D

SAND2026-23958O SANDWake3D models atmospheric surface layers and turbine wakes using a 3D parabolic RANS solver. This Python-based tool uses an efficient method to simulate wakes, capturing complex wake behaviors such as wind shear, veer, and atmospheric stratification, naturally. It has been calibrated and validated against higher-fidelity large eddy simulations (LES), providing reliable results for wind energy and atmospheric research applications. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

SciDAC↗

High Efficiency 2-Bladed Utility Wind Turbine Enhanced by CoFlow Jet Active Flow Control

The aerodynamic performance and power output of a high efficiency Co-Flow Jet (CFJ) 2-bladed Wind Turbine is studied in this paper. CFJ is a Zero-Net-Mass-Flux (ZNMF) active flow control method that dramatically increases airfoil lift coefficient and suppresses flow separation at a low energy expenditure. The 3D Reynolds Averaged Navier-Stokes (RANS) equations with one-equation Spalart-Allmaras (SA) turbulence model are solved to simulate the 3D flows of the wind turbines. The CFJ-Wind Turbine in this paper is modified from the NREL 3-bladed 3.4 MW reference wind turbine with the same RPM, blade length, distribution of chord, twist, and bending. The CFJ 2-bladed wind turbine utilizes the CFJ-NACA 64 series airfoils at most of the blade span from 31.88\% to the tip. The CFJ injection and suction slots are implemented along the full blade span to enhance the effectiveness and power output. The study shows that the 2-bladed CFJ turbine significantly increases power output compared with the 3-bladed baseline turbine at all wind speeds by 15.8\% at the wind speed of 9.8 m/s and by 25.9\% at 4 m/s respectively. The efficiency enhancement is substantially more at the low wind speed than at high wind speed. This would be very beneficial to increase the annual power output or capacity factor as wind turbines work at the speeds lower than the rated speed for most of the time. The results show that the flow field around the blade surface presents a significant enhanced suction peak near the blade leading edge, which results in a very high tangential force and thus increased wind turbine net power coefficient. Consistent with the previous study for the small NREL Phase VI research wind turbine, this paper demonstrates that CFJ 2-bladed wind turbine is an effective technology to extract more power from the wind at all speeds. This study is just an initial effort to demonstrate the advantage of the CFJ blade with no design optimization. It is believed that there is more potential to further enhance the efficiency improvement.

active flow control↗

SST ..kappa..-..omega.. Simulations of the Atmospheric Boundary Layer Including the Coriolis Effect

For large-scale structures in the atmospheric boundary layer (ABL), the Coriolis effect and near-wall behavior can have a meaningful impact. For example, both the Coriolis effect and blade boundary layer impact how muchpower wind farms produce. RANS simulations of the ABL typically use the ..kappa..-epsilon turbulence model, which has been developed to accurately capture the Coriolis effect but typically does not perform well near walls. The SST ..kappa..-..omega.. turbulence model performs well near walls but does not accurately capture the Coriolis effect. This work modifies SST ..kappa..-..omega.. to accurately model the Coriolis effect. We discuss the similarities and differences in how to modify ..kappa..-epsilon and SST ..kappa..-..omega.. for the Coriolis effect. Finally, we compare ..kappa..-epsilon and SST ..kappa..-..omega.. simulations of the ABL, including the Coriolis effect, with large eddy simulations and measurements.

atmospheric boundary layer↗