Reynolds-averaged Navier-Stokes Model Research Articles

Performance of dual‐chamber oscillating water column device under irregular incident waves using Reynolds averaged Navier–Stokes model

AbstractThe purpose of this study is to analyze the hydrodynamic performance and efficiency of a dual‐chamber oscillating water column (OWC) device. For the Joint North Sea Wave Project (JONSWAP) incident waves spectrum, a two dimensional numerical wave tank is employed with nonlinear Reynolds averaged Navier–Stokes equations model along with the standard turbulence model. The free surface elevation is measured using the volume of fluid method. The numerical simulation demonstrates the streamline and velocity vector profiles throughout an entire pressure fluctuation cycle inside the chambers of the given OWC device. Further, investigation is carried out to analyze the impact of pressure drop and air flow rate through the orifice of the dual‐chamber OWC device on the power generation. Moreover, the power spectral density analysis of the free surface elevation is provided to know the variation of the parameters in the frequency domain. These results demonstrate that the effectiveness of the dual‐chamber OWC device is more near the significant wave height m.

Numerical investigation gaseous ammonia basic jet and mixing characteristics in the constant volume vessel

Ammonia is considered a promising zero-carbon fuel under the dual-carbon targets. Systematically understanding ammonia's basic jet and mixing characteristics can promote its practical application in the engine field. Thus, a three-dimensional computational fluid dynamics (CFD) model of constant volume vessel (CVV) is established in this paper, and the forecasting abilities of the Large Eddy Simulation (LES) and Reynolds-Averaged Navier-Stokes (RANS) models for the gaseous ammonia jet process are compared based on the experimental data. Then, the ammonia jet development rule and mixing characteristics under different ambient temperatures, ambient pressures, and fuel temperatures are investigated. The variation laws of key data such as penetration distance, jet area, ammonia mass concentration distribution, equivalence ratio, and turbulent kinetic energy are obtained and analyzed. The results show that during the injection process, the airflow on the left and right sides of the jet rotates in opposite directions. A higher temperature and lower pressure within the CVV lead to a larger flammable range for ammonia jets. Moreover, the distribution of ammonia mass concentration on the radial plane shows a dynamic development law with time, meaning that it first increases to a maximum value, then gradually decreases, and finally remains stable. The farther the radial plane is from the nozzle outlet position, the lower the ammonia mass concentration. In addition, the ammonia jet's turbulent kinetic energy has a large core region and symmetrical distribution along the central axis. At the beginning of the injection, the core length is small, gradually increasing with time and finally stabilizing.

Evaluating numerical models for the prediction of pollutant dispersion over Tokyo's Polytechnic University campus

This paper focuses on assessing how different Computational Fluid Dynamics (CFD) methodologies perform in modelling pollutant dispersion over extended urban areas. The case selected for evaluating the proposed methodologies is based on an extensive experimental study conducted by Tachibana et al. (2022), in which outdoor field measurements and wind tunnel experiments were carried out for monitoring tracer gas dispersion over the Atsugi Campus of Tokyo's Polytechnic University (TPU). Numerical results obtained by solving steady Reynolds Averaged Navier Stokes (RANS) governing equations, as well as using a scale resolving Large Eddy Simulation (LES) approach are compared against experimental data, in terms of both dimensionless local velocities and pollutant concentrations. The different meshing strategies that are employed for each methodology are also discussed in detail. The aim of the paper is to help gain further insights about the extent to which the Menter's Shear Stress Transport (SST) k-ω RANS model and LES can be used in the Architectural, Engineering and Construction (AEC) industry for pollutant dispersion modelling.

Aerodynamic study of high-speed railway tunnels with variable cross section utilizing equivalent excavation volume

High-speed railway tunnels, being critical components of transportation infrastructure, are subject to various aerodynamic effects that can impact train operations and passenger comfort. To address these challenges, the concept of tunnels with variable cross sections offers a promising solution, allowing for non-uniform adjustments to tunnel geometry along its length. By employing the notion of equivalent excavation volume, this paper aims to provide a comprehensive aerodynamic analysis of variable cross section tunnels, focusing on different rates of cross section variation (CR). The simulation of high-speed trains (HSTs) passing through tunnels is conducted using the compressible, unsteady Reynolds-Averaged Navier–Stokes model, and the accuracy is confirmed through experimental validation. The transient pressure and peak distribution, slipstream characteristics, micro-pressure waves, and aerodynamic loads acting on trains are fully evaluated. The results indicate that variable cross section tunnels can alleviate the negative pressure on train surface, particularly with streamlined heads and tails exhibiting superior effects, whereas its influence on positive pressure is minimal. The mitigation of both positive and negative pressures on the tunnels is promising, with the maximum peak-to-peak pressures exhibiting a quadratic decrease as the CR increases, resulting in a maximum relief of 17.7%. However, variable cross section tunnels have certain adverse effects on slipstreams and transient loads when HSTs passing through front junctions. Therefore, it is necessary to choose an appropriate CR to control these effects during design process. The findings of this research contribute novel insight for optimizing tunnel design and engineering practices to enhance operational efficiency and passenger comfort.

Enhancing pier local scour prediction in the presence of floating debris

AbstractLocal scour poses a grave threat to bridge foundations, potentially causing catastrophic collapses. This study uses FLOW-3D with the Reynolds-Averaged Navier-Stokes model to analyze pier scour and dune formation under bridges. It focuses on submerged debris shapes near the water's surface. Results closely match experiments when specific conditions are met. The study introduces an innovative approach to debris impact assessment. Instead of traditional methods, it proposes a novel equation accounting for debris's effective area and elevation. This enhances reliability by over 20%, improving scour depth assessment in debris-laden scenarios. This advances the understanding of debris's role in local scour, benefiting bridge design and management practices.

Characteristics of Laminar Separation Bubble With Varying Leading-Edge Shapes and Deflections of the Trailing-Edge Flap

Abstract A series of implicit large eddy simulations (ILES) is carried out to examine the characteristics of a leading edge (LE) separation bubble. The test case comprises a flat plate with an elliptic leading edge (ELE), which is equipped with a trailing edge flap. Simulations are carried out (a) at three different flap angles (20 deg, 30 deg, 90 deg) and (b) using two different geometries of ELE where the ratio of the semimajor to semiminor axis is set to either 2:1 or 4:1. The flap is modeled using the immersed boundary method, which is computationally economical as it avoids regenerating the grid for varying flap angles. The results show that (a) the flow separates at lower flap deflection angles with a decrease in the aspect ratio of the ELE from 4:1 to 2:1 (b) an increase in the flap angle promotes separation at the LE due to an increase in the blockage in the bottom passage and a subsequent increase in the flow incidence at the leading edge. Simulations are also carried out using the γ−Reθ transition model and comparisons are drawn against ILES and experiments. Although the qualitative trends predicted using both ILES and Reynolds-Averaged Navier–Stokes (RANS) agree with the experiments, both approaches predict relatively shorter separation bubbles. This is attributed to the excess flow blockage in experiments due to the support plates, which are not modeled in the simulations. Nevertheless, the results demonstrate the superior accuracy of ILES over the RANS model.

Large-Eddy vs. Reynolds-Averaged Navier–Stokes Simulations of Flow and Heat Transfer in a U-Duct with Unsteady Flow Separation

Large-eddy simulation (LES) and Reynolds-Averaged Navier–Stokes (RANS) equations were used to study incompressible flow and heat transfer in a U-duct with a high-aspect-ratio trapezoidal cross section. For the LES, the WALE subgrid-scale model was employed, and its inflow boundary condition was provided by a concurrent LES of incompressible fully-developed flow in a straight duct with the same cross section and flow conditions as the U-duct. LES results are presented for turbulent kinetic energy, Reynolds stresses, pressure–strain rate, turbulent diffusion, turbulent transport, and velocity–temperature correlations, with a focus on how they are affected by the U-turn region of the U-duct. The LES results were also used to assess three commonly used RANS models: the realizable k-ε with the two-layer model in the near-wall region, the two-equation shear-stress transport model, and the seven-equation stress-omega Reynolds stress model. Results obtained show steady and unsteady RANS to incorrectly predict the effects of unsteady flow separation. The results obtained also identified the terms in the RANS models that need to be modified and suggested how turbulent diffusion should be modeled when there is unsteady flow separation.

Effectiveness of natural ventilation through single-sided window opening in air-conditioning rooms

Since many buildings are not equipped with fresh air systems, many people open windows to allow for natural ventilation while the air conditioner is running. However, prolonged window opening may cause unnecessary energy consumption. Additionally, the diverse ways of window opening lead to significant variations in indoor airflow distribution, consequently impacting ventilation efficiency. Therefore, this study used field experiments and computational fluid dynamics (CFD) to determine the air exchange efficiency and air change rate of single-sided natural ventilation in air-conditioning rooms by fitting the decay curves of tracer gas. CFD simulation was performed using the unsteady Reynolds-averaged Navier-Stokes (RANS) model to examine how window openings affect the room’s air distribution, and the computed indoor CO2 concentration was compared to the corresponding field experiment data. The results show that natural ventilation through the window opening induced constant heat and mass exchange between indoor and outdoor air, which caused extra cooling losses but was globally effective in eliminating indoor contaminants. The air exchange efficiency is influenced to varying degrees by factors such as the air supply register’s position, window opening percentage, and window opening position. The air supply register’s position exerted the most significant impact at 46.45%. Efficient indoor-outdoor air exchange can be achieved by opening windows intermittently. When the window is opened from one side and the opening percentage is 100%, the indoor environment can be improved by opening the window for about 10 min every 39 min for X-direction air supply and about 7 min every 39 min for Y-direction.

Computational Study on Influence Factors and Vortical Structures in Static Drift Tests

This paper conducted a computational study on the KCS benchmark model at static drift conditions. At the first instance, the roles played by the grid size, turbulence model, and time step are qualitatively and quantitatively analyzed with the orthogonal experimental method (OEM). After the verification of simulated results compared with experimental data in a Static Oblique Towing Test (OTT), hydrodynamic performance is obtained with the employment of the SST κ-ω turbulence model. The grid size is set as 0.07 m while the time step as 0.01 s. The characteristics of the wake field are illustrated in different forms, such as contours of the free surface, distribution of pressure and hydrodynamic forces, variation of turbulent kinetic energy (TKE), and so on. For a deep insight into the physical mechanisms of the asymmetrical flow field, the Detached Eddy Simulation (DES) method is also utilized to capture vortical structures occurring around the hull, in comparison with results obtained through the Reynolds Averaged Navier Stokes (RANS) model. With the aim of a hydrodynamic derivative estimation or detailed flow characteristics analysis, corresponding selections of the computational method are disparate.

Wave and Roller Transformation Over Barred Bathymetry

AbstractThe cross‐shore transformation of breaking‐wave roller momentum and energy on observed barred surfzone bathymetry is investigated with a two‐phase Reynolds Averaged Navier Stokes model driven with measured incident waves. Modeled wave spectra, wave heights, and wave‐driven increases in the mean water level (setup) agree well with field observations along transects extending from 5‐m water depth to the shoreline. Consistent with prior results the roller forcing contributes 50%–60% to the setup, whereas the advective terms contribute ∼20%, with the contribution of bottom stress largest (up to 20%) for shallow sandbar crest depths. The model simulations suggest that an energy‐flux balance between wave dissipation, roller energy, and roller dissipation is accurate. However, as little as 70% of the modeled wave energy ultimately dissipated by breaking was first transferred from the wave to the roller. Furthermore, of the energy transferred to the roller, 15%–25% is dissipated by turbulence in the water column below the roller, with the majority of energy dissipated in the aerated region or near the roller‐surface interface. The contributions of turbulence to the momentum balance are sensitive to the parameterized turbulent anisotropy, which observations suggest increases with increasing turbulence intensity. Here, modeled turbulent kinetic energy dissipation decreases with increasing depth of the sandbar crest, possibly reflecting a change from plunging (on the steeper offshore slope of the bar) to spilling breakers (over the flatter bar crest and trough). Thus, using a variable roller front slope in the roller‐wave energy flux balance may account for these variations in breaker type.

CFD simulations of turbulent flow and dispersion in built environment: A perspective review

Computational fluid dynamics (CFD), a powerful analysis tool in wind engineering, has been applied to a wide variety of problems over the past few decades. The application of CFD to environmental wind problems in the built environment is much more common than its application to structural wind problems, in both practice and research. This paper briefly reviews the history of urban wind problems and the development of wind engineering. Then, the progress in the applications of CFD to environmental problems is outlined, particularly in terms of the evolution of the studies presented over time at the International Conferences on Wind Engineering. The major achievements of CFD in environmental wind engineering in the last 30 years are discussed in terms of Large Eddy Simulation versus the Reynolds-averaged Navier-Stokes model, appropriate boundary conditions, verification and validation, and best practice guidelines. Furthermore, notable topics in recent applications of CFD to the built environment, including complicated particle (e.g., snow, rain, sand, sea salt) dispersion, are reviewed. Finally, the future direction of the applications of CFD to environmental problems as an advanced design and research tool is discussed.

Validation of helicity-corrected Spalart-Allmaras model for corner separation prediction in incompressible flow with OpenFOAM

Steady Reynolds-averaged Navier-Stokes (RANS) computations save significant computational resources compared to unsteady RANS and large eddy simulation (LES). However, the ability of most RANS models to accurately predict flow separation in compressor/fan blade rows is limited. Recent research focused on reducing the computational cost of predicting compressor/fan stall points with steady computations has shown that the helicity-corrected Spalart-Allmaras (SA) turbulence model is able to avoid over-predicting corner separations and thus lead to converged RANS up to the actual stall point. To date, this model has mostly been implemented in in-house codes or in commercial codes as a user add-on, where the source code is not available. In a recent paper, the authors implemented the helicity-corrected SA model in OpenFOAM, an open-source CFD package. In this paper, the differences in the flow field for RANS solutions with the original SA model, the helicity-corrected SA model, and Menter’s shear stress transport (SST) model are highlighted for a linear cascade with incompressible flow. A NACA 65-1810 cascade is used, and computational results are compared to experimental data.

Computable turbulence modeling of laminar-turbulent transition characterized boundary layer flows with the aid of artificial neural network

The continuous development of machine learning algorithms has stimulated the technological revolution on turbulence modeling for Reynolds-averaged Navier–Stokes (RANS) simulations. In this paper, a computable transition-enabled turbulence model is developed with the aid of an artificial neural network (ANN), which maps the relation between the mean flow variables from the shear stress transport (SST) model on coarse grid and the turbulent viscosity from SST-γ model on fine grid. It turns out that the ANN model can predict the aerodynamic integral quantities, transition onset location, laminar separation bubble structure, streamwise velocity distribution, etc. with superior accuracy and robustness for subsonic and moderate transonic airfoil flows. Meanwhile, the ANN model can significantly improve the convergence property with a much higher convergence speed of the model equation in comparison with traditional transition-enabled RANS model. Moreover, due to the lack of solving RANS model equations and use of grid interpolation technology, the computation speed of this ANN model is improved by a factor of about six over the conventional benchmark model. Therefore, the present computable ANN model provides a new perspective for high-efficiency simulation of transition-characterized flows in engineering applications.

Turbulent Particle Flow in Spent Nuclear Fuel Storage Systems

Deposition models are being developed with the commercial computational fluid dynamics software STAR-CCM+ to evaluate particulate deposition on spent nuclear fuel (SNF) canisters. The primary particulate of concern is chloride salts, which are dispersed in the atmosphere and then deposited onto the canisters. During dry storage, the primary degradation process is likely to be chloride-induced stress corrosion cracking (CISCC) at the heat-affected zones of the canister welds. It is known that stainless steel canisters are susceptible to CISCC; however, the rate of chloride deposition onto the canisters is poorly known, based on sparse field data from a small number of sites. This paper describes work looking at various approaches to modeling turbulence, such as Reynolds-averaged Navier Stokes (RANS) and large eddy simulation (LES), and its impact on particle flow and deposition within a ventilated SNF storage system. The deposition rate is determined for a vertical canister system and a horizontal canister system. LES has the potential to simulate turbulent flows more accurately versus RANS, but is much more computationally expensive. A k-omega version of the RANS turbulence model was used for this study. The computational efficient RANS steady-state model predicted a similar canister deposition result as the LES simulation for a vertical canister storage system. For a horizontal storage system, the RANS steady-state model predicted more particles depositing on the canister than the LES simulation, providing a conservative estimation for particle deposition. A wall correction factor was added to the RANS model to dampen the turbulence fluctuation normal to a surface that left undamped, leads to the RANS model overpredicting deposition along a surface for smaller particles. This work was done to further development of deposition models that could be used to plan and inform SNF canister aging management programs with predictive models for the timing and occurrence of canister CISCC. This work is part of a larger effort tasked with understanding the likelihood of canister degradation due to CISCC. These models are still under development, and testing is needed for validation. However, these models are being presented now to demonstrate to canister vendors, utilities, regulators, and stakeholders the value of this type of modeling.

Predictive capability of an improved AD/RANS method for multiple wind turbines and wind farm wakes

The actuator disc (AD) model combined with the Reynolds-averaged Navier-Stokes (RANS) model has been demonstrated as the most effective approach for simulating wind farm wakes due to its computational efficiency and acceptable accuracy. However, challenges remain in defining the reference inflow wind speed for the AD model and identifying a robust turbulence model for the RANS method. To solve these issues, two strategies for establishing the AD model (AD-up1D model and AD-local model), along with four turbulence models (standard k-ε, SST k-ω, linear pressure-strain RSM and modified RSM), are comprehensively validated here to predict multiple wakes within two representative wind farms. The temporal variability of multiple turbines’ power output and the significant impact of wind direction on the power is particularly emphasized. Overall, this study indicates that the proposed AD-local/Mod RSM method facilitates a realistic wake recovery in the cumulated wake flow and agrees well with the field measurements. It consistently performs well, never ranking last in any test cases, with percentage deviations ranging from 1.8% to 9.0%. Most importantly, this study evaluates the strengths and weaknesses of each AD/RANS method and provides recommendations for wind farm design purposes.

On the Fidelity of RANS-Based Turbulence Models in Modeling the Laminar Separation Bubble and Ice-Induced Separation Bubble at Low Reynolds Numbers on Unmanned Aerial Vehicle Airfoil

The operational regime of Unmanned Aerial Vehicles (UAVs) is distinguished by the dominance of laminar flow and the flow field is characterized by the appearance of Laminar Separation Bubbles (LSBs). Ice accretion on the leading side of the airfoil leads to the formation of an Ice-induced Separation Bubble (ISB). These separation bubbles have a considerable influence on the pressure, heat flux, and shear stress distribution on the surface of airfoils and can affect the prediction of aerodynamic coefficients. Therefore, it is necessary to capture these separation bubbles in the numerical simulations. Previous studies have shown that these bubbles can be modeled successfully using the Large Eddy Simulation (LES) and Direct Numerical Simulation (DNS) but are computationally costly. Also, for numerical modeling of ice accretion, the flow field needs to be recomputed at specific intervals, thus making LES and DNS unsuitable for ice accretion simulations. Thus, it is necessary to come up with a Reynolds-Averaged Navier–Stokes (RANS) equation-based model that can predict the LSBs and ISBs as accurately as possible. Numerical studies were performed to assess the fidelity of various RANS turbulence models in predicting LSBs and ISBs. The findings are compared with the experimental and LES data available in the literature. The structure of these bubbles is only studied from a pressure coefficient perspective, so an attempt is made in these studies to explain it using the skin friction coefficient distribution. The results indicate the importance of the use of transition-based models when dealing with low-Reynolds-number applications that involve LSB. ISB can be predicted by conventional RANS models but are subjected to high levels of uncertainty. Possible recommendations were made with respect to turbulence models when dealing with flows involving LSBs and ISBs, especially for ice accretion simulations.

Deep Reinforcement Learning-Augmented Spalart–Allmaras Turbulence Model: Application to a Turbulent Round Jet Flow

The purpose of this work is to explore the potential of deep reinforcement learning (DRL) as a black-box optimizer for turbulence model identification. For this, we consider a Reynolds-averaged Navier–Stokes (RANS) closure model of a round turbulent jet flow at a Reynolds number of 10,000. For this purpose, we augment the widely utilized Spalart–Allmaras turbulence model by introducing a source term that is identified by DRL. The algorithm is trained to maximize the alignment of the augmented RANS model velocity fields and time-averaged large eddy simulation (LES) reference data. It is shown that the alignment between the reference data and the results of the RANS simulation is improved by 48% using the Spalart–Allmaras model augmented with DRL compared to the standard model. The velocity field, jet spreading rate, and axial velocity decay exhibit substantially improved agreement with both the LES reference and literature data. In addition, we applied the trained model to a jet flow with a Reynolds number of 15,000, which improved the mean field alignment by 35%, demonstrating that the framework is applicable to unseen data of the same configuration at a higher Reynolds number. Overall, this work demonstrates that DRL is a promising method for RANS closure model identification. Hurdles and challenges associated with the presented methodology, such as high numerical cost, numerical stability, and sensitivity of hyperparameters are discussed in the study.

Secondary flows in the actuator-disk simulation of wind-turbine wakes

This study explores the generation of secondary flows of Prandtl's second kind in the actuator-disk simulation of wind-turbine wakes. Leveraging large-eddy simulation data and conducting an analysis of the mean streamwise vorticity budget, we uncover the physical mechanisms contributing to this phenomenon. Our investigations attribute the emergence of such flows to the spatial gradients of the Reynolds stresses in the wake downstream of the turbines, which are, in turn, influenced by ground effects. To further investigate the phenomenon, we specifically isolate the impact of secondary flows on the wake by employing a model recognized for its incapacity to capture such dynamics: a two-equation Reynolds-averaged Navier–Stokes (RANS) model founded on the linear eddy-viscosity hypothesis. By comparing the predictions of the RANS model with those of large-eddy simulations and wind-tunnel experiments, we highlight the effect of secondary flows on the wake structure and, in particular, the upward shift of the wake. Motivated by the obtained results, we then enhance the baseline RANS model by introducing a non-linear term within the Reynolds stress tensor. This modification leads to a more accurate representation of Reynolds stresses, enabling the RANS model to capture the secondary flows in the wake. Our analysis emphasizes the importance of employing advanced RANS models in the simulation of wind farms.

Comparison of RANS and LES turbulent flow models in a real stenosis

This study focuses on the performance of various turbulence models in predicting hemodynamic variables within a patient-specific geometry of the Brachiocephalic trunk exhibiting a severe stenosis. Numerical simulations employing Reynolds-averaged Navier-Stokes (RANS) and Large Eddy Simulation (LES) models were conducted, comparing four RANS with two LES models. Results indicated significant differences in turbulent structures between RANS and LES models, with the k-ω RANS model closely approximating LES throughout the cardiac cycle. The velocity and Turbulent Kinetic Energy (TKE) results were consistent in the stenosis region due to the proximity to the inlet and plug flow conditions. However, notable disparities were observed in bifurcation and outlet regions. Time-Averaged Wall Shear Stress (TAWSS) comparisons revealed that the k-ω-based models provided closer agreement with LES, particularly in atherosclerosis-prone areas. The study highlights the limitations and strengths of each turbulence model, emphasizing the importance of model selection in simulating complex cardiovascular conditions. While RANS models demonstrated computational efficiency, their accuracy varied across regions. The effectiveness of the k-ω model in capturing the intricacies of such a complex flow field suggests its potential as a reliable and accurate tool for simulating physiological conditions with strong curvature and advanced stenosis.

Using dispersion models at microscale to assess long-term air pollution in urban hot spots: A FAIRMODE joint intercomparison exercise for a case study in Antwerp

In the framework of the Forum for Air Quality Modelling in Europe (FAIRMODE), a modelling intercomparison exercise for computing NO2 long-term average concentrations in urban districts with a very high spatial resolution was carried out. This exercise was undertaken for a district of Antwerp (Belgium). Air quality data includes data recorded in air quality monitoring stations and 73 passive samplers deployed during one-month period in 2016. The modelling domain was 800 × 800 m2. Nine modelling teams participated in this exercise providing results from fifteen different modelling applications based on different kinds of model approaches (CFD – Computational Fluid Dynamics-, Lagrangian, Gaussian, and Artificial Intelligence). Some approaches consisted of models running the complete one-month period on an hourly basis, but most others used a scenario approach, which relies on simulations of scenarios representative of wind conditions combined with post-processing to retrieve a one-month average of NO2 concentrations.The objective of this study is to evaluate what type of modelling system is better suited to get a good estimate of long-term averages in complex urban districts. This is very important for air quality assessment under the European ambient air quality directives. The time evolution of NO2 hourly concentrations during a day of relative high pollution was rather well estimated by all models. Relative to high resolution spatial distribution of one-month NO2 averaged concentrations, Gaussian models were not able to give detailed information, unless they include building data and street-canyon parameterizations. The models that account for complex urban geometries (i.e. CFD, Lagrangian, and AI models) appear to provide better estimates of the spatial distribution of one-month NO2 averages concentrations in the urban canopy. Approaches based on steady CFD-RANS (Reynolds Averaged Navier Stokes) model simulations of meteorological scenarios seem to provide good results with similar quality to those obtained with an unsteady one-month period CFD-RANS simulations.