scholarly journals Efficacy of the Cell Perturbation Method in Large-Eddy Simulations of Boundary Layer Flow over Complex Terrain

Atmosphere ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 55
Author(s):  
Alex Connolly ◽  
Leendert van Veen ◽  
James Neher ◽  
Bernard J. Geurts ◽  
Jeff Mirocha ◽  
...  
Keyword(s):  
Perturbation Method ◽  
Complex Terrain ◽  
Wrf Model ◽  
Multiscale Simulation ◽  
Atmospheric Conditions ◽  
Mean Flow ◽  
Area Of Interest ◽  
Stable Conditions ◽  
Large Eddy ◽  
Weakly Stable

A challenge to simulating turbulent flow in multiscale atmospheric applications is the efficient generation of resolved turbulence motions over an area of interest. One approach is to apply small perturbations to flow variables near the inflow planes of turbulence-resolving simulation domains nested within larger mesoscale domains. While this approach has been examined in numerous idealized and simple terrain cases, its efficacy in complex terrain environments has not yet been fully explored. Here, we examine the benefits of the stochastic cell perturbation method (CPM) over real complex terrain using data from the 2017 Perdigão field campaign, conducted in an approximately 2-km wide valley situated between two nearly parallel ridges. Following a typical configuration for multiscale simulation using nested domains within the Weather Research and Forecasting (WRF) model to downscale from the mesoscale to a large-eddy simulation (LES), we apply the CPM on a domain with horizontal grid spacing of 150 m. At this resolution, spurious coherent structures are often observed under unstable atmospheric conditions with moderate mean wind speeds. Results from such an intermediate resolution grid are often nested down for finer, more detailed LES, where these spurious structures adversely affect the development of turbulence on the subsequent finer grid nest. We therefore examine the impacts of the CPM on the representation of turbulence within the nested LES domain under moderate mean flow conditions in three different stability regimes: weakly convective, strongly convective, and weakly stable. In addition, two different resolutions of the underlying terrain are used to explore the role of the complex topography itself in generating turbulent structures. We demonstrate that the CPM improves the representation of turbulence within the LES domain, relative to the use of high-resolution complex terrain alone. During the convective conditions, the CPM improves the rate at which smaller-scales of turbulence form, while also accelerating the attenuation of the spurious numerically generated roll structures near the inflow boundary. During stable conditions, the coarse mesh spacing of the intermediate LES domain used herein was insufficient to maintain resolved turbulence using CPM as the flow develops downstream, highlighting the need for yet higher resolution under even weakly stable conditions, and the importance of accurate representation of flow on intermediate LES grids.

Examination of Errors in Near-Surface Temperature and Wind from WRF Numerical Simulations in Regions of Complex Terrain

2013 ◽  
Vol 28 (3) ◽  
pp. 893-914 ◽  
Author(s):  
Hailing Zhang ◽  
Zhaoxia Pu ◽  
Xuebo Zhang
Keyword(s):  
Complex Terrain ◽  
Forecast Error ◽  
Wrf Model ◽  
Atmospheric Temperature ◽  
Lower Atmosphere ◽  
Forecast Errors ◽  
Atmospheric Conditions ◽  
Near Surface ◽  
System A ◽  
Synoptic Forcing

Abstract The performance of an advanced research version of the Weather Research and Forecasting Model (WRF) in predicting near-surface atmospheric temperature and wind conditions under various terrain and weather regimes is examined. Verification of 2-m temperature and 10-m wind speed and direction against surface Mesonet observations is conducted. Three individual events under strong synoptic forcings (i.e., a frontal system, a low-level jet, and a persistent inversion) are first evaluated. It is found that the WRF model is able to reproduce these weather phenomena reasonably well. Forecasts of near-surface variables in flat terrain generally agree well with observations, but errors also occur, depending on the predictability of the lower-atmospheric boundary layer. In complex terrain, forecasts not only suffer from the model's inability to reproduce accurate atmospheric conditions in the lower atmosphere but also struggle with representative issues due to mismatches between the model and the actual terrain. In addition, surface forecasts at finer resolutions do not always outperform those at coarser resolutions. Increasing the vertical resolution may not help predict the near-surface variables, although it does improve the forecasts of the structure of mesoscale weather phenomena. A statistical analysis is also performed for 120 forecasts during a 1-month period to further investigate forecast error characteristics in complex terrain. Results illustrate that forecast errors in near-surface variables depend strongly on the diurnal variation in surface conditions, especially when synoptic forcing is weak. Under strong synoptic forcing, the diurnal patterns in the errors break down, while the flow-dependent errors are clearly shown.

High-resolution atmospheric boundary layer simulations using WRF-LES

2020 ◽  
Author(s):  
Gokhan Kirkil
Keyword(s):  
Boundary Layer ◽  
Large Eddy Simulation ◽  
Cross Sections ◽  
Wrf Model ◽  
Field Measurements ◽  
Mean Flow ◽  
Spatial And Temporal Scales ◽  
Eddy Simulation ◽  
Wide Range ◽  
Large Eddy

<p>WRF model provides a potentially powerful framework for coupled simulations of flow covering a wide range of<br>spatial and temporal scales via a successive grid nesting capability. Nesting can be repeated down to turbulence<br>solving large eddy simulation (LES) scales, providing a means for significant improvements of simulation of<br>turbulent atmospheric boundary layers. We will present the recent progress on our WRF-LES simulations of<br>the Perdigao Experiment performed over mountainous terrain. We performed multi-scale simulations using<br>WRF’s different Planetary Boundary Layer (PBL) parameterizations as well as Large Eddy Simulation (LES)<br>and compared the results with the detailed field measurements. WRF-LES model improved the mean flow field<br>as well as second-order flow statistics. Mean fluctuations and turbulent kinetic energy fields from WRF-LES<br>solution are investigated in several cross-sections around the hill which shows good agreement with measurements.</p>

The Dispersion of Silver Iodide Particles from Ground-Based Generators over Complex Terrain. Part II: WRF Large-Eddy Simulations versus Observations

2014 ◽  
Vol 53 (6) ◽  
pp. 1342-1361 ◽  
Author(s):  
Lulin Xue ◽  
Xia Chu ◽  
Roy Rasmussen ◽  
Daniel Breed ◽  
Bruce Boe ◽  
...  
Keyword(s):  
Complex Terrain ◽  
Silver Iodide ◽  
Wrf Model ◽  
Static Stability ◽  
Particle Dispersion ◽  
Grid Spacing ◽  
Medicine Bow Mountains ◽  
Eddy Simulation ◽  
Large Eddy ◽  
Orographic Clouds

AbstractA numerical modeling study has been conducted to explore the ability of the Weather Research and Forecasting (WRF) model-based large-eddy simulation (LES) with 100-m grid spacing to reproduce silver iodide (AgI) particle dispersion by comparing the model results with measurements made on 16 February 2011 over the Medicine Bow Mountains in Wyoming. Xue et al.'s recently developed AgI cloud-seeding parameterization was applied in this study to simulate AgI release from ground-based generators. Qualitative and quantitative comparisons between the LES results and observed AgI concentrations were conducted. Analyses of turbulent kinetic energy (TKE) features within the planetary boundary layer (PBL) and comparisons between the 100-m LES and simulations with 500-m grid spacing were performed as well. The results showed the following: 1) Despite the moist bias close to the ground and above 4 km AGL, the LES with 100-m grid spacing captured the essential environmental conditions except for a slightly more stable PBL relative to the observed soundings. 2) Wind shear is the dominant TKE production mechanism in wintertime PBL over complex terrain and generates a PBL of about 1000-m depth. The terrain-induced turbulent eddies are primarily responsible for the vertical dispersion of AgI particles. 3) The LES-simulated AgI plumes were shallow and narrow, in agreement with observations. The LES overestimated AgI concentrations close to the ground, which is consistent with the higher static stability in the model than is observed. 4) Non-LES simulations using PBL schemes had difficulty in capturing the shear-dominant turbulent PBL structure over complex terrain in wintertime. Therefore, LES of wintertime orographic clouds with grid spacing close to 500 m or finer are recommended.

scholarly journals Evaluation of WRF-Predicted Near-Hub-Height Winds and Ramp Events over a Pacific Northwest Site with Complex Terrain

2013 ◽  
Vol 52 (8) ◽  
pp. 1753-1763 ◽  
Author(s):  
Qing Yang ◽  
Larry K. Berg ◽  
Mikhail Pekour ◽  
Jerome D. Fast ◽  
Rob K. Newsom ◽  
...  
Keyword(s):  
Wind Speed ◽  
Pacific Northwest ◽  
Complex Terrain ◽  
Capture Rate ◽  
Atmospheric Conditions ◽  
Doppler Sodar ◽  
Stable Conditions ◽  
Mean Wind Speed ◽  
Vertical Wind Speed ◽  
Pbl Parameterization

AbstractOne challenge with wind-power forecasts is the accurate prediction of rapid changes in wind speed (ramps). To evaluate the Weather Research and Forecasting (WRF) model's ability to predict such events, model simulations, conducted over an area of complex terrain in May 2011, are used. The sensitivity of the model's performance to the choice among three planetary boundary layer (PBL) schemes [Mellor–Yamada–Janjić (MYJ), University of Washington (UW), and Yonsei University (YSU)] is investigated. The simulated near-hub-height winds (62 m), vertical wind speed profiles, and ramps are evaluated against measurements obtained from tower-mounted anemometers, a Doppler sodar, and a radar wind profiler deployed during the Columbia Basin Wind Energy Study (CBWES). The predicted winds at near–hub height have nonnegligible biases in monthly mean under stable conditions. Under stable conditions, the simulation with the UW scheme better predicts upward ramps and the MYJ scheme is the most successful in simulating downward ramps. Under unstable conditions, simulations using the YSU and UW schemes show good performance in predicting upward ramps and downward ramps, with the YSU scheme being slightly better at predicting ramps with durations longer than 1 h. The largest differences in mean wind speed profiles among simulations using the three PBL schemes occur during upward ramps under stable conditions, which were frequently associated with low-level jets. The UW scheme has the best overall performance in ramp prediction over the CBWES site when evaluated using prediction accuracy and capture-rate statistics, but no single PBL parameterization is clearly superior to the others when all atmospheric conditions are considered.

scholarly journals Mesoscale to Microscale Simulations over Complex Terrain with the Immersed Boundary Method in the Weather Research and Forecasting Model

2020 ◽  
Vol 148 (2) ◽  
pp. 577-595 ◽  
Author(s):  
David J. Wiersema ◽  
Katherine A. Lundquist ◽  
Fotini Katopodes Chow
Keyword(s):  
Boundary Conditions ◽  
Immersed Boundary Method ◽  
Complex Terrain ◽  
Wrf Model ◽  
Weather Research And Forecasting ◽  
Immersed Boundary ◽  
Eddy Simulation ◽  
Boundary Method ◽  
Large Eddy ◽  
Terrain Following

Abstract Improvements to the Weather Research and Forecasting (WRF) Model are made to enable multiscale simulations over highly complex terrain with dynamically downscaled boundary conditions from the mesoscale to the microscale. Over steep terrain, the WRF Model develops numerical errors that are due to grid deformation of the terrain-following coordinates. An alternative coordinate system, the immersed boundary method (IBM), has been implemented into WRF, allowing for simulations over highly complex terrain; however, the new coordinate system precluded nesting within mesoscale simulations using WRF’s native terrain-following coordinates. Here, the immersed boundary method and WRF’s grid-nesting framework are modified to seamlessly work together. This improved framework for the first time allows for large-eddy simulation over complex (urban) terrain with IBM to be nested within a typical mesoscale WRF simulation. Simulations of the Joint Urban 2003 field campaign in Oklahoma City, Oklahoma, are performed using a multiscale five-domain nested configuration, spanning horizontal grid resolutions from 6 km to 2 m. These are compared with microscale-only simulations with idealized lateral boundary conditions and with observations of wind speed/direction and SF6 concentrations from a controlled release from intensive observation period 3. The multiscale simulation, which is configured independent of local observations, shows similar model skill predicting wind speed/direction and improved skill predicting SF6 concentrations when compared with the idealized simulations, which require use of observations to set mean flow conditions. Use of this improved multiscale framework shows promise for enabling large-eddy simulation over highly complex terrain with dynamically downscaled boundary conditions from mesoscale models.

A Total Turbulent Energy Closure Model for Neutrally and Stably Stratified Atmospheric Boundary Layers

2007 ◽  
Vol 64 (11) ◽  
pp. 4113-4126 ◽  
Author(s):  
Thorsten Mauritsen ◽  
Gunilla Svensson ◽  
Sergej S. Zilitinkevich ◽  
Igor Esau ◽  
Leif Enger ◽  
...  
Keyword(s):  
Potential Temperature ◽  
Stability Limit ◽  
Turbulent Energy ◽  
Large Eddy Simulations ◽  
Turbulence Closure ◽  
Turbulent Heat ◽  
Atmospheric Conditions ◽  
Mean Flow ◽  
Wide Range ◽  
Large Eddy

Abstract This paper presents a turbulence closure for neutral and stratified atmospheric conditions. The closure is based on the concept of the total turbulent energy. The total turbulent energy is the sum of the turbulent kinetic energy and turbulent potential energy, which is proportional to the potential temperature variance. The closure uses recent observational findings to take into account the mean flow stability. These observations indicate that turbulent transfer of heat and momentum behaves differently under very stable stratification. Whereas the turbulent heat flux tends toward zero beyond a certain stability limit, the turbulent stress stays finite. The suggested scheme avoids the problem of self-correlation. The latter is an improvement over the widely used Monin–Obukhov-based closures. Numerous large-eddy simulations, including a wide range of neutral and stably stratified cases, are used to estimate likely values of two free constants. In a benchmark case the new turbulence closure performs indistinguishably from independent large-eddy simulations.

scholarly journals Downscaled Finite Element Modeling of Metal Targets for Surface Roughness Level under Pulsed Laser Irradiation

2021 ◽  
Vol 11 (3) ◽  
pp. 1253
Author(s):  
Evaggelos Kaselouris ◽  
Kyriaki Kosma ◽  
Yannis Orphanos ◽  
Alexandros Skoulakis ◽  
Ioannis Fitilis ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Finite Element ◽  
Surface Acoustic Waves ◽  
Pulsed Laser ◽  
Multiscale Simulation ◽  
Experimental Methodology ◽  
Computational Domain ◽  
Area Of Interest ◽  
Depth Analysis ◽  
Laser Solid Interactions

A three-dimensional, thermal-structural finite element model, originally developed for the study of laser–solid interactions and the generation and propagation of surface acoustic waves in the macroscopic level, was downscaled for the investigation of the surface roughness influence on pulsed laser–solid interactions. The dimensions of the computational domain were reduced to include the laser-heated area of interest. The initially flat surface was progressively downscaled to model the spatial roughness profile characteristics with increasing geometrical accuracy. Since we focused on the plastic and melting regimes, where structural changes occur in the submicrometer scale, the proposed downscaling approach allowed for their accurate positioning. Additionally, the multiscale simulation results were discussed in relation to experimental findings based on white light interferometry. The combination of this multiscale modeling approach with the experimental methodology presented in this study provides a multilevel scientific tool for an in-depth analysis of the influence of heat parameters on the surface roughness of solid materials and can be further extended to various laser–solid interaction applications.

The Application of the Micro-Siting Technique in Tioman Island, Malaysia Using the RIAM-COMPACT Software

2014 ◽  
Vol 660 ◽  
pp. 745-749
Author(s):  
Rosly Nurhayati ◽  
Mohd Sofian
Keyword(s):  
Complex Terrain ◽  
Meteorological Data ◽  
Computational Prediction ◽  
Applied Mechanics ◽  
Eddy Simulation ◽  
Turbine Generators ◽  
Wind Turbine Generators ◽  
Large Eddy ◽  
Asean Countries ◽  
Wind Resources

ASEAN (Association of Southeast Asian Nations) countries may have a huge potential for utilizing wind energy as it requires little in the way of land. Land in these countries is very fertile and is used by other alternatives, therefore reducing its conduciveness for developing solar energy. The wind resources map is widely available for Laos, Vietnam, Thailand, Cambodia and Philippines but there is not much information about other ASEAN countries. Based on meteorological data, Tioman Island was selected as the area that had the best potential for installing wind turbines in Malaysia. A more detailed study was conducted using a CFD model for unsteady flow, known as the Research Institute for Applied Mechanics, Kyushu University, COMputational Prediction of Airflow over Complex Terrain (RIAM-COMPACT®) which is based on the Large-Eddy Simulation (LES) technique. Micro-siting technique is used as a tool for selecting appropriate point and an inappropriate point for locating wind turbine generators (WTGs) at Tioman Island, Malaysia. The suggested points for locating WTGs were shown based on the numerical results obtained from the calculation.

RANS and Large Eddy Simulation of Internal Combustion Engine Flows—A Comparative Study

2014 ◽  
Vol 136 (5) ◽  
Author(s):  
Xiaofeng Yang ◽  
Saurabh Gupta ◽  
Tang-Wei Kuo ◽  
Venkatesh Gopalakrishnan
Keyword(s):  
Large Eddy Simulation ◽  
High Speed ◽  
Combustion Engine ◽  
Flow Analysis ◽  
Partial Geometry ◽  
Computational Domain ◽  
Mean Flow ◽  
Eddy Simulation ◽  
Large Eddy ◽  
Rans Simulations

A comparative cold flow analysis between Reynolds-averaged Navier–Stokes (RANS) and large eddy simulation (LES) cycle-averaged velocity and turbulence predictions is carried out for a single cylinder engine with a transparent combustion chamber (TCC) under motored conditions using high-speed particle image velocimetry (PIV) measurements as the reference data. Simulations are done using a commercial computationally fluid dynamics (CFD) code CONVERGE with the implementation of standard k-ε and RNG k-ε turbulent models for RANS and a one-equation eddy viscosity model for LES. The following aspects are analyzed in this study: The effects of computational domain geometry (with or without intake and exhaust plenums) on mean flow and turbulence predictions for both LES and RANS simulations. And comparison of LES versus RANS simulations in terms of their capability to predict mean flow and turbulence. Both RANS and LES full and partial geometry simulations are able to capture the overall mean flow trends qualitatively; but the intake jet structure, velocity magnitudes, turbulence magnitudes, and its distribution are more accurately predicted by LES full geometry simulations. The guideline therefore for CFD engineers is that RANS partial geometry simulations (computationally least expensive) with a RNG k-ε turbulent model and one cycle or more are good enough for capturing overall qualitative flow trends for the engineering applications. However, if one is interested in getting reasonably accurate estimates of velocity magnitudes, flow structures, turbulence magnitudes, and its distribution, they must resort to LES simulations. Furthermore, to get the most accurate turbulence distributions, one must consider running LES full geometry simulations.

scholarly journals Domain-Adversarial Training of Self-Attention-Based Networks for Land Cover Classification Using Multi-Temporal Sentinel-2 Satellite Imagery

2021 ◽  
Vol 13 (13) ◽  
pp. 2564
Author(s):  
Mauro Martini ◽  
Vittorio Mazzia ◽  
Aleem Khaliq ◽  
Marcello Chiaberge
Keyword(s):  
Land Cover ◽  
Large Scale ◽  
Domain Adaptation ◽  
Learning Approaches ◽  
Atmospheric Conditions ◽  
Practical Applications ◽  
Area Of Interest ◽  
Multi Temporal ◽  
Significant Performance ◽  
Adversarial Training

The increasing availability of large-scale remote sensing labeled data has prompted researchers to develop increasingly precise and accurate data-driven models for land cover and crop classification (LC&CC). Moreover, with the introduction of self-attention and introspection mechanisms, deep learning approaches have shown promising results in processing long temporal sequences in the multi-spectral domain with a contained computational request. Nevertheless, most practical applications cannot rely on labeled data, and in the field, surveys are a time-consuming solution that pose strict limitations to the number of collected samples. Moreover, atmospheric conditions and specific geographical region characteristics constitute a relevant domain gap that does not allow direct applicability of a trained model on the available dataset to the area of interest. In this paper, we investigate adversarial training of deep neural networks to bridge the domain discrepancy between distinct geographical zones. In particular, we perform a thorough analysis of domain adaptation applied to challenging multi-spectral, multi-temporal data, accurately highlighting the advantages of adapting state-of-the-art self-attention-based models for LC&CC to different target zones where labeled data are not available. Extensive experimentation demonstrated significant performance and generalization gain in applying domain-adversarial training to source and target regions with marked dissimilarities between the distribution of extracted features.

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