Inflow Generation Research Articles

Assessing the influences of future water development projects in Tekeze-Atbara-Setit basin on the Nile River inflow at Aswan, Egypt

Study regionThe Tekeze-Atbara-Setit (TAS) basin as a portion of the Eastern Nile Basin (ENB) in Africa. Study focusENB consists of four sub-basins; one of them is the Tekeze-Atbara-Setit basin. TAS basin is subject to future water development projects, including irrigation projects and hydropower dams. Potential impacts of these projects need to be assessed regarding the inflow and hydroelectric generation at Egypt's High Aswan Dam (HAD). New hydrological insights for the regionTwo models are coupled offline; The Soil Water Assessment Tool (SWAT) model and HEC-Reservoir Simulation Model (HEC-ResSim). Base-case scenario is created without the expected future projects, in addition to five additional scenarios representing hydropower and irrigation projects. The maximum annual inflow at HAD declines by 1.6 km3 in the hydropower scenarios, while the produced power at HAD descends by 9.5 %. The maximum reduction in the annual inflow for hydropower and irrigation projects scenario at HAD is 4.63 km3 and 35.2 % for power reduction. Finally, the proposed future development project in TAS basin will have negative impacts on the flow, and generated hydropower at HAD in Egypt.

Inflow generation using Thomas- Fiering model for Thaphanseik Reservoir in Myanmar

Thomas-Fiering (T-F) model was applied for generating synthetic streamflow for the Thaphanseik reservoir. The Thomas-Fiering model accommodated the non-stationarity of seasonal data. Time series of streamflow are crucial for the planning, design, and management of various water resource systems. In this study, the model was tested using historical data spanning 39 years (from 1985 to 2023). The model’s performance was evaluated by using statistical measurements such as Coefficient of Determination (R2) and Nash-Sutcliffe Efficiency (NSE). Additionally, this model was utilized to generate synthetic streamflow data for the years 2024 to 2100. The logarithmic transformation method was used in order to avoid the negative flows in the synthetic data. In this study, synthesis flow data were generated using different random sequences. The mean, standard deviation and correlation coefficient of different synthetic series were calculated. The calibration process was performed for the periods 1985 to 2016 and validation process was performed for the years 2017 to 2023. Based on R2 value, most suitable synthetic series were chosen. The generated data showed a high goodness of fit, with R² and NSE values. An analysis of the historical and synthetic discharge statistics revealed that the model successfully captured the features of the historical data and integrated them into the generated sequences.

In-Flow Generation of Thionyl Fluoride (SOF2) Enables the Rapid and Efficient Synthesis of Acyl Fluorides from Carboxylic Acids.

Herein, we report an approach for generating thionyl fluoride (SOF2) from the commodity chemicals thionyl chloride (SOCl2) and potassium fluoride (KF). The methodology relies on a microfluidic device that can efficiently produce and dose this toxic gaseous reagent under extremely mild and safe conditions. Subsequently, the in situ-generated thionyl fluoride is reacted with an array of structurally and electronically differing carboxylic acids, leading to the direct and efficient synthesis of highly sought-after acyl fluorides. Importantly, our investigation also highlights the inherent modularity of this flow-based platform. We demonstrate the adaptability of this approach by not only synthesizing acyl fluorides but also directly converting carboxylic acids into a diverse array of valuable compounds such as esters, thioesters, amides, and ketones. This versatility showcases the potential of this approach for a wide range of synthetic applications, underscoring its significance in the realm of chemical synthesis.

Tailoring anisotropic synthetic inflow turbulence generator for wind turbine wake simulations

In computational fluid dynamics, defining precise boundary conditions, especially at inlets, is of great importance. Inlet flows typically exhibit natural turbulence, which is managed in various ways in scale-resolving simulations. Methods to establish turbulent inlet conditions are commonly created using natural transition, uncorrelated oscillations, periodic boundary conditions from auxiliary simulations, or synthetic turbulent fields. In this study, we explore a technique aimed at generating a divergence-free synthetic inflow turbulence with arbitrary anisotropy. The methodology is based on the conventional portrayal of turbulence as consisting of several coherent structures. While our approach adeptly emulates predefined statistical characteristics across different scales, its primary focus is on generating input parameters that impact the airflow within the wake of individual wind turbines and the atmospheric boundary layer within a wind farm. The results are compared with high-resolution velocity experimental measurements, large eddy simulations, and the digital filter-based inlet boundary condition already available in OpenFOAM. The findings demonstrate that the applied inflow generator outperforms the default OpenFOAM filter, particularly in the context of a single wind turbine.

Predicting climate-driven changes in reservoir inflows and hydropower in Côte d'Ivoire using machine learning modeling

This study investigates the impact of climate change and variability on reservoir inflow and hydropower generation at three key hydropower plants in Côte d'Ivoire including Buyo, Kossou, and Taboo. To simulate inflow to reservoir and energy generation, the Random Forest (RF), a machine-learning algorithm allowing fewer input variables was applied. In three-step, RF k-fold cross validation (with k = 5) was used; (i) 12 and 6 multiple lags of precipitation and temperature at monthly increments were used as predictors, respectively; (ii) the five most important variables were used in addition to the current month's precipitation and temperature; and (iii) a residual RF was built. The bias-adjusted ensemble mean of eleven climate models output of the COordinated Regional Downscaling Experiment was used for the representative concentration pathways (RCP4.5 and RCP8.5). The model output was highly correlated with the observations, with Pearson correlations >0.90 for inflow and >0.85 for energy for the three hydropower plants. The temperature in the selected sub-catchments may increase significantly from 0.9 to 3 °C in the near (2040–2069) and from 1.7 to 4.2 °C in far (2070–2099) future periods relative to the reference period (1981–2010). A time series of precipitation showed a change in range −7 and 15 % in the near and −8 to 20 % in the far future and more years are with increasing change. Depending on the sub-catchment, the magnitude of temperature and precipitation changes will increase as greenhouse gas emissions (GHG)(greater in RCP8.5 than RCP4.5) rise. At all time scales (monthly, seasonal, and annual), the simulated inflow and energy changes were related to climate variables such as temperature and precipitation. At the annual time scale, the inflow is projected to change between −10 and 37 % and variability may depend on the reservoir. However, the energy change is promised to change between −10 and 25 %, −30 to 15 %, and 5–40 % relative to the historical (1981–2010) period for Taabo, Kossou, and Buyo dams, respectively at an annual scale. The changes may vary according to the year, the RCPs, and the dam. Consequently, decision-makers are recommended to take into consideration an energy mix plan to meet the energy demand in these seasons.

Large-eddy simulation of wind pressures on elevated low-rise buildings

Residential buildings in coastal communities are often elevated to mitigate flooding and wave-surge impacts. However, the elevations change the local wind field characteristics and may increase the aerodynamic pressure on buildings. Post-event reconnaissance showed that elevated buildings experienced severe structural damage to the roofs, walls, and floors during major hurricanes. Currently, our understanding of aerodynamic pressure on elevated houses is limited. In this paper, a large eddy simulation (LES)-based method is developed to better understand the wind effects on elevated buildings. The inflow generation method, discretizing and synthesizing random flow generation, is adopted to generate inflow boundary conditions satisfying the target spectrum. Two sub-grid scale models, the Smagorinsky and wall-adapted local eddy-viscosity models, are employed to represent the unresolved small-scale eddies. It is found that the eddy structure sizes can strongly affect the pressure fluctuations at the eddy separation zones. The present study advances the understanding of aerodynamics on elevated buildings and provides a reference for future LES-based research on wind effect modeling.

On the settling of a spherical particle in slightly perturbed ambient fluid

Direct numerical simulations of the settling of a spherical particle under the action of gravity in a slightly perturbed ambient fluid have been performed. The ambient perturbations are generated using a synthetic turbulence inflow generator method, and their length scale and intensity are varied to study their influence on the particle motion. The Galileo number is 151 and the solid-to-fluid density ratio is 1.5, so that in the absence of perturbations, the particle settles following a steady vertical trajectory. It has been found that the ambient perturbations trigger the formation of double-threaded vortical structures in the wake of the particle. These structures resemble those that appear in the oblique oscillating regime that is found in the absence of perturbations at higher Galileo numbers. Due to the flow perturbations the particle is pushed randomly in all directions, and this results in a combination of slow lateral drifts along fixed directions and relatively fast excursions in random directions. The particle response has been characterized using probability density functions of the velocity in the cross-plane and persistence probability. The slow drifts are strongly influenced by the size of the perturbations and by the rotational motion of the particle, while the intensity of the perturbations seems to play a minor role.

Realistic turbulent inflow conditions for estimating the performance of a floating wind turbine

Abstract. A novel method for generating turbulent inflow boundary conditions for aeroelastic computations is proposed, based on interfacing hybrid hot-wire and particle image velocimetry measurements performed in a wind tunnel to a full-scale load simulation conducted with FAST. This approach is based on the use of proper orthogonal decomposition (POD) to interpolate and extrapolate the experimental data onto the numerical grid. The temporal dynamics of the temporal POD coefficients is driven by the high-frequency hot-wire measurements used as input for a lower-order model built using a multi-time-delay linear stochastic estimation (LSE) approach. Being directly extracted from the data, the generated three-component velocity fields later used as inlet conditions present correct one- and two-point spatial statistics and realistic temporal dynamics. Wind tunnel measurements are performed at a scale of 1:750, using a properly scaled porous disk as a floating wind turbine model. The motions of the platform are imposed by a linear actuator. Between all 6 degrees of freedom (DOFs) possible, the present study focus on the streamwise direction motion of the model (surge motion). The POD analysis of the flow, with or without considering the presence of the surge motion of the model, shows that a few modes are able to capture the characteristics of the most energetic flow structures and the main features of the wind turbine wake, such as its meandering and the influence of the surge motion. The interfacing method is first tested to estimate the performance of a wind turbine in an offshore boundary layer and then those of a wind turbine immersed in the wake of an upstream wind turbine subjected to a sinusoidal surge motion. Results are also compared to those obtained using the standard inflow generation method provided by TurbSim available in FAST.

Analysis of improved digital filter inflow generation methods for compressible turbulent boundary layers

We propose several enhancements to improve the accuracy and performance of the digital filter turbulent inflow generation technique and assess their efficacy in the context of wall-resolved large-eddy simulations of a compressible turbulent boundary layer. Improvements of accuracy include a more realistic correlation function for the transversal directions, target length scales that vary with wall-distance, and a counter-intuitive approach that involves the suppression of streamwise velocity fluctuations at the inflow. For improving the computational performance, we propose to generate the inflow data in parallel in single precision and at a prescribed time interval based on the turbulence time scale, and not at every time-step of the simulation. Based on the results of 7 wall-resolved large-eddy simulations, we find that the new correlation functions and the considered performance improvements are beneficial and therefore desired. Suppressing streamwise velocity fluctuations at the inflow leads to the fastest relaxation of the pressure fluctuations; however, this approach increases the adaptation length defined in terms of compliance with the von Kármán integral equation. The adaptation length can be shortened by artificially increasing the wall-normal Reynolds stresses, thereby preserving the desired turbulence kinetic energy level. A detailed inspection of the Reynolds stress transport budgets reveals that the observed spurious spatial transients are largely driven by pressure-related terms. For instance, increased values of u′p′¯ are found throughout the computational domain when a physical Reynolds stress distribution is prescribed at the inflow. Therefore, efforts to enhance digital filter techniques should aim at modeling pressure fluctuations as well as their correlation with the velocity components.

Climate-associated risks for reliability, resilience, vulnerability and sustainability of irrigation reservoirs in small ungauged watersheds

Climate change poses an existential threat to the functional integrity of the network of agricultural reservoirs responsible for sustaining rice production in South Korea. Anthropogenic interventions have triggered a cycle of droughts and floods by magnifying the already existing supply–demand gap, which is seriously hampering reservoir performance. The watersheds of most agricultural reservoirs in South Korea are ungauged, and inflow and outflow data are not measured. In this study, recorded volumetric water storage data from five reservoirs were used to derive observed inflow data based on the hydrological reasoning and reservoir operation rule curves. These data were then used to evaluate the performance of a lumped rainfall-runoff model in simulating the runoff generated in upstream ungauged watersheds. A water balance analysis was conducted for 400 major agricultural reservoirs spread throughout the country during 1973–2017. Performance indices were estimated based on inflow availability in the reservoirs and downstream irrigation demands. Empirical relationships were derived to predict performance indices by using the reservoirs’ physical characteristics as input variables. Generally, reservoirs received substantially higher inflows compared to irrigation demands, suggesting sufficient water availability during the rice growing season (Apr−Sep). An out-of-phase cycle of peak inflow generation and water demand periods induced frequent failure events during the rice nursery transplanting period (May−Jun), and reservoir sustainability was minimal in these months. Southern and southwestern major agricultural regions with a higher density of small- to medium-sized reservoirs would be at higher risk of climate-induced water scarcity. Upsizing storage capacity could alleviate the water deficit in reservoirs associated with watersheds featuring higher means and lower standard deviations of runoff. A watershed-to-irrigated area ratio > 5 indicated acceptable reservoir sustainability.

A Turbulent Inflow Generation Method for the LES of High Re Flow by Scaling Low Re Flow Data

The rescaling–recycling method (RRM) is usually used to generate turbulent inflow for the LES of compressible wall-bounded flows, which can lead to relatively high computational cost for high Re flows since the mesh resolution increases exponentially with Re number. A turbulent inflow generation method based on the scaling of low Re flow, referred as TIG-LowRe, is proposed, aiming at reducing the computational cost when applying the RRM. To validate the proposed method, the TIG-LowRe method was applied to generate turbulent inflow for the LES of a non-isothermal round jet flow at Re = 86,000. Two cases were carried out with the inflow generated based on two round pipe flows at Re = 10,000 and 24,000. The results show that the mean and fluctuating temperatures of the two cases agree well with the experimental data. In the case of low Re flow at Re = 10,000, the jet flow decays too fast along the axial direction, the mean and fluctuating axial velocities are over-predicted and the radial fluctuating velocity is under-predicted. By increasing the Re of the low Re flow to 24,000, the decay rate of the jet flow decreases and the accuracies of the mean and fluctuating axial velocities are obviously improved, while the radial fluctuating velocity shifts further away from the experimental data. The main reason for the difference between the two cases is that more fine turbulent structure of the inflow in case-Re10000 is lost than in case-Re24000 during the turbulence generation process.

Large Eddy Simulation Inflow Generation Using Reduced Length Scales for Flows Past Low-Rise Buildings

When undertaking wind assessment around buildings using large eddy simulation (LES), the implementation of the integral length scale at the inlet for inflow generation is controversial, as real atmospheric length scales require huge computational domains. While length scales significantly influence inflow generation in the domain, their effect on the downstream flow field has not, as yet, been investigated. In this paper, we validate the effectiveness and accuracy of implementing a reduced turbulence integral length scale for inflow generation in LES results at the rooftop of low-rise buildings and develop a technique to estimate the real local length scales using simulation results. We measure the wind locally and calculate the turbulence length scales from the energy spectrum of the wind data and simulation data. According to these results, there is an excellent agreement between the length scale from simulation and measurement when they are scaled with their corresponding freestream/inlet value. These results indicate that a reduced integral length scale can be safely used for LES to provide a reliable prediction of the energy spectrum as well as the length scales around complex geometries. The simulation results were confidently employed to obtain the best location for a wind turbine installation on low-rise buildings.

Reynolds stresses and turbulent heat fluxes in fan-shaped and cylindrical film cooling holes

Large eddy simulation (LES) is carried out to predict the thermal performance, unsteady flow patterns, and turbulence characteristics of the fan-shaped hole and the cylindrical hole cooling films. Velocity fields, Reynolds stresses, and turbulent heat flux distributions are the factors that ultimately determine the film cooling effectiveness by deciding the concentration of coolant and heat near the surface. Accurate prediction of these processes can provide a reliable data set for the design of film cooling systems. It can also help solve difficulties of improving RANS-based simulations in terms of their inaccuracies in matching measured flow rates for a given pressure drop across the film and the mixing process once the coolant is ejected from the film. Credible estimates and modest costs of the current LES originate from the multiblock hexahedra meshing, the turbulence inflow generator, and the numerical schemes implemented. Multiblock hexahedra meshes are adopted and generated by a quasi-automatic mesh generation algorithm utilizing template-based multi-block construction followed by elliptic smoothing. Computational resources are utilized in a way that mesh refinement exists only near cooling decorations of small size and wall boundaries, without the need for associated clustering in the far field which is commonly used in commercial packages. The high orthogonality and continuous smoothness throughout the computational domain are maintained to facilitate turbulence capturing. The synthetic inflow generator produces a random field matching a realistic set of two-point statistics based on eigen-reconstruction in a computationally inexpensive processing step. To prove that the current LES simulations of modest cost can reproduce with high accuracy, the discharge characteristics, velocity, and turbulence intensity profiles of cylindrical and fan-shaped cooling films are compared with published measured data on the same flow configurations. Results reveal that the set of modeling methodologies is valid for calculating film-cooling performance within an acceptable range of accuracy. The energy-carrying turbulence structures in and near the cooling holes are shown and their behaviors are linked to turbulent Reynolds stresses. Reynolds stresses and turbulent heat fluxes are compared for different blowing ratios and two types of cooling holes in the parametric study. Similarity patterns of velocity profiles, non-dimensional temperature profiles, Reynolds stress and turbulent heat flux profiles are discussed.

Investigation of peak wind loading on a high-rise building in the atmospheric boundary layer using large-eddy simulations

Significant negative peak pressures have been observed in two recent wind tunnel experiments of a high-rise building for certain wind directions. This peak wind loading is crucial for the design of cladding systems. However, the governing flow physics is not well understood. In this study, large-eddy simulations with sufficient resolution are performed to capture and analyze these peak pressure phenomena. The atmospheric boundary layer flow is generated using a divergence free synthetic turbulence inflow generator before the high-rise building is placed in the flow at various wind directions. The mean, standard deviation, and peak pressure coefficients are shown to agree well with the experimental measurements. The strongest negative peak pressures near the top trailing corner on the leeward surface are captured by simulations with the resolved scale between the Taylor microscale and Kolmogorov scale. The probability density function of the pressure at the top trailing corner is well approximated using a log-normal distribution, which is a signature of the effect of small-scale turbulence intermittency. Flow visualization indicates that the strong negative peak values result from the interaction between small eddies shed from the separated flow region at the upwind roof edge and larger eddies downstream of the leeward roof edge.

Plasma-Activated Mist: Continuous-Flow, Scalable Nitrogen Fixation, and Aeroponics

Nitrogen fixation underpins diverse biological and industrial processes and is currently one of the leading producers of carbon emissions at a global scale. Radical solutions to decarbonize nitrogen fixation include plasma-electrified ammonia (NH3) synthesis using water and atmospheric nitrogen. Here, we resolve the intrinsic limitations of the state-of-the-art solutions in (i) energy efficiency; (ii) scalability; (iii) direct use of clean renewable energy; and (iv) direct sustainable application of water-based nitrogen fixation by the novel, scalable plasma-enabled process and system for the continuous-flow, scalable nitrogen fixation, and aeroponics using plasma-activated mist (PAM). The new approach is based on the continuous, scalable, in-flow generation of PAM containing NH4+, NO3–, NO2–, and other nitrogen-fixation species through the reaction of large-area uniform air plasma and high-flux water mist containing large area-to-volume ratio micron-sized droplets. Through the solar-energy-driven plasma-assisted oxidation confined within the droplet micro-reactors, a liquid-phase nitrogen fixation product dominated by NO3– is produced. This PAM nitrogen fixation system is applied for the continuous delivery of nitrogen-based nutrients directly to the roots of living plants using a custom-designed aeroponic system which increases the leaf emergence rate and leaf area of bean sprouts by more than 30%. The unique energy concentration in droplet microreactors leads to the much increased (from 2 to 39 times) energy efficiency at a larger scale compared to the key types of common lab-scale plasma reactors. Compatibility with direct solar power, flow-reactor chemistry, and electrified processes at industry-relevant scales make this low-cost, low-carbon-footprint, renewable-energy-driven process and system promising for the widespread sustainable and distributed production and applications of plasma-enabled nitrogen fixation.

Turbulent Inflow Generation for Large-Eddy Simulation of Winds around Complex Terrain

Accurate turbulent inflow conditions are needed to broaden the application of the large-eddy simulation technique to predict winds around arbitrarily complex terrain. We investigate the concept of buoyancy perturbations with colored noise to trigger turbulence in upstream flows approaching complex terrain regions. Random perturbations are imposed on the source term in the pseudo-temperature transport equation. These perturbations are effective within three-dimensional boxes and scaled using a bulk Richardson number defined for each box. We apply the turbulent inflow generation technique to predict winds around the Askervein and Bolund Hills under neutrally stratified conditions. We find that a common value for the bulk Richardson number works well for a variety of flow problems. Additionally, we show that the height of the perturbation box plays an important role in the accuracy of the predictions around complex terrain. We consistently obtained good results for both simulation cases when the perturbation box height was made a fraction of the Obukhov length scale.

A transformer-based synthetic-inflow generator for spatially developing turbulent boundary layers

This study proposes a newly developed deep-learning-based method to generate turbulent inflow conditions for spatially developing turbulent boundary layer (TBL) simulations. A combination of a transformer and a multiscale-enhanced super-resolution generative adversarial network is utilised to predict velocity fields of a spatially developing TBL at various planes normal to the streamwise direction. Datasets of direct numerical simulation (DNS) of flat plate flow spanning a momentum thickness-based Reynolds number, $Re_\theta = 661.5\unicode{x2013}1502.0$ , are used to train and test the model. The model shows a remarkable ability to predict the instantaneous velocity fields with detailed fluctuations and reproduce the turbulence statistics as well as spatial and temporal spectra with commendable accuracy as compared with the DNS results. The proposed model also exhibits a reasonable accuracy for predicting velocity fields at Reynolds numbers that are not used in the training process. With the aid of transfer learning, the computational cost of the proposed model is considered to be effectively low. Furthermore, applying the generated turbulent inflow conditions to an inflow–outflow simulation reveals a negligible development distance for the TBL to reach the target statistics. The results demonstrate for the first time that transformer-based models can be efficient in predicting the dynamics of turbulent flows. They also show that combining these models with generative adversarial networks-based models can be useful in tackling various turbulence-related problems, including the development of efficient synthetic-turbulent inflow generators.

Generation of turbulent inflow data from realistic approximations of the covariance tensor

This study presents a novel synthetic inflow generator capable of producing a random field matching a realistic set of two-point statistics with minimal input. The method is based on two main elements. The first element is a procedure to infer realistic two-point covariance tensors from readily available data (e.g., freestream velocity, boundary layer thickness, and turbulence intensity) by a preliminary Reynolds-averaged Navier–Stokes simulation with an explicit algebraic Reynolds stress model closure. The second element is an efficient eigen-decomposition step of the two-point correlation tensor, which determines a set of modes. The modal decomposition guarantees the spatial correlation in transversal directions, while the temporal correlation/streamwise spatial correlation is obtained by digital filters based on longitudinal and transversal spectra of a realistic shape and Taylor's hypothesis. The instantaneous inlet flow field is obtained by a linear combination of the modes via uncorrelated random weights with unit variance. The modes are generated in a computationally inexpensive pre-processing step. Compared to existing inflow generation methods that try to match given two-point statistics, the proposed method relieves the burden of obtaining data from direct numerical simulation (DNS) or experiments, while the complexity of the eigenvalue problem that needs to be solved is reduced. The proposed method is shown to produce a realistic turbulent channel flow and a realistic turbulent boundary layer by the large-eddy simulation, which contains statistics that are in good agreement with results from DNS. The proposed inflow generator features, cost-effectiveness, robustness, and potential for generalization to complex geometries.

Freestream Turbulence Effects on the Aerodynamics of an Oscillating Square Cylinder at the Resonant Frequency

Flow past a bluff body in freestream turbulence can substantially change the flow behaviour compared to that in smooth inflow. This paper presents the study of wake flow and aerodynamics of an oscillating square cylinder at the resonant frequency in freestream turbulence, with the integral length not greater than the cylinder side and the turbulence intensity not greater than 10%. Large eddy simulations (LES) in the Cartesian grid using the Immersed Boundary Method (IBM) technique embedded in a FVM solver, together with an efficient synthetic turbulent inflow generator implemented in an in-house parallel FORTRAN code are used for the study. The results are compared with those for smooth inflow, and relevant data published in the literature. The key findings are: the freestream turbulence conditions evidently reduces the local turbulent scales and fluctuations in the shear layer compared to in smooth flow, as small scale freestream turbulence breaks down cylinder-generated larger scale eddies and weakens them; but does not evidently affect the vortex shedding frequency, or the length of the recirculation region behind the cylinder. This suggests negligible change of drag coefficient compared to in smooth inflow. Moreover, this is because the vortex shedding is dominated by the forced oscillation at the resonance frequency, and the turbulence intensity is small.

Calibrated consistent flow generator for tall building aerodynamics using large eddy simulation

Ensuring proper matching of the target wind characteristics of the inflow is vital for the accuracy of both experimental and numerical wind studies. In the current study, a calibrated turbulent inflow generation technique was developed to accurately simulate the inflow boundary condition for large eddy simulation (LES) of the lower region of the atmospheric boundary layer (ABL) based on a newly developed technique, namely consistent discrete random flow generator (CDRFG). The proposed technique, namely Calibrated-CDRFG (C-CDRFG), targets specific incoming turbulence at distances downstream to account for dissipation of the turbulent kinetic energy. The proposed technique generates accurate turbulent velocities with proper turbulence intensity, spectra, coherency, and correlation at the target distance downstream for a range of terrain conditions. The technique was validated by evaluating the wind-induced loads and responses for the Commonwealth Advisory Aeronautical Research Council (CAARC) and comparing that to the existing wind tunnel (WT) wind-induced response for the angle of attack (AOA) ranging between 0° and 90°. It was found that the resulting wind-induced response from the C-CDRFG technique resulted in an average matching of 91% of the wind tunnel results. The proposed technique is believed to be computationally efficient, flexible, and easy to be sustainable for parallel computing environments and thus provides significant value for Large Eddy Simulation (LES) wind engineering applications.