Large-eddy simulation of airborne wind energy farms

The future utility-scale deployment of airborne wind energy technologies requires the development of large-scale multi-megawatt systems. This study aims at quantifying the interaction between the atmospheric boundary layer (ABL) and large-scale airborne wind energy systems operating in a farm. To that end, we present a virtual flight simulator combining large-eddy simulations to simulate turbulent flow conditions and optimal control techniques for flight-path generation and tracking. The two-way coupling between flow and system dynamics is achieved by implementing an actuator sector method that we pair to a model predictive controller. In this study, we consider ground-based power generation pumping-mode AWE systems (lift-mode AWES) and on-board power generation AWE systems (drag-mode AWES). For the lift-mode AWES, we additionally investigate different reel-out strategies to reduce the interaction between the tethered wing and its own wake. Further, we investigate AWE parks consisting of 25 systems organized in 5 rows of 5 systems. For both lift- and drag-mode archetypes, we consider a moderate park layout with a power density of 10 MW km−2 achieved at a rated wind speed of 12 m s−1. For the drag-mode AWES, an additional park with denser layout and power density of 28 MW km−2 is also considered. The model predictive controller achieves very satisfactory flight-path tracking despite the AWE systems operating in fully waked, turbulent flow conditions. Furthermore, we observe significant wake effects for the utility-scale AWE systems considered in the study. Wake-induced performance losses increase gradually through the downstream rows of systems and reach in the last row of the parks up to 17 % for the lift-mode AWE park and up to 25 % and 45 % for the moderate and dense drag-mode AWE parks, respectively. For an operation period of 60 minutes at a below-rated reference wind speed of 10 m s−1, the lift-mode AWE park generates about 84.4 MW of power, corresponding to 82.5 % of the power yield expected when AWE systems operate ideally and interaction with the ABL is negligible. For the drag-mode AWE parks, the moderate and dense layouts generate about 86.0 MW and 72.9 MW of power, respectively, corresponding to 89.2 % and 75.6 % of the ideal power yield.

Convective drying performance of porous moist objects under turbulent flow conditions: effects of object shape and material

Purpose The purpose of this paper is to examine the coupled heat and mass transport of different shaped porous moist objects in a rectangular channel under the effects of convective drying. Numerical simulations were performed under turbulent conditions for cylindrical, triangular and rectangular shaped different food products in a two-dimensional channel. Design/methodology/approach Finite element method was used for the unsteady problem and, effects of drying air velocity (AV) and temperature on transport mechanism were evaluated. Three different food materials were used for the circular shaped object and drying performance of the products under different conditions was compared. Findings Results showed that, changing the air temperature has an important effect on drying for all shaped objects and all materials. The same effect was seen for the AV as, increasing the velocity had positive effects on drying. Two identical objects were placed in the channel one behind the other, and this configuration showed that location of the object in the channel is also important for drying. The moisture content in the object at the front is lower than in the object behind at the end of drying. Originality/value This paper can provide technical support to optimize drying performance in the industry with comprehensive data for the process.

Introducing a Rheology Model for Non-Newtonian Drilling Fluids

An API standard drilling fluid was investigated from laminar to turbulent flow conditions using an in-house-built viscometer at speeds from 200 to 1600 RPM. A power-based method was applied to obtain the apparent viscosity and the shear stress of the water-based drilling mud (WBM) in the annulus of the viscometer. Then, a MATLAB optimization program was developed to obtain model parameters for five rheology models integrated in a generalized Herschel-Bulkley-Extended (HBE) model and two widely used 4-parameter models in drilling industry. It is found that the Bingham, Cross, and HBE rheology models have precisely matched the WBM measurements in the viscometer. A generalized Reynolds number was applied to determine the Darcy friction factor although the PL (power law model) and the HB (Herschel-Bulkley model) exhibited a nonrealistic negative shift from the laminar friction factor.

Shrouded wind turbine performance in yawed turbulent flow conditions

Wind turbines represent a growing energy source worldwide. In many cases, operating in turbulent and changing wind direction spots. In this work, we use a wind tunnel to analyze the effect of the turbulence in a wind turbine provided with a Wind Lens flow concentrator, under yaw conditions, for turbulence intensity values of 10% and 15%. Measurements are made of the power coefficient as a function of the Tip Speed Ratio using two types of Wind Lens, CiiB5 and CiiB10, at yaw angles from [Formula: see text] to [Formula: see text]. In general, for the turbine with Wind Lens, an increase of the yaw angle causes a reduction of the power coefficient. If the turbine operates with the CiiB10, the stronger the turbulence, the greater performance is obtained. In conclusion, for the case of turbulent flow and yaw = [Formula: see text] or less, the Wind Lens turbine offers better performance than without the flow concentrator.

Seismic quantification of river flow depth - from the flume to the field

<p>Seismic measurements are used to study various processes that shape the Alpine landscape, including rock falls, debris flows, bedload transport and turbulent water flow. Here, we focus on the seismic quantification of turbulent flow conditions which is particularly useful for the remote monitoring of channels that are inaccessible (e.g. subglacial conduits) and/or highly dynamic (e.g. actively braiding river reaches). We test a physically-based model (Gimbert et al., 2014) to quantify force spectra generated by turbulent flow in flume experiments performed by Lamb et al. (2017) and subsequently apply the model to estimate river flow depth from continuous seismic measurements in the field.</p><p>In the flume, we assess near-bed flow velocity spectra and resulting drag and lift force spectra experienced by particles (D=0.075-0.20 m) on the cobble bed for a wide range of channel gradients (S=0.004-0.3) and submergence levels (h/D<sub>50</sub>=1-9.6). These measurements are used to test our model, and to quantify wake (interaction) effects and fluid-dynamic admittance on force spectral amplitude. Based on the conservation of turbulent energy in the Kolmogorov inertial subrange, we predict lift and drag force spectra to within ±5 dB rel. N<sup>2</sup>/Hz (frequency ~10-25 Hz) of the measured values.</p><p>We apply the calibrated model to bank-side geophone measurements from an Alpine stream (Séveraisse River, France). Using locally-derived seismic parameters, riverbed particle-size distribution and bed roughness, we can invert for water depth over a range of flow conditions, including flows with bedload transport (bedload transport dominates the seismic signal at higher frequencies). This allows us to monitor changes in flow depth during the course of a high-magnitude flood (October 2019). During the falling limb, the inferred flow depths progressively deviate from independently made water level measurements, indicating local riverbed aggradation of approximately 0.5 m, which is in agreement with post-flood observations. Through insights in near-bed turbulent flow conditions and their seismic signature, we can study flow-bedload transport interactions and the effects of extreme flow events on river morphodynamics.</p><p><strong>References</strong></p><p>Gimbert, F., Tsai, V. C. & Lamb, M. P. (2014). A physical model for seismic noise generation by turbulent flow in rivers. Journal of Geophysical Research: Earth Surface, 119(10), 2209-2238. http://dx.doi.org/10.1002/2014JF003201</p><p>Lamb, M. P., Brun, F. & Fuller, B. M. (2017). Direct measurements of lift and drag on shallowly submerged cobbles in steep streams: Implications for flow resistance and sediment transport. Water Resources Research, 53(9), 7607-7629. https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1002/2017WR020883</p>

Sample preparation under turbulent flow with renewable sorbent

An open platform for sample preparation under turbulent flow conditions with stationary phase renewal and smart control.