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Scott, Ryan

Publications and source records attributed to Scott, Ryan.

10 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Graph network heterogeneity predicts interplant wake losses

Wind plants generate large-scale wakes, which can affect the performance of neighboring installations. Such wakes are challenging to estimate due to the inherent complexity in modeling wake interactions between large quantities of turbines at various distances. Weighted directed graph networks can inform complex models by linking turbine pairs into chains of upstream and downstream neighbors for a given wind direction. A novel interpretation of the graph network adjacency matrix is proposed where each element of the matrix represents the cumulative impact of upstream turbines on an individual. In this study, wake losses were estimated with an engineering wake model across a range of inflow conditions for nine parametric variations of a system containing two neighboring wind plants. The parametric nature of the study isolates turbine spacing within the plant, separation distance between plants, and wind direction as the main drivers of wake losses. Spatial heterogeneity is computed from the weighted average adjacency matrix of each plant arrangement. The proposed method is orders of magnitude faster than wake modeling and does not require detailed turbine information or atmospheric conditions. Furthermore, the weighted average adjacency matrix provides insight on the spatial organization of wake losses at various scales. Plant heterogeneity is correlated with wake losses within and among plants. Framing wind plant wake interaction in terms of graph network spatial heterogeneity provides an efficient approach for predicting wake losses within and among neighboring wind plants with applications to other complex systems where wake interactions are key factor.

17 WIND ENERGY↗
DOE OSTI2024

Wind plant wake losses: Disconnect between turbine actuation and control of plant wakes with engineering wake models

Wake losses from neighboring plants may become a major factor in wind plant design and control as additional plants are constructed in areas with high wind resource availability. Because plant wakes span a large range of physical scales, from turbine rotor diameter to tens of kilometers, it is unclear whether conventional wake models or turbine control strategies are effective at the plant scale. Wake steering and axial induction control are evaluated in the current work as means of reducing the impact of neighboring wind plants on power and levelized cost of electricity. FLOw Redirection and Induction in Steady State (FLORIS) simulations were performed with the Gauss–Curl Hybrid and TurbOPark wake models as well as two operation and maintenance models to investigate control setpoint sensitivity to wake representation and economic factors. Both wake models estimate losses across a range of atmospheric conditions, although the wake loss magnitude is dependent on the wake model. Annual energy production and levelized cost of electricity are driven by wind direction frequency, with frequently aligned plants experiencing the greatest losses. However, both wake steering and axial induction are unable to mitigate the impact of upstream plants. Wake steering is constrained by plant geometry, since wake displacement is much less than the plant wake width, while axial induction requires curtailing the majority of turbines in upstream plants. Individual turbine strategies are limited by their effective scale and model representation. New wake models that include plant-scale physics are needed to facilitate the design of effective plant wake control strategies.

Scott, Ryan (ORCID:0000000328107574)↗
DOE OSTI2023

Investigation of Farm-to-Farm Interactions and Blockage Effects from AWAKEN using Large-Scale Numerical Simulations

A large-scale numerical computation of five wind farms was performed as a part of the American Wake Experiment (AWAKEN). This high-fidelity computation used the ExaWind/AMR-Wind LES solver to simulate a 100km × 100km domain containing 541 turbines under unstable atmospheric conditions matching previous measurements. The turbines were represented by Joukowski and OpenFAST coupled actuator disk models. Results of this qualitative comparison illustrate the interactions with wind farms with large scale ABL structures in the flow, as well as the extent of downstream wake penetration in the flow and blockage effects around wind farms.

Cheung, Lawrence C.↗
DOE OSTI2023

AWAKEN Wind Plant Simulation Comparison

A series of numerical simulations of wind farms, using different model fidelities and for different atmospheric stability conditions, were performed as a part of the American WAKE ExperimeNt. The simulations included using FLORIS wake models, a number of microscale AMR-Wind and Nalu-Wind runs, as well as idealized and complex terrain WRF runs. The largest computations used the AMR-Wind LES solver to simulate a 100 km x 100 km domain containing 541 turbines under unstable atmospheric conditions matching previous measurements, while other LES computations focused on sections of the King Plains wind farm. Results of this qualitative comparison illustrate the interactions with wind farms with large-scale ABL structures in the flow, as well as the extent of downstream wake penetration in the flow and blockage effects around wind farms.

17 WIND ENERGY↗
DOE OSTI2023

A Three-Dimensional, Analytical Wind Turbine Wake Model: Flow Acceleration, Empirical Correlations, and Continuity

A new, three-dimensional, analytical, steady-state wake model is presented that includes local flow acceleration near the rotor, improving the wake description compared to existing models. Wake structures such as the momentum deficit and regions of accelerated flow are concisely described with compound and normal Gaussian functions. Large-eddy simulations (LES) are used as training data to develop the model using two in-line turbines under various inflow conditions parameterized by hub-height wind speed and turbulence intensity. Mass conservation is considered by fixing two components of the wake velocity model and optimizing the third to best satisfy continuity; after which, the model performs comparably if not better than existing work with regards to both relative error and mass consistency. The final model demonstrates a high degree of flexibility, making use of empirical correlations to scale across different inflow conditions. The inclusion of these effects is capable of revealing unused opportunities for enhanced power generation by aligning wake trajectories with these regions of accelerated flow.

modeling↗
DOE OSTI2023

Evolution of eddy viscosity in the wake of a wind turbine

The eddy viscosity hypothesis is a popular method in wind turbine wake modeling for estimating turbulent Reynolds stresses. We document the downstream evolution of eddy viscosity in the wake of a wind turbine from experimental and large-eddy-simulation data. Wake eddy viscosity is isolated from its surroundings by subtracting the inflow profile, and the driving forces are identified in each wake region. Eddy viscosity varies in response to changes in turbine geometry and nacelle misalignment with larger turbines generating stronger velocity gradients and shear stresses. We propose a model for eddy viscosity based on a Rayleigh distribution. Model parameters are obtained from scaling the eddy viscosity hypothesis and demonstrate satisfactory agreement with the reference data. The model is implemented in the curled wake formulation in the FLOw Redirection and Induction in Steady State (FLORIS) framework and assessed through comparisons with the previous formulation. Our approach produced more accurate flow field estimates with lower total error for the majority of cases.

17 WIND ENERGY↗
NASA NTRS2017

Characterizing the Effects of Chronic 2G Centrifugation on the Rat Skeletal System

During weightlessness, the skeletal system of astronauts is negatively affected by decreased calcium absorption and bone mass loss. Therefore, it is necessary to counteract these changes for long-term skeletal health during space flights. Our long-term plan is to assess artificial gravity (AG) as a possible solution to mitigate these changes. In this study, we aim to determine the skeletal acclimation to chronic centrifugation. We hypothesize that a 2G hypergravity environment causes an anabolic response in growing male rats. Specifically, we predict chronic 2G to increase tissue mineral density, bone volume fraction of the cancellous tissue and to increase overall bone strength. Systemically, we predict that bone formation markers (i.e., osteocalcin) are elevated and resorption markers (i.e., tartrate resistant acid phosphatase) are decreased or unchanged from controls. The experiment has three groups, each with an n8: chronic 2g, cage control (housed on the centrifuge, but not spun), and a vivarium control (normal rat caging). Pre-pubescent, male Long-Evans rats were used to assess our hypothesis. This group was subject to 90 days of 2G via centrifugation performed at the Chronic Acceleration Research Unit (CARU) at University of California Davis. After 90 days, animals were euthanized and tissues collected. Blood was drawn via cardiac puncture and the right leg collected for structural (via microcomputed tomography) and strength quantification. Understanding how counteract these skeletal changes will have major impacts for both the space-faring astronauts and the people living on Earth.

rat↗
NASA NTRS2017

Estrous Cyclicity of Mice During Simulated Weightlessness

Hindlimb unloading (HU) is a rodent model system used to simulate weightlessness experienced in space. However, some effects of this approach on rodent physiology are under-studied, specifically the effects on ovarian estrogen production which drives the estrous cycle. To resolve this deficiency, we conducted a ground-based validation study using the HU model, while monitoring estrous cycles in 16-weeks-old female C57BL6 mice. Animals were exposed to HU for 12 days following a 3 day HU cage acclimation period, and estrous cycling was analyzed in HU animals (n22), normally loaded HU Cage Pair-Fed controls (CPF; n22), and Vivarium controls fed ad libitum (VIV; n10). Pair feeding was used to control for potential nutritional deficits on ovarian function. Vaginal cells were sampled daily in all mice via saline lavage. Cells were dried and stained with crystal violet, and the smears evaluated using established vaginal cytology techniques by two individuals blinded to the animal treatment group. Estrous cyclicity was disrupted in nearly all HU and CPF mice, while those maintained in VIV had an average normal cycle length of 4.8 0.5 days, with all stages in the cycle visibly observed. CPF and HU animals arrested in the diestrous phase, which precedes the pre-ovulatory estrogen surge. Additionally, infection-like symptoms characterized by vaginal discharge and swelling arose in several HU animals, which we suspect was due to an inability of these mice to properly groom themselves, andor due to the change in the gravity vector relative to the vaginal opening, which prevented drainage of the lavage solution. Pair-feeding resulted in similar weight gains of HU and CPF (1.5 vs 3.0, respectively). The current results indicate that pair-feeding controlled weight gain and that the HU cage alone influenced estrous cyclicity. Thus, longer acclimation needs to be tested to determine if and when normal estrous cycling resumes in non-loaded mice in HU cages prior to HU testing. Future studies might also examine whether modifications to the vaginal lavage procedure might prevent the onset of the infection-like symptoms, and allow estrous cyclicity to be measured in this model system.

fertilit↗