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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Validated Reduced Computational Methods for Realistic RDC Injection Modeling

This paper outlines a simplified computational method without chemistry for single and multi-injector performance for rotating detonation combustion (RDC) environment as well as relevant performance metrics. For non-reactive cases, an unsteady pressure profile from a Method of Characteristics (MOC) simulation was used to simulate an RDC combustion wave travelling around the annulus. In reactive cases, a pre-mixed stoichiometric mixture of hydrogen and air is injected into a 2D unwrapped combustion chamber with a specified injector area. The performance is evaluated based on several performance metrics including unsteady discharge coefficient, average mass flux coming into the combustor, and percentage time obstructed. Finally, the computational method was validated through an experimental RDC test setup with a single element injector in a hydrogen-air detonation driver environment.

Propulsion↗
DOE OSTI2022

Wave energy converter buoy with variable geometry

A nonlinear control design technique capitalizes on a wave energy converter comprising a shaped buoy having a variable geometry wave energy. For example, the shaped buoy can have an hourglass (HG) geometry having a variable cone or steepness angle. The HG buoy is assumed to operate in the heave motion of the wave. The unique interaction between the HG buoy and the wave creates a nonlinear cubic storage effect that produces actual energy storage or reactive power during operation. A multi-frequency Bretschneider spectrum wave excitation input was simulated for the HG design both with constant and varying steepness angle profiles which demonstrated further increased power generation with changing sea states for the variable design.

Wilson, David G.↗
DOE OSTI2024

A Comparison of Battery Charge Controller Technologies for Wave Energy Converters: Preprint

Wave energy is a uniquely challenging field for electrical system designers. High peak and low average power potential with a constantly varying energy input is difficult to harness and control through conventional means. To power the blue economy, low-powered wave energy converters (WECs) need batteries for energy storage. Safely and effectively charging batteries from waves requires a charge controller to properly monitor and control voltage and current going to the battery. Currently, off-the-shelf charge controllers exist for other renewable generation such as wind, hydro, and solar. Two topologies were validated: a buck converter and a pulse width modulation (PWM) charge controller. Using an in-lab dry testbed, wave energy power inputs were simulated to properly validate the effectiveness of existing charge controller technologies, identifying the shortcomings and improvements needed to effectively harness wave energy.

battery storage↗
DOE OSTI2024

HERO WEC V1.0 - WEC-Sim Model (July 2024)

**This submission supersedes submission MHKDR-483** This submission file contains the files that are needed to simulate NREL's HERO WEC (hydraulic and electric reverse osmosis wave energy converter). This requires the user to have already installed WEC-Sim. In addition to the standard toolboxes that are required to run WEC-Sim the user will also need the Simscape Fluids and Simscape Driveline packages. The zip file (HERO_V1_WECSim_2024.zip) contains the following: - HERO_HPTO_2024.slx: Simulink-based WEC Sim model of the first gen (V1.0) Hydraulic PTO (power take-off) that was designed for the HERO WEC. This model has been updated since submission #483 based on in-laboratory experimental results. - wecSimInputFile.m: Input file needed to run the model - userDefinedFunctionsMCR.m: MCR (multi condition run) script that is needed if a use wants to simulate multiple wave conditions. - geometry (folder): Includes the geometry file that is needed for visualization - hydroData (folder): Includes the required WAMIT data to run WEC-Sim -HydVisualization.mlx: Visualization script to plot simulation results (not needed to run)

16 TIDAL AND WAVE POWER↗
DOE OSTI2020

Influence of Time and Frequency Domain Wave Forcing on the Power Estimation of a Wave Energy Converter Array

Industry-specific tools for analyzing and optimizing the design of wave energy converters (WECs) and associated power systems are essential to advancing marine renewable energy. This study aims to quantify the influence of phase information on the device power output of a virtual WEC array. We run the phase-resolving wave model FUNWAVE-TVD (Total Variation Diminishing) to generate directional waves at the PacWave South site offshore from Newport, Oregon, where future WECs are expected to be installed for testing. The two broad cases presented correspond to mean wave climates during warm months (March–August) and cold months (September–February). FUNWAVE-TVD time series of sea-surface elevation are then used in WEC-Sim, a time domain numerical model, to simulate the hydrodynamic response of each device in the array and estimate their power output. For comparison, WEC-Sim is also run with wave energy spectra calculated from the FUNWAVE-TVD simulations, which do not retain phase information, and with wave spectra computed using the phase-averaged model Simulating WAves Nearshore (SWAN). The use of spectral data in WEC-Sim requires a conversion from frequency to time domain by means of random superposition of wave components, which are not necessarily consistent because of the linear assumption implicit in this method. Thus, power response is characterized by multiple realizations of the wave climates.

13 HYDRO ENERGY↗
DOE OSTI2025

Propagation of ion cyclotron emission in the DIII-D tokamak

Experiments in L- and H-mode plasmas performed on the DIII-D tokamak explored ion cyclotron emission (ICE) propagation via the recently upgraded ICE diagnostic. The distance between the plasma and the outer wall was scanned to alter the evanescent region, which was seen to impact the detection of runaway electron-driven whistler modes in a comparable frequency range to typical ICE harmonics (f≳10fci) [Heidbrink et al., Plasma Phys. Controlled Fusion 61, 014007 (2018)]. In L-mode plasmas, core ICE did not exhibit clear trends as the plasma-wall distance was altered. Instead, inadvertent changes to the fast ion density correlated with different ICE fine structures; the most spectral bands (spaced ∼150–200 kHz apart) were observed at the highest fast ion density, and a just single band when nfast decreased by ∼ 40%. The full-wave Petra-M code simulated core ICE propagation through the plasma and to ICE probes, agreeing with experimental findings that these are likely compressional fast waves, which propagate to probe locations with no dependence on plasma-wall gap. Edge ICE in H-mode plasmas was similarly unaffected by plasma-wall distance. Unlike in core ICE cases, there were negligible changes to the edge fast ion distribution and edge bulk plasma profiles. However, changes in ELM frequency seemed most closely tied to ICE behavior. Ultimately, core and edge ICE did not exhibit clear dependencies on the plasma-wall distance, and ICE harmonics were observed with even the largest plasma-wall gaps. This independence bodes well for similar diagnostics in future tokamaks, which might be placed further from high radiation areas without adversely impacting measurement capabilities.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

MBARI-WEC September and October 2022 Field Data

This data is needed to simulate a model of the MBARI-WEC (Monterey Bay Aquarium Research Institute, Wave Energy Converter device) in a simulation environment (e.g. Gazebo) for 56 observation dates in the time between September and October 2022, and to compare the simulation outputs to the corresponding field data of the physical MBARI-WEC. There were 50 observations chosen in Sept and 6 observations in Oct. To help understand terms below, a summary of the system can be found at the github link in the downloads section below. The Gazebo MBARI-WEC model is also provided, should users wish to simulate using this platform. There are 4 *mat files included. ................................................................................................................................................................................................................................... Spectrum and Simulation Inputs: September2022_spectrum_siminputs.mat and October2022_spectrum_siminputs.mat has data needed for simulation inputs in table format. These include the ocean spectrum for an observation and operating parameters of the MBARI-WEC during that observation. They are organized as rows representing an observation and columns representing data. For example, for the September *mat there are 50 rows. The first 7 columns are Datetime, sig_waveheight, peak_period, mean_period, heaveconedoor_status, pistonpos_mean, and scale_factor: - Datetime is the date and time the observation occurred in PST - sig_waveheight is the significant wave height of the ocean spectrum during that observation in meters - peak_period is the peak period of the ocean spectrum during that observation in seconds - mean_period is the mean period of the ocean spectrum during that observation in seconds - heaveconedoor_status is the status of the heave cone doors where 0 represents the doors are open and 1 represents they are closed - pistonpos_mean is the mean position of the PTO ram (piston) in meters - scale_factor is an additional factor of 0.5 --1.4 applied to a default damping relationship The next columns are data needed to represent the ocean spectrum. First are the frequencies [Hz] labeled as "f0-f38", then the variance density [m2/Hz] labeled as "vardens0-vardens38". October2022_spectrum_siminputs.mat follows as a similar format as above, but includes a larger amount of ocean spectrum frequencies and variance density elements. ................................................................................................................................................................................................................................... Field data: The field data is found in MBARIWEC_septdata.mat and MBARIWEC_octdata.mat for the observations of September and October, respectively. These contain data in a struct format. The struct contains the following fields for each observation: PC_BattCurr, PC_LoadCurr, PC_RPM, PC_Voltage, SC_Range, SC_Velocity, DateTime, where: - PC_BattCurr is the current flowing to or from the onboard batteries in Amps - PC_LoadCurr is the current flowing to the load dump in Amps - PC_RPM is the electric/hydraulic motor shaft speed (directly coupled) in RPM - PC_Voltage is the bus voltage at the power converter in Volts - SC_Range is the PTO ram (piston) position in meters where 0 is fully retracted and 2.03 is fully extended - SC_Velocity is the PTO ram (piston) velocity in meters/sec - DateTime is the date and time of the sampled field data in each observation in PST - Electric Power is equal to: PC_Voltage*(PC_BattCurr + PC_LoadCurr) in Watts For example, upon loading MBARIWEC_octdata.mat, the aforementioned fields would be loaded, each with {6x1} cells for the 6 observations chosen in October. Within the first cell of e.g. SC_Range would be sampled data representing the field data of the MBARIWEC PTO piston position for say, one hour, of the first October observation. The corresponding field DateTime would...

16 TIDAL AND WAVE POWER↗
NASA NTRS1993

Two-dimensional CFD modeling of wave rotor flow dynamics

A two-dimensional Navier-Stokes solver developed for detailed study of wave rotor flow dynamics is described. The CFD model is helping characterize important loss mechanisms within the wave rotor. The wave rotor stationary ports and the moving rotor passages are resolved on multiple computational grid blocks. The finite-volume form of the thin-layer Navier-Stokes equations with laminar viscosity are integrated in time using a four-stage Runge-Kutta scheme. The Roe approximate Riemann solution scheme or the computationally less expensive Advection Upstream Splitting Method (AUSM) flux-splitting scheme are used to effect upwind-differencing of the inviscid flux terms, using cell interface primitive variables set by MUSCL-type interpolation. The diffusion terms are central-differenced. The solver is validated using a steady shock/laminar boundary layer interaction problem and an unsteady, inviscid wave rotor passage gradual opening problem. A model inlet port/passage charging problem is simulated and key features of the unsteady wave rotor flow field are identified. Lastly, the medium pressure inlet port and high pressure outlet port portion of the NASA Lewis Research Center experimental divider cycle is simulated and computed results are compared with experimental measurements. The model accurately predicts the wave timing within the rotor passage and the distribution of flow variables in the stationary inlet port region.

Welch, Gerard E.↗
NASA NTRS1994

Two-dimensional CFD modeling of wave rotor flow dynamics

A two-dimensional Navier-Stokes solver developed for detailed study of wave rotor flow dynamics is described. The CFD model is helping characterize important loss mechanisms within the wave rotor. The wave rotor stationary ports and the moving rotor passages are resolved on multiple computational grid blocks. The finite-volume form of the thin-layer Navier-Stokes equations with laminar viscosity are integrated in time using a four-stage Runge-Kutta scheme. Roe's approximate Riemann solution scheme or the computationally less expensive advection upstream splitting method (AUSM) flux-splitting scheme is used to effect upwind-differencing of the inviscid flux terms, using cell interface primitive variables set by MUSCL-type interpolation. The diffusion terms are central-differenced. The solver is validated using a steady shock/laminar boundary layer interaction problem and an unsteady, inviscid wave rotor passage gradual opening problem. A model inlet port/passage charging problem is simulated and key features of the unsteady wave rotor flow field are identified. Lastly, the medium pressure inlet port and high pressure outlet port portion of the NASA Lewis Research Center experimental divider cycle is simulated and computed results are compared with experimental measurements. The model accurately predicts the wave timing within the rotor passages and the distribution of flow variables in the stationary inlet port region.

Welch, Gerard E.↗
NASA NTRS2005

Formation of a Tropopause Cirrus Layer Observed over Florida during CRYSTAL-FACE

On July 13, 2002 a widespread, subvisible tropopause cirrus layer occurred over the Florida region. This cloud was observed in great detail with the NASA Cirrus Regional Study of Tropical Anvils and Cirrus Layers-Florida Area Cirrus Experiment (CRYSTAL-FACE) instrumentation, including in situ measurements with the WB-57 aircraft. In this paper, we use the 13 July cloud as a case study to evaluate the physical processes controlling the formation and evolution of tropopause cirrus layers. Microphysics measurements indicate that ice crystal diameters in the cloud layer ranged from about 7 to 50 microns, and the peak number mode was about 10-25 microns. In situ water vapor and temperature measurements in the cloud indicated supersaturation with respect to ice throughout, with ice saturation ratios as large as 1.8. Even when the ice surface area density was as high as about 500 sq microns/cu cm, ice supersaturations of 20-30% were observed. Trajectory analysis shows that the air sampled near the tropopause on this day generally came from the north and cooled considerably during the previous few days. Examination of infrared satellite imagery along air parcel back trajectories from the WB-57 flight track indicates that the tropopause cloud layer formation was, in general, not simply left over ice from recently generated anvil cirrus. Simulations of cloud formation using time-height curtains of temperature along the trajectory paths show that the cloud could have formed in situ near the tropopause as the air was advected into the south Florida region and cooled to unusually low temperatures. If we assume a high threshold for ice nucleation via homogeneous freezing of aqueous sulfate aerosols, the model reproduces the observed cloud structure, ice crystal size distributions, and ice supersaturation statistics. Inclusion of observed gravity wave temperature perturbations in the simulations is essential to reproduce the observed cloud properties. Without waves, crystal number densities are too low, crystal sizes are too large, and the crystals fall out too fast, leaving very little cloud persisting at the end of the simulations. In the cloud simulations, coincidence of high supersaturations and high surface areas can be produced by either recent nucleation or sedimentation of crystals into supersaturated layers. The agreement between model results and observed supersaturations is improved somewhat if we assume that the steady state relative humidity within cirrus at T<200 K is enhanced by about 30%. The WB-57 measurements and the model results suggest that the cloud layer irreversibly dehydrated air near the tropopause.

Jensen, Eric↗
DOE OSTI2020

Implementation and Verification of Cable Bending Stiffness in MoorDyn: Preprint

Cable bending stiffness capabilities have been added to MoorDyn to enable modeling of dynamic power cables. The relatively large motions experienced by floating wind turbines and wave energy converters pose a challenge for power cables, whose internal components provide significant bending resistance and are sensitive to deformation. The behavior and associated design considerations of power cables in these highly dynamic applications make coupled analysis relevant for design. MoorDyn is a lumped-mass mooring dynamics model that is used for floating wind energy simulation (often coupled with OpenFAST) and floating wave energy converter simulation (often coupled with WEC-Sim). Its existing line elasticity formulation considers axial stiffness only. To properly capture the dynamics of power cables, a cable bending stiffness model has been added that approximates cable curvature based on the difference in tangent vectors of adjacent line elements. The resulting bending moment is realized by applying forces on adjacent nodes, leaving the underlying lumped-mass formulation unchanged. The bending stiffness implementation is verified in static conditions against analytical solutions and then in a dynamic power cable scenario in comparison with OrcaFlex. The dynamic scenario uses prescribed motions and includes wave loadings on the cable. Results indicate correct implementation of bending stiffness and show close agreement with OrcaFlex.

50 EE - Wind and Water Power Program - Water (EE-4↗
DOE OSTI2021

Machine learning the dynamics of quantum kicked rotor

Highlights: • Quantum kicked rotor. • Quantum phase transition. • Machine learning. • LSTM network. • Convolutional neural network. Using the multilayer convolutional neural network (CNN), we can detect the quantum phases in random electron systems, and phase diagrams of two and higher dimensional Anderson transitions and quantum percolations as well as disordered topological systems have been obtained. Here, instead of using CNN to analyze the wave functions, we analyze the dynamics of wave packets via long short-term memory network (LSTM). We adopt the quasi-periodic quantum kicked rotors, which simulate the three and four dimensional Anderson transitions. By supervised training, we let LSTM extract the features of the time series of wave packet displacements in localized and delocalized phases. We then simulate the wave packets in unknown phases and let LSTM classify the time series to localized and delocalized phases. We compare the phase diagrams obtained by LSTM and those obtained by CNN.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS2008

Precipitating Snow Retrievals from Combined Airborne Cloud Radar and Millimeter-Wave Radiometer Observations

An algorithm for retrieving snow over oceans from combined cloud radar and millimeter-wave radiometer observations is developed. The algorithm involves the use of physical models to simulate cloud radar and millimeter-wave radiometer observations from basic atmospheric variables such as hydrometeor content, temperature, and relative humidity profiles and is based on an optimal estimation technique to retrieve these variables from actual observations. A high-resolution simulation of a lake-effect snowstorm by a cloud-resolving model is used to test the algorithm. That is, synthetic observations are generated from the output of the cloud numerical model, and the retrieval algorithm is applied to the synthetic data. The algorithm performance is assessed by comparing the retrievals with the reference variables used in synthesizing the observations. The synthetic observation experiment indicates good performance of the retrieval algorithm. The algorithm is also applied to real observations from the Wakasa Bay field experiment that took place over the Sea of Japan in January and February 2003. The application of the retrieval algorithm to data from the field experiment yields snow estimates that are consistent with both the cloud radar and radiometer observations.

Grecu, Mircea↗