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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Generating Emissions Inventory for Carbon Capture and Storage Analysis for Carbon-Intensive Industrial Sectors

Decarbonizing the industrial sector is critical to achieve carbon dioxide (CO2) emissions reductions goals of the Biden Administration. Currently available decarbonization options include electrification, fuel switching to zero carbon fuels like green hydrogen (H2) and carbon capture and storage (CCS). Application of post-combustion carbon capture (PCCC) technology in the power sector, as well as research at the U.S. Department of Energy's Fossil Energy and Carbon Management (FECM) Office has shown that its application in the industrial sector could have co-benefits in the form of emissions reductions of non-CO2 regulated pollutants. For example, solvent based PCCC systems require pre-conditioning of flue gas to remove sulfur and particulate matter (PM) upstream of the CO2 absorber. However, there is a lack of understanding about the type of non-CO2 pollutants which can be captured and the amount of reduction possible. PCCC application differs across industrial sectors as it depends on the availability of decarbonization options, characteristics of industrial processes and the amount and composition of pollutant flows. Certain facilities can also have multiple effluent flows with or without a CO2 stream. As such, understanding industrial processes and their effluent flows in detail is required to quantify the co-benefits opportunities presented by PCCC. Considering this requirement, the goal of this analysis is to develop a high-resolution inventory of effluent flows from facilities of 8 industrial sectors in the U.S. These industrial sectors - ethanol, ammonia, cement, steel, natural gas processing, hydrogen, petroleum refining and wood and pulp products - have carbon-intensive effluent flows, and thus are prime candidates for PCCC applications. In this study, we map the composition of pollutant flow from flue stacks across the identified facilities. Using data available in three Environmental Protection Agency (EPA) databases - the Green House Gas Reporting Program (GHGRP), the National Emissions Inventory (NEI) and the Toxic Release Inventory (TRI), we create a combined inventory which lists the type, amount, and concentration of pollutant flows. Using total weight of the pollutant flow back calculated from observed data for CO2 concentrations in flue gas for individual sectors, we calculate the concentration of each pollutant in the flue gas stream. Thus, the resultant emissions inventory includes the following details for each facility in the sector: facility-level and if possible, process-level pollutant flows, concentrations of pollutants in the flue gas, and geographical coordinates of the facilities. A detailed statistical analysis and summary allows us to search for erroneous data and remove them from the final inventory. The generation of the inventory is achieved using a python-based framework which can recreate this inventory for other industrial sectors as well as using newer releases of emission inventories from EPA. The statistical analysis performed on the inventory is also calibrated and automated to identify outliers efficiently.

air pollutants↗
DOE OSTI2020

Predicting Water Cycle Characteristics from Percolation Theory and Observational Data

The fate of water and water-soluble toxic wastes in the subsurface is of high importance for many scientific and practical applications. Although solute transport is proportional to water flow rates, theoretical and experimental studies show that heavy-tailed (power-law) solute transport distribution can cause chemical transport retardation, prolonging clean-up time-scales greatly. However, no consensus exists as to the physical basis of such transport laws. In percolation theory, the scaling behavior of such transport rarely relates to specific medium characteristics, but strongly to the dimensionality of the connectivity of the flow paths (for example, two- or three-dimensional, as in fractured-porous media or heterogeneous sediments), as well as to the saturation characteristics (i.e., wetting, drying, and entrapped air). In accordance with the proposed relevance of percolation models of solute transport to environmental clean-up, these predictions also prove relevant to transport-limited chemical weathering and soil formation, where the heavy-tailed distributions slow chemical weathering over time. The predictions of percolation theory have been tested in laboratory and field experiments on reactive solute transport, chemical weathering, and soil formation and found accurate. Recently, this theoretical framework has also been applied to the water partitioning at the Earth’s surface between evapotranspiration, ET, and run-off, Q, known as the water balance. A well-known phenomenological model by Budyko addressed the relationship between the ratio of the actual evapotranspiration (ET) and precipitation, ET/P, versus the aridity index, ET 0 /P, with P being the precipitation and ET 0 being the potential evapotranspiration. Existing work was able to predict the global fractions of P represented by Q and ET through an optimization of plant productivity, in which downward water fluxes affect soil depth, and upward fluxes plant growth. In the present work, based likewise on the concepts of percolation theory, we extend Budyko’s model, and address the partitioning of run-off Q into its surface and subsurface components, as well as the contribution of interception to ET. Using various published data sources on the magnitudes of interception and information regarding the partitioning of Q, we address the variability in ET resulting from these processes. The global success of this prediction demonstrated here provides additional support for the universal applicability of percolation theory for solute transport as well as guidance in predicting the component of subsurface run-off, important for predicting natural flow rates through contaminated aquifers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Stereoscopic high-speed microscopy to understand transient internal flow processes in high-pressure nozzles

The flow and cavitation behavior inside fuel injectors is known to affect spray development, mixing and combustion characteristics. We discuss that while diesel fuel injectors with converging and hydro-eroded holes are generally known to limit cavitation and feature higher discharge coefficients during the steady period of injection, less is known about the flow during transient periods corresponding to needle opening and closing. Multiple injection strategies involve short injections, multiplying these aspects and giving them a growing importance as part of the fuel delivery process. In this study, single-hole transparent nozzles were manufactured with the same hole inlet radius and diameter as the Engine Combustion Network Spray D nozzle, mounted to a modified version of a common-rail Spray A injector body and needle. Needle opening and closing periods were visualized with stereoscopic high-speed microscopy at injection pressures relevant to modern diesel engines. Time-resolved sac pressure was extracted via elastic deformation analysis of the transparent nozzles. Sources of cavitation were observed and tracked, enabling the identification of a gas exchange process after the end of injection with ingestion of chamber gas into the sac and orifice. We observed that the gas exchange contributed widely to disrupting the start of injection and outlet flow during the subsequent injection event.

42 ENGINEERING↗
DOE OSTI2023

Molecular-gas-dynamics simulations of turbulent Couette flow over a mean-free-path-scale permeable substrate

Here we report flow statistics and visualizations from molecular-gas-dynamics simulations using the direct simulation Monte Carlo (DSMC) method for turbulent Couette flow in a minimal domain where the lower wall is replaced by an idealized permeable fibrous substrate representative of thermal-protection-system materials for which the Knudsen number is O(10 -1 ). Comparisons are made with smooth-wall DSMC simulations and smooth-wall direct numerical simulations (DNS) of the Navier-Stokes equations for the same conditions. Roughness, permeability, and noncontinuum effects are assessed. In the range of Reynolds numbers considered herein, the scalings of the skin friction on the permeable substrate and of the mean flow within the substrate suggest that they are dominated by viscous effects. While the regenerative cycle characteristic of smooth-wall turbulence remains intact for all cases considered, we observe that the near-wall velocity fluctuations are modulated by the permeable substrate with a wavelength equal to the pore spacing. Additionally, the flow within the substrate shows significant rarefaction effects, resulting in an apparent permeability that is 13% larger than the intrinsic permeability. In contrast, the smooth-wall DSMC and DNS simulations exhibit remarkably good agreement for the statistics examined, despite the Knudsen number based on the viscous length scale being as large as O(10 -1 ). This latter result is at variance with classical estimates for the breakdown of the continuum assumption and calls for further investigations into the interaction of noncontinuum effects and turbulence.

42 ENGINEERING↗
DOE OSTI2024

Discrete element modeling of irregular-shaped soft pine particle flow in an FT4 powder rheometer

Pine residues are a commonly used biomass feedstock that consists of different anatomical fractions, each with distinct particle characteristics. Here, in this work, an experiment-informed discrete element model is developed to investigate the flowability of pine residues in an FT4 rheometer. Multi-sphere particles with distinct particle attributes are created to model each anatomical fraction type. A systematic analysis of specimens with varying particle characteristics (e.g., anatomical fraction type, particle shape, and size) is conducted to elucidate the relationship between particle attributes and flowability. The results show that stems recorded the highest axial force and torque and, correspondingly, the highest flow energy, which is attributed to their high stiffness and interlocking effect. Increasing their percentage in the mixture increases the flow energy while increasing needles tends to decrease flow energy. Knowledge gained in this study on the flow of anatomical fractions is important for the efficient and robust processing of pine residues.

09 BIOMASS FUELS↗
DOE OSTI2022

Model study of the energy dependence of the correlation between anisotropic flow and the mean transverse momentum in Au + Au collisions

A hybrid model that employs the hadron-string transport model UrQMD and the (3+1)-dimensional relativistic viscous hydrodynamic code vHLLE, is used to investigate the beam energy dependence of the correlation coefficient ρ(v$^{2}_{2}$,[p T ]) between the average transverse momentum [p T ] of hadrons emitted in an event and the square of the anisotropic flow coefficient v$^{2}_{2}$. For Au+Au collisions, the model predicts characteristic patterns for the energy and event-shape dependence of the variances for [p T ] and v$^{2}_{n}$ [Var([p T ] and Var(v$^{2}_{2}$)], and the covariance of v$^{2}_{n}$ and [p T ][cov(v$^{2}_{2}$,[p T ])], consistent with the attenuation effects of the specific shear viscosity η/s. Here in contrast, ρ(v$^{2}_{2}$,[p T ]) is predicted to be insensitive to the beam energy but sensitive to the initial-state geometry of the collisions. These observations suggest that a precise set of measurements for Var([p T ]), Var(v$^{2}_{2}$), cov(v$^{2}_{2}$,[p T ]) and ρ(v$^{2}_{2}$,[p T ]) as a function of beam energy and event shape, could serve to constrain better the eccentricities and their fluctuations over the entire span of beam energies, and consequently aid precision extraction of the temperature and baryon chemical-potential dependence of η/s from the wealth of Au+Au data obtained in the RHIC beam energy scan.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Emissions and Flame Structure Assessment of Aeroengine Micromixing Injectors for Lean Direct Injection of Hydrogen and Hydrogen/Natural Gas Blends

Abstract The present study focuses on whether adapting low emissions liquid fuel injection concepts can be applied to gaseous mixtures. The goal is to develop an injector with specific geometric characteristics that will achieve the lowest emissions. This is conducted by evaluating emissions and flame diagnostics on a set of test hardware that has been developed for combustion of pure hydrogen and hydrogen/methane mixtures. The current test hardware adapts lean direct injection concepts from aeroengine injectors to a ground-based engine based on target flows associated with a Solar Turbines Industrial Engine gas turbine. A statistical test plan was developed to assess these geometric characteristics using a three level Box Behnken design. The test plan investigates the effect of injector flow splits, air swirl, fuel swirl, pressure drop, preheat temperature, fuel composition, and the adiabatic flame temperature on the flame structure and emissions performance. A total of 16 injectors were considered for a total of 688 test points for emission and imaging data. Emissions data were reported on a mass basis in ng/J and chemical reactor network analysis were conducted to further interpret emissions behavior. Images were also captured to analyze the flame structure features of interest including reaction volume, flame length, flame spread, and flame width. With these results, a predictive model for emissions was made to conclude the most optimal injector configuration is to have the highest level of air split (more volume of air through the injector plate versus the injector) and air swirl angle for both methane and hydrogen gas mixtures. The predictive emissions level for all of these cases were below 10 ng/J.

08 HYDROGEN↗
DOE OSTI2022

Dynamics and bifurcations of laminar annular swirling and non-swirling jets

This paper presents bifurcation analyses characterising the nonlinear dynamics of fully developed laminar annular jets with respect to the centrebody diameter ${ {d}}$ , Reynolds number ${ {Re}}$ , and swirl ratio ${ {S}}$ . Similar flows appear in numerous applications and feature a vibrant range of topological and dynamical characteristics associated with phenomena including shear layer separation and vortex breakdown. Our results begin by describing the non-monotonic evolution of the axisymmetric jet's steady topology under varying ${ {S}}$ . In accord with earlier reports, the jet progresses through a sequence of wake, breakdown and wall jet regimes in a qualitatively similar manner across a wide span of ${ {d}}$ and ${ {Re}}$ values. In the wake regime, the non-swirling jet bifurcates to a plane-symmetric, but not axisymmetric, steady flow pattern beyond a ${ {d}}$ -dependent critical ${ {Re}}$ value. With further increase in ${ {Re}}$ , the steady non-swirling jet destabilises subsequently via multiple distinct Hopf bifurcations. Introducing ${ {S}}>0$ to the jet also induces unsteadiness by twisting the singly azimuthally periodic ( $|m|=1$ ) asymmetric wake structure and causing it to precess periodically in time about the central axis. Intermediate swirl stabilises this unsteady dynamics and restores the jet's axisymmetry. This stabilising effect is then reversed in the breakdown regime at higher ${ {S}}$ , where a variety of different $|m|=1$ and $|m|=2$ instabilities bifurcate from the steady flow as ${ {S}}$ is increased. Several instances of hysteresis and subcritical behaviour are reported and discussed, including one that manifests precessing vortex core oscillations.

Douglas, Christopher M. (ORCID:0000000259683315)↗
DOE OSTI2022

Optimal control to handle variations in moisture content and reactor in-feed rate

The variations in feedstock characteristics, such as moisture and particle size distribution, lead to an inconsistent flow of feedstock from the biomass pre-processing system to the reactor in-feed system. These inconsistencies result in low on-stream times at the reactor in-feed equipment. This research develops an optimal process control method for a biomass pre-processing system comprised of milling and densification operations to provide the consistent flow of feedstock to a reactor's throat. This method uses a mixed-integer optimization model to identify optimal bale sequencing, equipment in-feed rate, and buffer location and size in the biomass pre-processing system. This method, referred to as the hybrid process control (HPC), aims to maximize throughput over time. We compare HPC with a baseline feed forward process control. Our case study based on switchgrass finds that HPC reduces the variation of a reactor's feeding rate by up to 100% without increasing the operating cost of the biomass pre-processing system for biomass with moisture ranging from 10 to 25%. Additionally, HPC reduces the cost of processing biomass by 0.36%–2.22%, and reduces processing time by 0.35%-2.24%. Furthermore, a biorefinery can adapt HPC to achieve its design capacity.

09 BIOMASS FUELS↗
DOE OSTI2020

Impact of boundary layer simulation on predicting radioactive pollutant dispersion: a case study for HANARO Research Reactor using the WRF-MMIF-CALPUFF modeling system

Wind plays an important role in cases of unexpected radioactive pollutant dispersion, deciding distribution and concentration of the leaked substance. The accurate prediction of wind has been challenging in numerical weather prediction models, especially near the surface because of the complex interaction between turbulent flow and topographic effect. As such, in this study, we investigated the characteristics of atmospheric dispersion of radioactive material (i.e. 137 Cs) according to the simulated boundary layer around the HANARO research nuclear reactor in Korea using the Weather Research and Forecasting (WRF)-Mesoscale Model Interface (MMIF)-California Puff (CALPUFF) model system. We examined the impacts of orographic drag on wind field, stability calculation methods, and planetary boundary layer parameterizations on the dispersion of radioactive material under a radioactive leaking scenario. We found that inclusion of the orographic drag effect in the WRF model improved the wind prediction most significantly over the complex terrain area, leading the model system to estimate the radioactive concentration near the reactor more conservatively. We also emphasized the importance of the stability calculation method and employing the skillful boundary layer parameterization to ensure more accurate low atmospheric conditions, in order to simulate more feasible spatial distribution of the radioactive dispersion in leaking scenarios.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

USAID Grid-Scale Energy Storage Technologies Primer

This work provides an overview and compares key operating characteristics of select energy storage technologies. This work explores how these storage technologies may be used to improve the flexibility and reliability of power systems given their technical characteristics. The report covers various electrochemical (lithium-ion, lead-acid, flow, sodium-sulfur), chemical (hydrogen), mechanical (pumped hydro storage, compressed air energy storage, flywheels, gravity) and electrical (supercapacitors) storage mediums.

25 ENERGY STORAGE↗
DOE OSTI2022

Building Initial Dynamic System Models for Digital Twins of the Cryogenic Moderator System at the ORNL Spallation Neutron Source

This work describes the initial development of dynamic system models of the cryogenic moderator system (CMS) of the Spallation Neutron Source (SNS) at ORNL as a part of the ORNL LDRD funded project Building TRANSFORM to Accelerate Digital Twin Applications for Nuclear Systems, LOIS 10563. The goal of the work is to start the dynamic system modeling effort with the end goal of using them for real-time applications as digital twins. The CMS is a cryogenic liquid hydrogen flow loop that provides moderation of the neutrons that are generated by the SNS. For optimal neutron production, the CMS needs to maintain a steady and controlled density of cryogenic hydrogen in the moderator section thus requiring precise temperature and pressure control. Due to the varied time scales and system characteristics, control of the system is complex, and diagnostics are also difficult. Difficulty in accessing the flow loop during operations, limited instrumentation and unknown design details of the equipment combine to make the case for having sophisticated digital twin models of the system. Operationally the CMS also provides a strong use case for digital twins due to the constant need of optimization and for troubleshooting/diagnostics. The large amount of data collected which are freely available for using in building the model and verifying and validating the model also makes it a great candidate for a proof-of-concept for digital twins. The project extends ORNL's capacity of development and implementation of the open-source dynamic system modeling tool TRANSFORM for engineering design and digital twin/real-time applications. Specific system configuration data for the CMS have been gathered and an initial dynamic model was created in the TRANSFORM library using Dymola as the solution platform. Models of increasing complexity are created to demonstrate the need for a multi-layered approach in digital twin modeling depending on the scale and phenomena being focused on. The dynamic modeling is shown to bring the dynamic operational aspects to the design process for systems as well as serve as a digital twin to the hardware and allow for models to be tuned and compared against real time operational data. These aims should help to push forward strategic goals of application of digital twins and increase the impact of ORNL systems modeling capabilities with TRANSFORM/Modelica for various advanced energy systems.

42 ENGINEERING↗
DOE OSTI2021

Region-Based Convolutional Neural Network for Wind Turbine Wake Characterization in Complex Terrain

We present a proof of concept of wind turbine wake identification and characterization using a region-based convolutional neural network (CNN) applied to lidar arc scan images taken at a wind farm in complex terrain. We show that the CNN successfully identifies and characterizes wakes in scans with varying resolutions and geometries, and can capture wake characteristics in spatially heterogeneous fields resulting from data quality control procedures and complex background flow fields. The geometry, spatial extent and locations of wakes and wake fragments exhibit close accord with results from visual inspection. The model exhibits a 95% success rate in identifying wakes when they are present in scans and characterizing their shape. To test model robustness to varying image quality, we reduced the scan density to half the original resolution through down-sampling range gates. This causes a reduction in skill, yet 92% of wakes are still successfully identified. When grouping scans by meteorological conditions and utilizing the CNN for wake characterization under full and half resolution, wake characteristics are consistent with a priori expectations for wake behavior in different inflow and stability conditions.

17 WIND ENERGY↗
DOE OSTI2020

Performance and Wake Characterization of a Model Hydrokinetic Turbine: The Reference Model 1 (RM1) Dual Rotor Tidal Energy Converter

The mechanical power and wake flow field of a 1:40 scale model of the US Department of Energy’s Reference Model 1 (RM1) dual rotor tidal energy converter are characterized in an open-channel flume to evaluate power performance and wake flow recovery. The NACA-63(4)-24 hydrofoil profile in the original RM1 design is replaced with a NACA-4415 profile to minimize the Reynolds dependency of lift and drag characteristics at the test chord Reynolds number. Precise blade angular position and torque measurements were synchronized with three acoustic Doppler velocimeters (ADV) aligned with each rotor centerline and the midpoint between the rotor axes. Flow conditions for each case were controlled to maintain a hub height velocity, uhub= 1.04 ms−1, a flow Reynolds number, ReD= 4.4 × 105, and a blade chord length Reynolds number, Rec= 3.1 × 105. Performance was measured for a range of tip-speed ratios by varying rotor angular velocity. Peak power coefficients, CP= 0.48 (right rotor) and CP= 0.43 (left rotor), were observed at a tip speed ratio, λ= 5.1. Vertical velocity profiles collected in the wake of each rotor between 1 and 10 rotor diameters are used to estimate the turbulent flow recovery in the wake, as well as the interaction of the counter-rotating rotor wakes. The observed performance characteristics of the dual rotor configuration in the present study are found to be similar to those for single rotor investigations in other studies. Similarities between dual and single rotor far-wake characteristics are also observed.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2023

Elucidating the Effects of Temperature on Nonaqueous Redox Flow Cell Cycling Performance

The impact of cell temperature is a relatively underexplored area within the burgeoning field of nonaqueous redox flow batteries (NAqRFBs). Here, we investigate the effect of elevated temperature on the performance of nonaqueous redox electrolytes and associated flow cells. Using a model compound, N-(2-(2-methoxyethoxy)-ethyl)phenothiazine (MEEPT), in a propylene-carbonate-based electrolyte, we experimentally measure the temperature dependence of relevant physicochemical properties (i.e., electrolyte conductivity, viscosity, diffusivity) and electrochemical characteristics (i.e., chemical and electrochemical reversibility) across a temperature range of 30 °C to 70 °C. We then perform flow cell studies, finding that while ohmic and mass transport resistances decrease significantly with increases in temperature for the MEEPT/MEEPT +· redox couple, accessible electrolyte capacity gradually reduces at temperatures > 50 °C. Ex-situ, post-test characterization using microelectrode voltammetry suggests that this capacity fade is due to instability of the MEEPT radical cation. Finally, using MEEPT as a posolyte and a model viologen negolyte (bis(2-(2-methoxyethoxy)ethyl)viologen), we assemble a full cell and perform polarization analyses, observing a 2× increase in the peak power density when the operating temperature is increased from 30 °C to 70 °C. Broadly, this work highlights opportunities for systematic engineering of nonaqueous electrolytes and flow cells for higher power operation at elevated temperatures.

Electrochemistry↗
DOE OSTI2023

Probing the chiral magnetic wave with charge-dependent flow measurements in Pb-Pb collisions at the LHC

The Chiral Magnetic Wave (CMW) phenomenon is essential to provide insights into the strong interaction in QCD, the properties of the quark-gluon plasma, and the topological characteristics of the early universe, offering a deeper understanding of fundamental physics in high-energy collisions. Measurements of the charge-dependent anisotropic flow coefficients are studied in Pb-Pb collisions at center-of-mass energy per nucleon-nucleon collision $\sqrt{s_{\textrm{NN}}}$ = 5.02 TeV to probe the CMW. In particular, the slope of the normalized difference in elliptic (v 2 ) and triangular (v 3 ) flow coefficients of positively and negatively charged particles as a function of their event-wise normalized number difference, is reported for inclusive and identified particles. The slope ${r}_3^{\textrm{Norm}}$ is found to be larger than zero and to have a magnitude similar to ${r}_2^{\textrm{Norm}}$, thus pointing to a large background contribution for these measurements. Furthermore, ${r}_2^{\textrm{Norm}}$ can be described by a blast wave model calculation that incorporates local charge conservation. In addition, using the event shape engineering technique yields a fraction of CMW (f CMW ) contribution to this measurement which is compatible with zero. This measurement provides the very first upper limit for f CMW , and in the 10–60% centrality interval it is found to be 26% (38%) at 95% (99.7%) confidence level.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Adaptive Angular Quadrature Scheme for a backwards-in-time Method of Characteristics Solution to the Radiative Transfer Equation [Slides]

Radiative transfer/radiation transport are important problems to solve in astrophysics and high energy density physics. Various methods exist to solve radiation transport, such as Monte Carlo (MC), Discrete Ordinates (S N ), Method of Characteristics (MOC), and the spherical harmonics (P N ) method. Method of Characteristics requires “launching” of rays in discrete directions. Unresolved details of angular mesh create ray effects and can miss sources in the domain. Ray effects can lead to unphysical “stepping” in solution and incorrect energy deposition. Adaptive quadrature schemes can be used to detect and mitigate these effects. The Method of Characteristics (MOC) is a common method for solving hyperbolic PDEs in radiation transport and supersonic flow problems. Generally in MOC for radiation transport, virtual particles are tracked from birth to the end of a timestep. This requires interpolation to go from final location to cell averaged or corner values of angular intensity. Backwards-in-Time (BIT) particle tracking avoids this by prescribing the final position of the virtual particle at the cell nodes/corners. Angular intensities are computed at time k + 1 by launching ray back to previous timestep(s), or t = 0. Scheme allows solution to be computed as the characteristic ray is traced backwards in time.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Lab-Scale, Closed-Loop Experimental Characterization, Model Refinement, and Validation of a Hydrokinetic Energy-Harvesting Ocean Kite

This paper presents a study wherein we experimentally characterize the dynamics and control system of a lab-scale ocean kite, and then refine, validate, and extrapolate this model for use in a full-scale system. Ocean kite systems, which harvest tidal and ocean current resources through high-efficiency cross-current motion, enable energy extraction with an order of magnitude less material (and cost) than stationary systems with the same rated power output. However, an ocean kite represents a nascent technology that is characterized by relatively complex dynamics and requires sophisticated control algorithms. In order to characterize the dynamics and control of ocean kite systems rapidly, at a relatively low cost, the authors have developed a lab-scale, closed-loop prototyping environment for characterizing tethered systems, whereby 3D printed systems are tethered and flown in a water channel environment. While this system has been shown to be capable of yielding similar dynamic characteristics to some full-scale systems, there are also fundamental limitations to the geometric scales and flow speeds within the water channel environment, making many other real-world scenarios impossible to replicate from the standpoint of dynamic similarity. Here, to address these scenarios, we show how the lab-scale framework is used to refine and validate a scalable dynamic model of a tethered system, which can then be extrapolated to full-scale operation. In this work, we present an extensive case study of this model refinement, validation, and extrapolation on an ocean kite system intended for operation in the Gulf Stream or similar current environments.

42 ENGINEERING↗