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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Liquid-phase turbulence measurements in air-water two-phase flows using particle image velocimetry

Liquid-phase turbulence plays a vital role in determining various gas-liquid two-phase flow parameters, such as void fraction distribution, bubble morphology, bubble-bubble interactions, and interfacial area concentration. In this study, a two-phase flow database including both the gas- and liquid-phases measurements was developed focusing on three bubbly flow conditions in an air-water two-phase flow loop with a vertical one-inch diameter circular pipe test section. A particle image velocimetry (PIV) system integrating an optical phase separation method, i.e., the planar laser-induced fluorescence (PLIF) technique using fluorescent particles and optical filtration, was applied to measure the liquid-phase turbulence information, including the time-averaged velocity, Reynolds stress, and turbulent kinetic energy for the liquid phase. The PIV measurements were taken at three ports along the test section at 14.5, 51.5, and 88.5 pipe inner diameters downstream of a bubble injector. In addition, a double-sensor conductivity probe was used to measure radial distributions of the local time-averaged void fraction and gas velocity. The measured liquid-phase turbulence was used to benchmark Sato's turbulence model considering the bubble-induced shear stress for the three tested bubbly flows. The benchmark results showed good agreement between the PIV measurements and model predictions. Lastly, in the two bubbly flows tested that have low void fractions being less than 3%, the effect of the bubble-induced turbulence was found not significant. However, the bubble-induced shear stress becomes important with the increase of the void fraction.

42 ENGINEERING↗
DOE OSTI2021

Research challenges and directions in HVAC fault prevalence

This study provides a review of the current state of knowledge, gaps, and potential value in research on the prevalence of faults in commercial buildings. Two separate efforts were made in this study: (1) we performed a literature review to determine the extent of currently available fault prevalence data for heating, ventilation, and air-conditioning (HVAC) systems, and (2) we conducted dozens of interviews with subject matter experts and stakeholders to determine the HVAC fault data that would be of greatest value. Through the literature review and interviews, we discovered unmet needs for empirical data on the prevalence of faults at the desired level of granularity, consistency, and scale; this lack of data leads us to recommend future work studying commercial buildings’ HVAC fault prevalence, with robust fault taxonomy and a variety of meaningful fault prevalence metrics.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Active Aerodynamic Load Control for Wind Turbines

The goal of this project was to develop and demonstrate an advanced dielectric barrier discharge (DBD) plasma actuator technology. We set out to demonstrate the efficacy and impact of the new actuator technology as a key component of an active load control system for wind turbines. A DBD plasma actuator consists of a thin layer of dielectric material separating a pair of offset electrodes. One of those electrodes is embedded between the dielectric layer and a non-conductive substrate, while the other is exposed to air. When driven by an appropriate high voltage waveform, the device ionizes the air near the surface of the dielectric and adjacent to the exposed electrode. Collisions between the ions in the plasma and neutral air molecules result in a wall-jet – a region of induced air velocity that can be used to modify the flow around a lifting body. Use of the device near the trailing edge of a wind turbine blade, designed in such a way as to amplify the effects of the flow-modifying device, can result in large changes to the global forces experienced by the blade. Because of the fast response time of the device, it can allow the turbine to react in real time to changes in the wind associated with turbulence, wind shear, gusts, and the like, when paired with appropriate sensors and control algorithms. The goal of this project was to increase the capacity of the device to induce velocity on its surface at the levels required by large, utility-scale wind turbines. The first technical goal was to increase the induced velocity from the current industry-best of about 4 m/s to 10 m/s by modifying the electrical waveform used to drive the device and by introducing a semi-conductive surface coating to control electrostatic charge build-up on the surface. The second goal was to use the device to modify the lift on a representative airfoil in a wind tunnel, demonstrating a reduction in lift coefficient of 0.2 or better. The third goal was to produce an actuator-induced velocity of 20 m/s. Alongside our partners at the University of Texas at Dallas, we also applied modern, advanced design methods to optimize the impact of the technology on the design of wind turbines. We also had planned to install a segmented, active load control system on a test turbine to demonstrate the ability to reduce unsteady aerodynamic forces on the turbine associated with changes in the wind. The highest induced velocity achieved during this research was 11 m/s. However, practical design constraints limited the change in lift coefficient to about 0.12 for a representative airfoil in the wind tunnel at a Reynolds number of 400,000. The primary conclusion is that the plasma actuator control authority remains insufficient for practical purposes when extrapolated to Reynolds numbers over 1 million. The potential impact of the active lift control concept was evaluated through detailed simulations for three wind turbine sizes: a 3.4MW onshore turbine, a 10MW offshore turbine, and a 15MW offshore turbine. A feedback control system was designed for each turbine within two scenarios: one where the active lift control is used as a retrofit capability on the baseline design, and the other where the designers were permitted to “upscale” the turbines in order increase annual energy production. The levelized cost of energy was then evaluated for the range of turbine sizes and design configuration. It was found that the LCOE reduction associated with active lift control fell in the range of 0.7% to 7.2%, with the highest reduction associated with upscaling the 3.4MW turbine.

17 WIND ENERGY↗
DOE OSTI2021

A permafrost implementation in the simple carbon–climate model Hector v.2.3pf

Abstract. Permafrost currently stores more than a fourth of global soil carbon. A warming climate makes this carbon increasingly vulnerable to decomposition and release into the atmosphere in the form of greenhouse gases. The resulting climate feedback can be estimated using land surface models, but the high complexity and computational cost of these models make it challenging to use them for estimating uncertainty, exploring novel scenarios, and coupling with other models. We have added a representation of permafrost to the simple, open-source global carbon–climate model Hector, calibrated to be consistent with both historical data and 21st century Earth system model projections of permafrost thaw. We include permafrost as a separate land carbon pool that becomes available for decomposition into both methane (CH4) and carbon dioxide (CO2) once thawed; the thaw rate is controlled by region-specific air temperature increases from a preindustrial baseline. We found that by 2100 thawed permafrost carbon emissions increased Hector’s atmospheric CO2 concentration by 5 %–7 % and the atmospheric CH4 concentration by 7 %–12 %, depending on the future scenario, resulting in 0.2–0.25 ∘C of additional warming over the 21st century. The fraction of thawed permafrost carbon available for decomposition was the most significant parameter controlling the end-of-century temperature change in the model, explaining around 70 % of the temperature variance, and was distantly followed by the initial stock of permafrost carbon, which contributed to about 10 % of the temperature variance. The addition of permafrost in Hector provides a basis for the exploration of a suite of science questions, as Hector can be cheaply run over a wide range of parameter values to explore uncertainty and can be easily coupled with integrated assessment and other human system models to explore the economic consequences of warming from this feedback.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Contributions to the Surface Downwelling Longwave Irradiance during Arctic Winter at Utqiaġvik (Barrow), Alaska

Intrusions of warm, moist air into the Arctic during winter have emerged as important contributors to Arctic surface warming. Previous studies indicate that temperature, moisture, and hydrometeor enhancements during intrusions all make contributions to surface warming via emission of radiation down to the surface. Here, datasets from instrumentation at the Atmospheric Radiation Measurement User Facility in Utqiaġvik (formerly Barrow) for the six months from November through April for the six winter seasons of 2013/14–2018/19 were used to quantify the atmospheric state. These datasets subsequently served as inputs to compute surface downwelling longwave irradiances via radiative transfer computations at 1-min intervals with different combinations of constituents over the six winter seasons. The computed six winter average irradiance with all constituents included was 205.0 W m −2 , close to the average measured irradiance of 206.7 W m −2 , a difference of −0.8%. During this period, water vapor was the most important contributor to the irradiance. The computed average irradiance with dry gas was 71.9 W m −2 . Separately adding water vapor, liquid, or ice to the dry atmosphere led to average increases of 2.4, 1.8, and 1.6 times the dry atmosphere irradiance, respectively. During the analysis period, 15 episodes of warm, moist air intrusions were identified. During the intrusions, individual contributions from elevated temperature, water vapor, liquid water, and ice water were found to be comparable to each other. These findings indicate that all properties of the atmospheric state must be known in order to quantify the radiation coming down to the Arctic surface during winter.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Validated model of a thermoelectric heat pump clothes dryer using secondary pumped loops

The energy associated with clothes drying makes up 4% of the total residential electrical energy consumption in the US. The cost is high since most clothes dryers use electric resistance heating which is inexpensive but also energy inefficient. State-of-the-art vapor-compression heat pump clothes dryers offer significant energy savings but have limited market penetration in the US. Here, a new configuration of clothes dryer was studied that utilizes a solid-state thermoelectric heat pump with pumped secondary water loops and conventional fin-and-tube water-to-air heat exchangers. Experimental results are presented for the thermoelectric dryer prototype with a combined energy factor of 6.89 lb BDW /kWh (specific moisture extraction rate of 1.71 kg w /kWh) and a dry time of 84 min for a standard load size of 8.45 lb (3.83 kg) with 57.5% starting moisture content. This is a 85% energy efficiency improvement over baseline electric resistance dryers. The efficiency and drying time results achieved are similar to vapor compression heat pump dryers. Compared to previous air-based thermoelectric clothes dryers, the energy efficiency has been increased by 6%, but drying time has been reduced by as much as 47% using secondary pumped loops and separate heat exchangers, which represents a significant advancement in the technology. In addition to the experimental prototype, a model was also developed to study the performance. The model was validated against experimental prototype data and used to identify the range of performance (dry time and efficiency) that could be expected of the design.

42 ENGINEERING↗
DOE OSTI2022

Picoseconds-Limited Exciton Recombination in Metal–Organic Chalcogenides Hybrid Quantum Wells

Metal-organic species can be designed to self-assemble in large-scale, atomically defined, supramolecular architectures. Hybrid quantum wells, where inorganic two-dimensional (2D) planes are separated by organic ligands, are a particular example. The ligands effectively provide an intralayer confinement for charge carriers resulting in a 2D electronic structure, even in multilayered assemblies. Air-stable metal organic chalcogenides hybrid quantum wells have recently been found to host tightly bound 2D excitons with strong optical anisotropy in a bulk matrix. Here, we investigate the excited carrier dynamics in the prototypical metal organic chalcogenide [AgSePh] ∞ , disentangling three excitonic resonances by low temperature transient absorption spectroscopy. Our analysis suggests a complex relaxation cascade comprising ultrafast screening and renormalization, inter-exciton relaxation, and self-trapping of excitons within few picoseconds. Finally, the ps-decay provided by the self-trapping mechanism may be leveraged to unlock the material's potential for ultrafast optoelectronic applications.

2D excitons↗
DOE OSTI2022

Electrochemical Corrosion of SIMFUEL: Effects of dissolved H2 and noble metal particles

This report describes the results from electrochemical corrosion tests that were conducted using simulated spent fuel (SIMFUEL) materials comprised of UO2 and surrogate fission products. Two SIMFUEL compositions were tested to quantify the effect of noble metal inclusions and dissolved H2 on the UO2 dissolution rate. One material consisted of UO2 with added lanthanide oxides (UO2 N) and the other consisted of UO2 with added lanthanide oxides and noble metals (UO2-H) at concentrations to simulate high burnup fuel. The electrochemical corrosion tests on the SIMFUEL materials were conducted in aqueous electrolyte solutions (pH 10) that were either saturated with air or purged with a H2/Ar gas mixture to maintain a constant dissolved H2 concentration. The results from electrochemical corrosion tests on SIMFUEL can be applied to qualitatively understand and also quantify the separate effects of water chemistry and fuel composition on the degradation behavior of the UO2 matrix. Open circuit potential (OCP) measurements on a SIMFUEL material of known composition (i.e., known fraction of NMPs at the fuel surface) immersed in a known solution chemistry (i.e., pH, Eh, [O2], [H2]) at known temperature provide qualitative insight into the degradation behavior of the UO2 matrix. If the OCP is above the threshold potential at which the oxidative dissolution of U(IV) to U(VI) occurs, the SNF is expected to degrade by oxidative processes under the experimental conditions. The net currents that are measured during potentiostatic tests, during which the surface potential of the SIMFUEL material is fixed by a potentiostat, can be used to quantify the UO2 degradation rate and optimize the rate constant values used in the Fuel Matrix Degradation Model (FMDM) for half reactions that occur on the SNF surface. Specifically, electrochemical measurements enable the estimation of the total anodic current at ECORR–which is the surface potential at which the total anodic and total cathodic currents are equal–so that the rate constant values for key reactions can be calculated. The open circuit potential measurements, potentiostatic tests, surface property measurements (scanning electron microscopy images and electrochemical impedence spectroscopy plots), and solution elemental composition analyses are being performed to update and optimize the FMDM. A case study is presented herein to show how electrochemical corrosion test results and accompanying characterization results for the UO2 N material in air-saturated solution can be used to validate the SNF surface reaction module of the FMDM. Future electrochemical tests will be conducted to provide quantitative information on the effects of NM content (burnup), H2 concentration, water chemistry, temperature, and galvanic couples with cladding and EBS alloys on UO2 degradation that can be used to improve the accuracy and functionality of the FMDM.

Thomas, Sara↗
DOE OSTI2025

Thermomagnetic generators for ultra-low-grade marine thermal energy harvesting

Low-grade thermal gradients in marine environments represent an underexploited energy source for autonomous sensing and monitoring. Converting such small temperature differences into usable electrical power remains a key challenge for ocean-deployed systems. We present a deployable thermomagnetic generator thoroughly characterized for marine-relevant energy harvesting. The device powers an internet-connected sensor and harvests ultra-low temperature differences akin to those at the ocean surface. It draws heat from water and rejects it to ambient air, operating optimally at a temperature difference (ΔT) of ~7.5 °C. Laboratory prototypes generated up to 6.7 mW at ΔT ~ 10 °C with gentle airflow (~1 m s -1 ). A separate controlled wave-tank demonstration validated stable operation and sensor powering under marine-like boundary conditions. Given its voltage and power margins, the generator could sustain multiple sensor nodes. Scalability and material assessments identify modular deployment and non-rare-earth alternatives as pathways toward practical marine energy harvesting and low-grade waste-heat recovery.

16 TIDAL AND WAVE POWER↗
DOE OSTI2026

Effect of NO on DME-Methanol HCCI Experimental Observations

Methanol is an attractive fuel for the maritime sector due to its wide availability. Its direct use as a fuel, however, is accompanied by challenges such as high latent heat of vaporization and low cetane number. A potential solution to overcome the ignition properties of methanol could be through on-board generation of dimethyl ether (DME) via catalytic dehydration of methanol. The resulting mixture from dehydration can be mixed in with the intake air to generate a homogenous charge compression ignition (HCCI) preburn for subsequent direct injection (DI) and successful ignition methanol at diesel–like timescales. However, if the preburn species are treated separately from the complete methanol MCCI approach the preburn heat release rate (HRR) phasing and behavior do not replicate the preburn behavior of the complete approach. Thus, the presence of the main methanol mixing controlled compression ignition (MCCI) combustion event influences the DME/methanol preburn kinetics. Specifically, it was found that trapped residual temperature alone was insufficient alone to be responsible for the observed differences, and that trace species concentrations of NO in the trapped residual gas also influenced DME/methanol kinetics increasing low temperature heat release (LTHR) magnitude and advancing high temperature heat release (HTHR) phasing. NO is not present in HCCI combustion of neat DME or DME/methanol blends nor is elevated gas temperature in the trapped residuals; both of which result in failure to accurately predict the HCCI combustion of DME/methanol blends when coupled with subsequent DI methanol MCCI. This work experimentally explores the effect of trapped residual temperature and NO on DME and DME/methanol HCCI combustion.

Jatana, Gurneesh [ORNL] (ORCID:0000000288903225)↗
DOE OSTI2022

Short–Term Forecasting of Wind Gusts at Airports Across CONUS Using Machine Learning

Short–term forecasting of wind gusts, particularly those of higher intensity, is of great societal importance but is challenging due to the presence of multiple gust generation mechanisms. Wind gust observations from eight high–passenger–volume airports across the continental United States (CONUS) are summarized and used to develop predictive models of wind gust occurrence and magnitude. These short–term (same hour) forecast models are built using multiple logistic and linear regression, as well as artificial neural networks (ANNs) of varying complexity. A suite of 19 upper–air predictors drawn from the ERA5 reanalysis and an autoregressive (AR) term are used. Stepwise procedures instruct predictor selection, and resampling is used to quantify model stability. All models are developed separately for the warm (April–September) and cold (October–March) seasons. Results show that ANNs of 3–5 hidden layers (HLs) generally exhibit higher hit rates than logistic regression models and also improve skill with respect to wind gust magnitudes. However, deeper networks with more HLs increase false alarm rates in occurrence models and mean absolute error in magnitude models due to model overfitting. For model skill, inclusion of the AR term is critical while the majority of the remaining skill derives from wind speeds and lapse rates. A predictive ceiling is also clearly demonstrated, particularly for the strong and damaging gust magnitudes, which appears to be partially due to ERA5 predictor characteristics and the presence of mixed wind climates.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Design optimization for Richtmyer–Meshkov instability suppression at shock-compressed material interfaces

We report the Richtmyer–Meshkov instability (RMI) is a phenomenon that occurs at the interface of two substances of different densities due to an impulsive acceleration, such as a shock wave passing through this interface. Under these conditions, the instability can be seen as interface perturbations begin to grow into narrow jets or spikes of one substance that propagate into the other. In some cases, this interface may involve an elastic–plastic material, which can play a significant role in the development and behavior of the RMI. The ability to effectively control RMI jetting and spike growth is one major limiting factor in technological challenges, such as inertial confinement fusion, that involve using high-pressure shock waves to implode a fuel target. The propagation of RMI growth can lead to increased asymmetry in this implosion process and significantly reduce the obtained energy yield. We use hydrodynamics simulations of impactor shock-compression experiments and methods based in design optimization to suppress RMI spike growth by altering the geometry and other properties of a shock-compressed elastic–plastic material target that shares an interface with atmospheric air. These hydrodynamics simulations use an arbitrary Lagrangian–Eulerian method with a high-order finite element approach. Our results demonstrate that RMI suppression can be achieved by intentionally creating a separate upstream interface instability to counteract the growth of long narrow RMI spikes at an interface with initial perturbations.

36 MATERIALS SCIENCE↗
DOE OSTI2026

1996 Bay Area Travel Study Wave 2

The 1996 Bay Area Travel Study, conducted by the Metropolitan Transportation Commssion, collected demographic, socioeconomic, and travel data for 3,618 households in California's nine-county Bay Area: Alameda, Contra Costa, Marin, Napa, San Francisco, San Mateo, Santa Clara, Solano, and Sonoma counties. The goal of the study was to collect information on activities for all people in each household, regardless of age or relationship. Respondents were asked to record all activities, including trips, over a two-day period. The data gathered during the survey will be used for the area's long-term transportation and air quality planning needs. The survey collected both weekday and weekend multi-day data and was the first activity-based survey conducted in the Bay Area. It also included separate sub-projects. A stated preference congestion pricing survey was administered to 150 of the respondents with a follow-up survey conducted with 110 participants. A follow-up survey was also completed by over half of the 3,618 respondent households to update contact and demographic information. These participants were then used as a panel sample for the 2000 Bay Area Travel Survey (NuStats Research and Consulting 1999).

1Hz data↗
DOE OSTI2024

Electrospinner Upgrades for Nanofiber Production

Electrospinning is an inexpensive method for producing nanofibers, with applications in accelerator targets, air filtration, and biomedicine. This project aims to upgrade and test an existing roll-to-roll electrospinner that is economical for industrial production. Our unit cannot adjust spinneret to collector separation and thus nanofiber diameter (application dependent). The electro-spinneret channel also does not have lateral adjustment capabilities. Lastly, the viscosities of our polymers have not been quantified, which can inform future injector nozzle designs. Modeling was done with Siemens NX CAD, and viscosity was measured using a Brookfield DVE-LV viscometer. A dual scissor lift design was approved, and construction was started, along with channel modifications. Viscosity measurements of polyvinyldimethylformamide were recorded with inconsistent results. Going forward, the scissor lift and channel modifications will be evaluated with our electrospinner. Future viscosity trials must be completed in accordance with testing requirements. The optimization of electrospinner units can make nanofiber production more feasible for many industries.

Black, Niko↗
DOE OSTI2022

Moving beyond 90% Carbon Capture by Highly Selective Membrane Processes

A membrane-based system with a retentate recycle process in tandem with an enriching cascade was studied for >90% carbon capture from coal flue gas. A highly CO 2 -selective facilitated transport membrane (FTM) was utilized particularly to enhance the CO 2 separation efficiency from the CO 2 -lean gases for a high capture degree. A techno-economic analysis showed that the retentate recycle process was advantageous for ≤90% capture owing to the reduced parasitic energy consumption and membrane area. At >90% capture, the enriching cascade outperformed the retentate recycle process since a higher feed-to-permeate pressure ratio could be applied. An overall 99% capture degree could be achieved by combining the two processes, which yielded a low capture cost of USD47.2/tonne, whereas that would be USD 42.0/tonne for 90% capture. This FTM-based approach for deep carbon capture and storage can direct air capture for the mitigation of carbon emissions in the energy sector.

42 ENGINEERING↗
DOE OSTI2022

Influence of discharge polarity on streamer breakdown criterion of ambient air in a non-uniform electric field

Streamer breakdown of atmospheric air with non-uniform dc electric field in a needle-to-plate electrode configuration is studied using a semi-analytic model and experimental measurements. A high voltage (either positive or negative) is applied to a hollow needle with 0.51 mm outer diameter and 0.25 mm inner diameter separated from a planar ground electrode by a gap distance of 0.1–1.4 cm. Breakdown voltages are recorded for both positive and negative discharge polarities. Empirical relations between the critical avalanche size for streamer breakdown and the gap distance are proposed. Using these empirical relations, a semi-analytic model based on Meek's criterion for streamer breakdown is developed to accurately predict the measured breakdown voltages. It is found that for pd > 380 Torr cm (or d > 0.5 cm at one atmosphere) streamer breakdown of ambient air occurs at a lower applied voltage for a positively biased needle compared to that with a negatively biased needle, referred as the polarity effect. For pd < 380 Torr cm breakdown is attained at a lower applied voltage with a negatively biased needle compared to that with a positively biased needle, and breakdown mode transits from the polarity effect to the so called inverted polarity effect.

42 ENGINEERING↗
DOE OSTI2026

Xanthos-Lake Dataset

The Xanthos-Lake v1.0 dataset provides the input data, trained machine-learning models, and simulation outputs needed to characterize lake water balance, snow and ice conditions, and mixing-layer temperature within the Xanthos global hydrological modeling framework. The dataset supports lake representation across a wide range of lake sizes and hydroclimatic conditions by combining xLSIM, a basin-specific machine-learning emulator of lake snow, ice, ice-cover fraction, and mixing-layer temperature, with the Xanthos-Lake water-balance model. The archive contains NetCDF datasets used to train and evaluate xLSIM, trained model weights, processed meteorological and lake-property inputs, and basin- and lake-category-specific simulation outputs. These materials are organized into four primary data groups, described below. Snowice_model_inputs: Contains the NetCDF input data used to train xLSIM. The xLSIM machine-learning framework uses three lake-based datasets. The meteorological forcing dataset provides monthly relative humidity, specific humidity, surface wind speed, maximum and minimum air temperature, downward longwave and shortwave radiation, snowfall, surface air pressure, and total precipitation. Lake surface area is included as an additional static predictor. The target-state dataset provides lake ice thickness, snow depth, snow cover, and lake mixing-layer temperature, while a companion lake-surface dataset provides the lake ice-cover fraction. Before training, ice thickness and snow depth are converted from meters to centimeters, mixing-layer temperature is converted from kelvin to degrees Celsius and constrained to nonnegative values, and ice-cover fraction is converted from a fraction to a percentage. The predictor variables are normalized using statistics calculated across the selected lakes and time steps. Snowice_model_outputs: Contains the NetCDF outputs generated by xLSIM. For each basin, xLSIM produces a file containing observed and predicted lake-state variables for the training, validation, and testing periods. The modeled variables include lake ice thickness, snow depth, snow cover, mixing-layer temperature, and lake ice-cover fraction. For basins without a sufficiently persistent snow-and-ice signal, the emulator predicts only mixing-layer temperature. The outputs also include training and validation loss histories, the selected model configuration, identifiers of the lakes used in training, and SHAP-based feature-importance information at the global, lake, and seasonal-regime levels. The trained machine-learning model weights are provided separately within the dataset archive. Together, these files support model evaluation and subsequent coupling with the Xanthos-Lake water-balance framework. XanthosLAKES: Contains the NetCDF input data used by the Xanthos-Lake framework. Monthly meteorological inputs include relative and specific humidity, downward shortwave and longwave radiation, mean, maximum, and minimum air temperature, wind speed, precipitation, snowfall, and surface air pressure. Static lake-property datasets provide lake identifiers, geographic locations, surface area, volume, mean depth, elevation, drainage area, fetch, outlet-routing information, and associated Xanthos grid-cell attributes. Separate bathymetric datasets provide the coefficients of the area–depth and volume–depth relationships for each aggregated lake unit. GLEV-based records provide observed lake surface area and evaporation data used to initialize lake states, define reference conditions, and calibrate and evaluate the model. Xanthos-Lake Outputs: Contains the basin- and lake-category-specific NetCDF outputs generated by Xanthos-Lake. Monthly variables include lake surface area, storage volume, outlet discharge, evaporation rate, evaporation volume, lake–groundwater exchange, lake inflow, ice thickness, snow depth, snow-cover fraction, ice-cover fraction, and mixing-layer temperature. The files also contain lake-specific calibration and validation statistics, including normalized root-mean-square error, mean absolute error, Nash–Sutcliffe efficiency, Kling–Gupta efficiency, and percent bias. Stored calibrated and derived parameters include the weir discharge coefficient, fractional freeboard, groundwater exchange coefficient, reference water level, corresponding reference surface area and storage volume, weir-width adjustment factor, and the fraction of routed inflow entering the lake. Basin identifiers, lake category, simulation period, calibration and validation periods, and parameter-schema information are retained as NetCDF metadata.

Abeshu, Guta [Pacific Northwest National Laborator↗
DOE OSTI2023

Design of a Two-Body Wave Energy Converter Featuring Controllable Geometry

While the field of wave energy has been the subject of numerical simulation, scale model testing, and precommercial project testing for decades, wave energy technologies remain in the early stages of development and must continue to prove themselves as a promising modern renewable energy field. A wave energy converter (WEC) concept currently being explored is the variable-geometry WEC (VGWEC), which aims to add an extra control option to WEC design. VGWECs attempt to incorporate controllable geometric features to adjust the floating body hydrodynamics to favor either power absorption, load shedding, or other operational goals. These variable geometry components have been proposed to be controlled on a sea-state-to-sea-state or wave-to-wave time scale depending on the force (or torque) and bandwidth limitations of the actuators required to manipulate just the controllable geometric hull features. Having control over both the WEC geometry components and the power takeoff (PTO) offers the potential to improve overall system performance and reliability if a cost-effective solution can be found for a given WEC architecture. This paper will present the recent developments and results of a VGWEC concept that incorporates variable-geometry modules into a two-body WEC. In the proposed VGWEC concept, the variable-geometry modules consist of air-inflatable bags in the surface float and a water inflatable ring in the subsurface body. The surface float is tethered directly to the subsurface body through tether lines, each connected to a separate PTO. Adjusting the geometry of both the surface and subsurface bodies along with the PTO coefficients can maximize power in design sea states while reducing motion response and PTO forces when transitioning to sea states where rated power is reached and load shedding is prioritized. The ability to transition between operating condition is expected to increase the sea state operational map and power capacity.

geometry control↗