Search NASA⌕ Search

SEARCH · Search NASA

Results for “Field Testing”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Energy performance of an operational government building retrofitted with ceiling phase change material tiles in a mixed-humid climate

The aging U.S. building stock requires various retrofit measures to enhance their energy efficiency. Here, this study explores the integration of thermal energy storage and advanced building controls as viable retrofit solutions for load flexibility and peak demand response while maintaining the occupants' comfort. A detailed assessment is conducted on the energy use of an administrative building in Sumner County, Kansas, focusing on the implementation of phase change materials (PCMs) in the ceiling of occupied zones. First, a time-resolved, whole-building energy model is developed in EnergyPlus, incorporating complex thermal behaviors such as air exchange between the plenum space and occupied zones, envelope leakage, and operational schedules. The model is then validated using experimental field test data, and subsequently a parametric assessment of key PCM properties and application strategies is performed to evaluate cooling electricity demand benefits. The parametric study shows that the optimal retrofit strategy, comprising a PCM with 23°C peak melting temperature, 0.125 in. (3.17 mm) thickness, and 150 kJ/kg latent heat, combined with active controls that include 8 h of precooling, forced convection under the ceiling, and a 2°C thermostat setback during peak hours, can result in a maximum load shift during the peak period of 99.6 % and the total electricity savings during the peak period of 98.9 % for the optimum case and thus provide significant cost savings under time-of-use pricing scenarios.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Commercial building HVAC demand flexibility with model predictive control: Field demonstration and literature insights

Model Predictive Control (MPC) for building Heating Ventilation and Air Conditioning (HVAC) systems is beginning to gain traction in the market, with a few controls companies incorporating it into their product offerings. However, it remains difficult to assess whether the energy cost savings are enough to justify the cost of MPC implementation for a particular building, given the limited number of reported demonstrations. For small commercial and residential buildings with relatively uniform systems, standardized approaches can help lower implementation costs. In contrast, for large buildings or district systems, the potential magnitude of cost savings could justify more customized solutions. Estimating the cost-effectiveness of MPC becomes more challenging for medium and large commercial buildings, where a one-size-fits-all solution may not be suitable, and the potential energy cost savings may be insufficient to justify a customized solution. To make MPC technology more appealing, incorporating additional value streams beyond energy efficiency alone can significantly increase its attractiveness. One such revenue stream is demand flexibility, in response to dynamic electricity prices, where MPC can leverage the thermal mass of the building to shift the load and support the grid. Building on an extensive literature review of MPC field studies focused on cost savings and demand flexibility, this paper presents the results of implementing MPC control in a large office building HVAC system in Berkeley, CA. Four different dynamic electricity price profiles were integrated into the MPC objective function to shift building demand while maintaining comfort, and field testing was performed with each price profile across four seasons. The results show potential for 40–65 % demand decrease percentage and up to 61 % annual cost savings compared to the existing rule-based control strategy, under the tested dynamic price scenarios. This paper also presents a sensitivity analysis on the cost savings with respect to the price profile variability, discusses the implementation effort for the price-responsive MPC, and compares the cost savings found in this study to those found in literature on the basis of dynamic price variability, or so-called Electricity Price Relative Standard Deviation.

Zanetti, Ettore↗
DOE OSTI2026

A call to standardize metrics for monitoring baleen whales near marine construction activities

Effective monitoring is necessary to protect marine mammal species during the construction of offshore infrastructure. The tools for detecting or monitoring marine mammals span traditional (e.g., visual observers, optical cameras), to newer (e.g., passive acoustic monitoring, infrared cameras, tags), and emerging (e.g., satellite imagery, environmental DNA, dimethyl sulfide concentration) technologies. Some are better suited for use during offshore development; however, peer-reviewed literature does not typically evaluate and report on the performance of these various technologies. We define a minimum set of metrics related to efficacy (i.e., confusion matrix, precision and recall, probability of missed mitigation), detection range (i.e., maximum and reliable detection range, spatial resolution), and data delivery (i.e., detection latency, system reliability, temporal resolution) that we recommend are needed to assess the utility of monitoring technologies for this purpose. Following a literature review of relevant studies, we highlight which publications reported these metrics and used multiple technologies to compare relative performance. We also emphasize the benefits of multi-modal approaches and recommend performance assessments through modeling or large-scale collaborative field testing. These metrics will standardize data collection, reporting, and analysis; promote consistent and comparable results; and foster collaboration among developers, regulatory agencies, and scientists. This may lead to the co-development of technology that achieves multiple goals, has greater application, and can answer research questions while collecting data to fulfill permitting requirements. These metrics may also inform decisions on what systems regulatory agencies might consider using and reduce monitoring costs, which is critical to support the marine sector's rapid growth alongside marine mammal conservation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Hydrological Control on Soil Redox Condition and Carbon Loss of Coastal Wetland Under Sea-Level Rise

Coastal wetlands are critical carbon sinks with their biogeochemical and ecological functioning shaped by dynamic hydrological conditions that are increasingly influenced by climate change. A key unresolved question is how hydrologic flow, vegetation response, and rising sea levels interact to regulate soil redox condition and carbon loss in coastal wetlands. Using a field-tested hydrological–biogeochemical–ecological modeling framework, we reveal how the interplay between terrestrial groundwater discharge and tidal fluctuations generates complex groundwater flow patterns at the terrestrial–aquatic interface, and how these patterns modulate soil redox conditions, in turn influencing soil organic matter decomposition and carbon loss. Notably, rising sea levels suppress soil CO2 emissions while reducing lateral dissolved carbon losses, thereby enhancing litter carbon sequestration under anoxic conditions. As vegetation responds to sea-level rise and carbon inputs diminish, litter carbon subsequently declines. These findings underscore a critical hydrological control on carbon cycling, advancing our understanding of coastal ecosystem resilience in a warming world.

Chen, Kewei [ORNL] (ORCID:000000032580514X)↗
DOE OSTI2025

Estimating Soil Thermal Inertia Profiles From the Passive Equilibration of a Temperature Probe

Knowledge of the distribution of soil thermal properties is important for understanding subsurface hydrological and biogeochemical processes. This study describes and evaluates quick thermal profiling (QTP), a new measurement technique aimed at providing rapid, depth-resolved measurements of soil thermal inertia at numerous locations across the landscape. A cylindrical probe with temperature sensors at multiple depths is quickly inserted into the ground, and soil thermal inertia is estimated from how quickly the probe temperature equilibrates with the soil. To this end, a finite volume heat transfer model is used to generate temperature equilibration time series across combinations of controlling factors, and a gridded search inversion approach is applied to infer soil thermal inertia. Field tests in the Arctic indicate that QTP measurements have a minimum uncertainty of 0.14 J m −2 K −1 s −1/2 and covary with dual-probe heat pulse thermal analyzer measurements (concordance correlation coefficient = 0.56) with a root-mean-square error of 0.40 J m −2 K −1 s −1/2 . Besides demonstrating the value of QTP for estimating thermal inertia, this study identifies various sources of measurement uncertainty, particularly probe-soil contact resistance and frictional heating. Further, analysis of soil samples indicates that thermal inertia can be used to estimate thermal conductivity and dry bulk density in the studied area, although such inferences are highly site-specific. Overall, the QTP method holds promise to generate thermal inertia data products and to complement other characterization approaches for advancing understanding of soil properties across far more locations than is currently possible.

Lamb, J. R. [Lawrence Berkeley National Laboratory↗
DOE OSTI2024

Tetris-inspired detector with neural network for radiation mapping

Abstract Radiation mapping has attracted widespread research attention and increased public concerns on environmental monitoring. Regarding materials and their configurations, radiation detectors have been developed to identify the position and strength of the radioactive sources. However, due to the complex mechanisms of radiation-matter interaction and data limitation, high-performance and low-cost radiation mapping is still challenging. Here, we present a radiation mapping framework using Tetris-inspired detector pixels. Applying inter-pixel padding for enhancing contrast between pixels and neural networks trained with Monte Carlo (MC) simulation data, a detector with as few as four pixels can achieve high-resolution directional prediction. A moving detector with Maximum a Posteriori (MAP) further achieved radiation position localization. Field testing with a simple detector has verified the capability of the MAP method for source localization. Our framework offers an avenue for high-quality radiation mapping with simple detector configurations and is anticipated to be deployed for real-world radiation detection.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Travelling wave‐based fault detection and location in a real low‐voltage DC microgrid

Abstract This paper discusses a device‐level implementation of a travelling wave (TW) protection device (PD) designed for a real low‐voltage DC microgrid. The TWPD fault detection and location algorithm is executed on a commercial digital signal processor (DSP) board, involving signal sampling at 1 MHz via the DSP board's analog‐to‐digital converter (ADC). The analogue input card measures positive pole, negative pole and pole‐to‐pole voltages at the TWPD location. Upon a successful fault detection using a second‐order high‐pass filter, the voltage data is normalised and multi‐resolution analysis (MRA) is performed on a 128‐sample buffer around the TW arrival time. MRA employs the discrete wavelet transform (DWT) to capture high‐frequency voltage patterns, and then the Parseval's energy theorem quantifies these TW characteristics by computing the energy of reconstructed wavelet coefficients. These energy values per decomposed frequency band are the basis for training a random forest classifier that predicts fault location and type. The TWPD is fully implemented and connected to a real DC microgrid in Albuquerque, NM, USA, for validation, and results are shown for field tests verifying the performance under faults.

Paruthiyil, Sajay Krishnan [Department of Electric↗
DOE OSTI2024

Identification of Distorted Gamma-Ray Signature Patterns Using Digital Filtering and Auto-Associative Memory Implemented with a Hopfield Neural Network

The detection and identification of radioactive sources in search applications involve analyzing passive gamma-ray emissions from high-level radioactive materials. This process uses a mobile detector-spectrometer in a complex field test environment. Recently, the use of artificial intelligence for gamma-ray spectrum analysis has shown promising results. However, challenges persist in identifying isotopic signatures from spectral measurements that may be distorted due to source shielding, random variations in natural radioactive background, or insufficient measurement time to obtain clear spectral lines. Here, this paper presents a novel intelligent signature recognition method that combines digital filtering techniques with an artificial Hopfield Neural Network (HNN). The HNN leverages auto-associative memory to store training sample patterns and match them with incoming gamma spectra from distorted sources. It restores the testing sources’ measurements by finding the closest matching signature patterns in the spectral library. Before HNN recognition, the measured spectrum undergoes preprocessing with a digital image filter to reduce fluctuations. Performance of the proposed method is evaluated using a set of gamma-ray spectra measured with a sodium iodide detector. The data collected include measurements from six pure samples: 241 Am, 60 Co, 137 Cs, 192 Ir, 239 Pu, and 235 U, which are used for training and validation (i.e. six cases). Additionally, the data set contains 24 distorted synthesized sources with various fluctuating backgrounds. Test results demonstrate the potential of the proposed method to accurately recognize the correct isotope with high precision, achieving an accuracy rate exceeding 85%. Furthermore, the proposed method exhibits superior performance compared to the conventional multiple regression fitting and simple feedforward neural network methods.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

An integrated experimental–modeling approach to identify key processes for carbon mineralization in fractured mafic and ultramafic rocks

Abstract Controlling atmospheric warming requires immediate reduction of carbon dioxide (CO2) emissions, as well as the active removal and sequestration of CO2 from current point sources. One promising proposed strategy to reduce atmospheric CO2 levels is geologic carbon sequestration (GCS), where CO2 is injected into the subsurface and reacts with the formation to precipitate carbonate minerals. Rapid mineralization has recently been reported for field tests in mafic and ultramafic rocks. However, unlike saline aquifers and depleted oil and gas reservoirs historically considered for GCS, these formations can have extremely low porosities and permeabilities, limiting storage volumes and reactive mineral surfaces to the preexisting fracture network. As a result, coupling between geochemical interactions and the fracture network evolution is a critical component of long-term, sustainable carbon storage. In this paper, we summarize recent advances in integrating experimental and modeling approaches to determine the first-order processes for carbon mineralization in a fractured mafic/ultramafic rock system. We observe the critical role of fracture aperture, flow, and surface characteristics in controlling the quantity, identity, and morphology of secondary precipitates and present where the influence of these factors can be reflected in newly developed thermo-hydro-mechanical–chemical models. Our findings provide a roadmap for future work on carbon mineralization, as we present the most important system components and key challenges that we are overcoming to enable GCS in mafic and ultramafic rocks.

58 GEOSCIENCES↗
DOE OSTI2025

Harnessing Virtual Power Plants Reliably: Enabling tools for increased observability, controllability, operation, and aggregation of distributed energy resources

Harnessing virtual power plants enhances the integration of distributed energy resources into utility grids for a sustainable energy future. Virtual power plants (VPPs) aggregate DERs to enhance resource adequacy and reduce emissions. U.S. utilities are exploring various technologies to manage DERs effectively. FERC Order 2222 allows DERs to participate in both wholesale and retail markets. Enhancing observability and controllability of behind-the-meter (BTM) DERs is essential for reliable grid operations. A hierarchical control architecture can improve coordination among residential energy resources. Field tests showed nearly 20% energy savings and 30% peak power reduction during grid events. Effective management of DERs requires enhanced situational awareness to prevent grid congestion. Integrating DER management systems (DERMS) with existing planning tools can improve operational security. Near-real-time grid models can validate optimal resource set points against resource uncertainty. Traditional uninterruptible power supplies (UPS) can be upgraded to support grid services and become part of VPPs. Upgrading UPS systems can reduce costs by 75% and unlock significant battery capacity. New battery management systems and grid-aware controllers are essential for optimizing UPS performance. Continued research and development are necessary to address challenges in integrating DERs into utility grids. Encouraging customer participation in pilot programs is vital for the evolution of VPPs. Here, the shift towards price-responsive DERs and VPPs is expected to enhance energy distribution efficiency.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Lossy Compression: An Online Multi-Stage Technology for High-Fidelity Synchro- Waveform Measurements

Effective real-time monitoring and analysis of distributed grids necessitate the use of synchro-waveform measurements, which capture almost all high-frequency disturbances and transient phenomena. However, due to limitations in high-speed measurements and network bandwidth, it is challenging to transfer all high-fidelity synchro-waveforms losslessly and successfully. To cope with these challenges, a hybrid-based online multi-stage compression algorithm is proposed to significantly improve the compression efficiency for synchro-waveform measurements. Initially, the multiple discrete Wavelet transformation is deployed to deconstruct the waveform components. The delta encoding is further developed to decrease the magnitude. In conjunction with the Lempel-Ziv-Markov chain, the hybrid compression algorithm is implemented to achieve real-time compression for the synchro-waveform measurements. Moreover, an innovative error index that synergizes the time and frequency domain error and correlation is formulated to evaluate the waveform distortion. By integrating compression ratio, suitable parameters can be optimally selected. Finally, the simulation, laboratory experiments, as well as field tests across a spectrum of sampling frequencies and time intervals are conducted to substantiate the efficacy of the proposed method. Here, the outcomes demonstrated that a compression ratio of approximately 15.5 and 17.83 can be reached for 0.5 s and 1 s data under both offline and online scenarios, which equates to a substantial 93.5% to 94.39% reduction in data storage requirements.

High-fidelity synchro-waveform measurements↗
DOE OSTI2024

The extent of multiallelic, co‐editing of LIGULELESS1 in highly polyploid sugarcane tunes leaf inclination angle and enables selection of the ideotype for biomass yield

Summary Sugarcane ( Saccharum spp. hybrid) is a prime feedstock for commercial production of biofuel and table sugar. Optimizing canopy architecture for improved light capture has great potential for elevating biomass yield. LIGULELESS1 ( LG1 ) is involved in leaf ligule and auricle development in grasses. Here, we report CRISPR/Cas9‐mediated co‐mutagenesis of up to 40 copies/alleles of the putative LG1 in highly polyploid sugarcane (2 n = 100–120, x = 10–12). Next generation sequencing revealed co‐editing frequencies of 7.4%–100% of the LG1 reads in 16 of the 78 transgenic lines. LG1 mutations resulted in a tuneable leaf angle phenotype that became more upright as co‐editing frequency increased. Three lines with loss of function frequencies of ~12%, ~53% and ~95% of lg1 were selected following a randomized greenhouse trial and grown in replicated, multi‐row field plots. The co‐edited LG1 mutations were stably maintained in vegetative progenies and the extent of co‐editing remained constant in field tested lines L26 and L35. Next generation sequencing confirmed the absence of potential off targets. The leaf inclination angle corresponded to light transmission into the canopy and tiller number. Line L35 displaying loss of function in ~12% of the lg1 NGS reads exhibited an 18% increase in dry biomass yield supported by a 56% decrease in leaf inclination angle, a 31% increase in tiller number, and a 25% increase in internode number. The scalable co‐editing of LG1 in highly polyploid sugarcane allows fine‐tuning of leaf inclination angle, enabling the selection of the ideotype for biomass yield.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

BSDF Data generation for daylight applications: A call for international standardization

Standardized methods for generating angle-dependent, bidirectional, solar-optical properties for complex fenestration systems do not exist, which means that energy and daylight evaluations in building performance simulations often suffer from major inaccuracies. This position paper provides an overview of state-of-the-art data-driven methods for characterizing light scattering properties of fenestration materials and blind systems (e.g. fabrics, metal slats, patterned glazing), validation via laboratory, simulation and field tests, and salient issues in support of standardization of such methods via the International Standardization Organization (ISO). The ISO standard is intended to provide the fundamental underpinnings for recently mandated daylight standards that rely on bidirectional scattering distribution function data for climate-based daylight modelling and building performance simulations.

Geisler-Moroder, D.↗
DOE OSTI2024

Intraspecific variability in plant and soil chemical properties in a common garden plantation of the energy crop Populus

Optimizing crops for synergistic soil carbon (C) sequestration can enhance CO 2 removal in food and bioenergy production systems. Yet, in bioenergy systems, we lack an understanding of how intraspecies variation in plant traits correlates with variation in soil biogeochemistry. This knowledge gap is exacerbated by both the heterogeneity and difficulty of measuring belowground traits. Here, we provide initial observations of C and nutrients in soil and root and stem tissues from a common garden field site of diverse, natural variant, Populus trichocarpa genotypes—established for aboveground biomass-to-biofuels research. Our goal was to explore the value of such field sites for evaluating genotype-specific effects on soil C, which ultimately informs the potential for optimizing bioenergy systems for both aboveground productivity and belowground C storage. To do this, we investigated variation in chemical traits at the scale of individual trees and genotypes and we explored correlations among stem, root, and soil samples. We observed substantial variation in soil chemical properties at the scale of individual trees and specific genotypes. While correlations among elements were observed both within and among sample types (soil, stem, root), above-belowground correlations were generally poor. We did not observe genotype-specific patterns in soil C in the top 10 cm, but we did observe genotype associations with soil acid-base chemistry (soil pH and base cations) and bulk density. Finally, a specific phenotype of interest (high vs low lignin) was unrelated to soil biogeochemistry. Our pilot study supports the usefulness of decade-old, genetically-variable, Populus bioenergy field test plots for understanding plant genotype effects on soil properties. Finally, this study contributes to the advancement of sampling methods and baseline data for Populus systems in the Pacific Northwest, USA. Further species- and region-specific efforts will enhance C predictability across scales in bioenergy systems and, ultimately, accelerate the identification of genotypes that optimize yield and carbon storage.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Characterizing Interference in a Wave-Powered Buoy

Oceanographic measurement buoys are power constrained by the capacity of their batteries and the available solar power. Many buoys are in locations with abundant wave energy, but wave energy converters are not being used to power them. One reason wave energy converters may not have not been developed for wave measurement buoys is that many buoys measure waves by precisely following the wave motion. Wave energy converters may inhibit this wave-following ability by altering a buoy's response to incoming waves. In this report, we present the results of field tests that measured the extent to which buoy motion was changed by modifications to the buoy for wave energy harvesting. The motion of the buoy was significantly modified by the addition of the hardware components necessary for harvesting wave energy. The ratio of the mass of the wave energy converter to the mass of the buoy was high for the system tested, which strongly affected buoy motion. A lower value for this ratio would decrease the effect of the wave energy converter on the motion of the buoy, thereby decreasing the impact on the buoy's ability to measure waves but also decreasing the power production capabilities. Therefore, the use of wave energy converters to power wave measurement buoys may be feasible for large buoys that measure low-frequency waves and have low power requirements.

16 TIDAL AND WAVE POWER↗
DOE OSTI2024

Advanced HVAC Humidity Control for Hot-Humid Climates

During this project we develop and validate a cost-effective, integrated control solution to improve humidity control and comfort for energy-efficient homes in hot-humid climates. This study focuses on developing a strategy that is effective, field tested, and practical for builders to install with minimal disruption to standard practices. A successful solution would simplify the transition to high-performance humidity control and be the basis for design and installation guidance. By relying on the central system as a starting point, the strategy employed minimizes system complexity and cost for builders, while improving comfort and operating cost for homeowners. The solution strategy was to coordinate the cooling, dehumidification, and ventilation functions of central, ducted HVAC systems to better control indoor humidity, improve occupant thermal comfort, and capture energy savings. The primary strategic goals were to: (1) optimize dehumidification by the central air-conditioning system, particularly during part-load conditions, using conventional equipment with modified control settings and lower system airflows; (2) maximize ventilation during heating/cooling on-cycles, to “bank” and condition outdoor ventilation air, and minimize ventilation during off-cycles; (3) quantify the effectiveness and energy impact of the dehumidification and ventilation strategies, while identifying a metric that would be useful to evaluate latent effectiveness. For the test houses in our study, located in Richmond Hill, Georgia; Houston, Texas; and Monroe, Louisiana we observed: (1) the indoor humidity did not exceed 60% RH during the monitored cooling season for 99% of the time in Richmond Hill, 96% of the time in Houston, and 90% of the time in Monroe; (2) the dehumidification strategy improved the steady-state latent capacity of the HVAC system at design conditions by 16% to 49% at the Houston test house and by 28% to 71% at the Monroe test house, depending on which mode the system was operating in; and (3) the good results at the test houses were primarily due to the amount of time the air-conditioning system operated in ramping or dehumidification modes, or both, particularly during the early cooling season. This study demonstrates that air conditioners or heat pumps with a single-stage compressor can provide good humidity control without the need for a two-stage or variable-stage compressor system. The airflow and control settings for ramping and dehumidification modes are critical to control indoor humidity in hot-humid climates, particularly during part-load and shoulder season conditions. The dehumidification strategy used in this study did not jeopardize the mechanical reliability of the cooling equipment. The strategies used in this study are applicable across various equipment brands, models, and efficiency levels, and also applicable to a broad range of homes in hot-humid climates. Results will vary by specific equipment, location, and house configuration and construction.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Membrane Development for CO2 Capture from Steel Manufacturing

The U.S. government is targeting a net-zero carbon-emission economy by 2050, offering an exciting opportunity for membrane-based CO2 capture from various industrial point sources. Given that industrial flue gas has low CO2 partial pressures and high volumetric flow rates, high-permeance membranes are needed to make membrane technology economically viable for large-scale deployment. Thin film composite (TFC) membranes are necessary for this implementation because they can provide high permeance by forming a thin selective layer on top of a porous support. This presentation will report the rational design and fabrication of NETL’s highly permeable non-aging TFCs achieved by: synthesizing a high-performance rubbery selective material; developing a high-porosity membrane support; optimizing coating methods to assemble the two materials into scalable membranes; and scaling up membrane supports and TFCs via a roll-to-roll process. The novel rubbery selective material shows mixed-gas CO2 permeability of 930 Barrer and CO2/N2 selectivity of 44, exceeding the 2008 Robeson upper bound. The resulting TFCs yield remarkably high CO2 permeance of 4,500 GPU and CO2/N2 selectivity of 34 at 23ºC. Moreover, the TFCs exhibit not only excellent performance stability (or non-aging behavior) for 1,000 hours in the lab, but also maintain their separation properties in a 700-hour field test at the U.S. DOE’s National Carbon Capture Center using real humid flue gas.

Tran, Thien↗
DOE OSTI2024

50 MW Segmented Ultralight Morphing Rotors for Wind Energy

A multi-institutional team designed a 50 Megawatt (MW) rated wind turbine featuring downwind aeroelastic morphing to reduce blade loads and allow an ultralight segmented rotor (mass reduction of about 25% compared to a conventional upwind rotor). The team used a control co-design approach with state-of-the art simulations including for the rotor and tower design using non-linear fluid-structure interactions and control algorithms, and the team also designed, built, and field-tested an aeroelastically-scaled downwind rotor to demonstrate this novel technology and validate the design tool fidelity. In a follow-on phase, these results were used along with an updated Levelized Cost Of Energy (LCOE) methodology to co-design a more detailed set of 25 MW rated turbine designs (including individual pitch control) based on minimum LCOE with highly flexible blades for an Atlantic Ocean offshore fixed-bottom design targeted towards market technology evaluation. A set of upwind and downwind designs at 25 MW rated scales were found to provide the best LCOE, with strong improvements over all previous offshore reference turbines (NREL 5MW, DTU 10 MW and IEA 15 MW). The optimized design would represent the world’s largest offshore turbine design, which combines several state-of-the-art structural, aerodynamic, and control technologies into a new and optimized system concept.

17 WIND ENERGY↗