Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “turbine evaluation”

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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Use of Multiple Tracer Gases to Quantify Vane Trailing Edge Flow Into Turbine Rim Seals

Abstract Overlapping features are commonly used as rim seals between stationary and rotating components in a turbine stage. These rim seals are used to prevent main gas path ingestion to the wheelspace cavity, which reduces the lifespan of critical engine components such as the turbine disk. In addition to the overlapping features, purge flow, diverted from the compressor, is injected into the rim cavity to act as an airflow sealing mechanism. Previous research identified that in addition to the purge flow in the rim cavity, cooling flow from the vane trailing edge (VTE) is ingested into the rim seal cavity carrying the potential to cool components in the wheelspace. These previous findings, however, were not able to distinctly separate purge from VTE cooling flows, which is the contribution of this paper based on uniquely using two different tracer gases. A one-stage test turbine operating at engine-relevant conditions and consisting of real engine hardware was used to validate and quantify the ingestion of the VTE flow by independently seeding the purge and VTE flows with two different tracer gases. Experimental results show the presence of VTE flow in the rim seal throughout all purge flowrates evaluated. Circumferential variation of VTE flow was also studied both experimentally and computationally using a computational fluid dynamics model. Results showed that ingested VTE flow can reduce the detrimental effect of hot gas ingestion particularly at higher purge flowrates.

Engineering↗
DOE OSTI2020

Data for Post-Access Report: Tidal Energy Resource Characterization and Model Validation via the Assessment of Cost-effective Spatially Distributed Current Measurements from microFloat Swarms

This project evaluated how high-resolution, spatially distributed field data can be used to refine and validate site-scale hydrodynamic simulations of tidal channels. Use of such spatially-distributed field observations or site-scale hydrodynamic simulations will be needed for producing accurate predictions of tidal energy production over larger arrays of tidal turbines. The data contained in this archive includes field observations of water velocity from a series of short surveys in Agate Pass taken on August 20th, 2020 using station-keeping ADCP (acoustic doppler current profiler) measurements, drifting downward-looking ADCPs, and microFloats, gathered by researchers at APL-UW under a previous project. It also includes high-resolution hydrodynamic model runs for the site during that time generated under TEAMER support. An explanatory file (.pdf format) describes the survey and field data structure. Processed data is stored in .mat format. Survey summary: start time, number of floats, water level. microFloat data: - Cleaned data for each float in survey, - Time series of position (lat., lon.), depth (relative to surface), and horizontal velocity (u, v) Drifting ADCP data: - Cleaned data for each drifting ADCP in survey - Time series of position (lat., lon.), sample depth (relative to surface), and observed water velocity (u,v,w) Stationary ADCP data: - Cleaned data for each station-keeping data set in survey - Time series of position (lat., lon.), sample depth (relative to surface), and observed water velocity (u,v,w) FVCOM (Finite Volume Coastal Ocean Model) model outputs: Water level and velocity, as well as derived variables (e.g., power density) from the final refined model simulations for the Agate Pass subdomain. Contained in NetCDF and ASCII files for the duration of August 18th and 20th 2020 field surveys. Additional scripts for processing the data and generating the figures in the report are included.

16 TIDAL AND WAVE POWER↗
DOE OSTI2022

Application of FARM to an IES scenario within the FORCE ecosystem

The FARM (Feasible Actuator Range Modifier) software module is a component of the RAVEN-based FORCE framework for analysis of Integrated Energy Systems (IES). FARM supports the HERON software module in the evaluation of the optimal dispatch by evaluating feasible set-points for the different IES unit components. Set-points are required to satisfy limits on both production variables (i.e., the variables to be optimized such as the electrical power, the hydrogen production rate, etc.) and process variables tied to the service life of equipment (e.g., steam flowrate, vessel pressure, turbine firing temperature, etc.). This problem is addressed by adopting a two-stage approach. First, the HERON power dispatcher determines set-points that meet the constraints on the former variables (e.g., power levels and power ramp rate limits). These constraints are called explicit constraints. Then, FARM adjusts these set-points to ensure the respect of the limits on the latter variables given the knowledge of the system physics acquired through machine learning algorithms. These constraints are called implicit constraints. From this standpoint, FARM constitutes a bridge between the HERON power dispatcher that adopts a simplified description of the IES unit (low-resolution physics) and the HYBRID high-fidelity models (high-resolution physics). The original version of the FARM software module (FARM-Alpha) was released by Argonne National Laboratory in January 2021. In the latest version of the code released in July 2022 (FARM-Delta), the Reference Governor (RG) algorithm was upgraded to a Multi-Input Multi-Output version from its original Single-Input Single-Output form. The RG algorithm acts to enforce constraints. With this improvement an IES unit is now treated as a single dynamic system from the standpoint of control. The crosstalk among components in an IES unit is now fully considered thereby ensuring a true optimization is obtained for those units that have multiple set-points. In this report, the capabilities of FARM-Delta operating within the FORCE ecosystem are demonstrated for an IES test case. The specific configuration of IES unit for this case was selected by the IES team with consultation from the Advanced Reactor IES Expert Group. A full TEA analysis that invoked HERON, HYBRID, FARM, and RAVEN was performed and serves to demonstrate how the latest modification to FARM algorithms (i.e., state variable selection, state-space matrices derivation, set-point verification) can shape setpoints that might otherwise compromise the health of equipment through accelerated wear and tear. In this specific test case, it was demonstrated that these algorithms ensure a more efficient utilization of steam resources to be shared by two different subsystems, namely Balance of Plant (BOP) and High-Temperature Steam Electrolysis (HTSE). Finally, some code improvements that can further enhance the user-friendliness are suggested.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Validation of Reanalysis-Based Offshore Wind Resource Characterization Using Lidar Buoy Observations

The offshore wind industry in the U.S. is gaining strong momentum to achieve sustainable energy goals, and the need for observations to provide resource characterization and model validation is greater than ever. Pacific Northwest National Laboratory (PNNL) operates two lidar buoys for the U.S. Department of Energy (DOE) in order to collect hub height wind data and associated meteorological and oceanographic information near the surface in areas of interest for offshore wind development. This work evaluates the performance of commonly used reanalysis products and spatial approximation techniques using lidar buoy observations off the coast of New Jersey and Virginia, USA. Reanalysis products are essential tools in order to set performance expectations and quantify the wind resource variability at a given site. Long-term accurate observations at typical wind turbine hub-heights have been lacking at offshore locations. Using wind speed observations from both lidar buoy deployments, biases and degrees of correspondence for the Modern Era Retrospective Analysis for Research and Applications-2 (MERRA-2), the North American Regional Reanalysis (NARR), and the analysis system of the Rapid Refresh (RAP) are examined both at hub height and near surface. Results provide insights on the performance and uncertainty of using reanalysis products for long-term wind resource characterization.

lidar buoy, model validation, offshore wind energy↗
DOE OSTI2024

Hawaii Fish Company Inc. Technical Assistance Voucher (Abstract)

For the past several years, the National Renewable Energy Laboratory (NREL), Sandia National Laboratories (SNL), and Pacific Northwest National Laboratory (PNNL) have provided technical assistance to the recipients of Department of Energy (DOE) -funded voucher programs, namely American-Made Challenges (AMC), the Incubator Program, and the Small Business Vouchers Program. Drawing on lessons learned and from first-hand experiences, NREL is leading a new holistic and streamlined voucher program aimed at strengthening ties between American innovators and the national labs. This new program, “Vouchers to Enable Laboratory and Organizational Collaboration for Innovation and Technology Improvements,” or VELOCITI, will leverage the successful elements of past programs, create administrative efficiencies, and enable the buildout of a national program to drive strong relationships between entrepreneurs and the national labs to accelerate the roll-out of new technologies in the US solar sector. This work will evaluate Hawaii Fish Company’s (HFC’s) floating renewable energy-powered aeration systems, designed primarily for aquaculture ponds, with crossover applications to farm ponds, reservoirs, and other water bodies. Notably, HFC’s systems include a variety of configurations, such as direct-solar systems, battery-storage systems, and systems with a secondary wind turbine option. HFC is planning to refine and commercialize their renewable energy aeration platforms. Presently, HFC is fabricating multiple configurations of the systems for deployment in multiple locations in the U.S. PNNL will apply technical expertise to assist in these goals, benefitting the industry partner by giving them an understanding of the performance of their systems. The technical objectives of this project are to understand system performance and reliability, determine a path toward certification, and model the performance of the systems in different locations.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

Wind farm blockage effects: comparison of different engineering models

The work presents four engineering methods to estimate the induction zone in front of a wind turbine and account for the wind farm blockage effect. The methods comprise the vortex cylinder model, vortex dipole model, self-similar model, and wake projection model. The majority of the models presented account for yaw misalignments and ground effect. Actuator disk simulations are used to verify the individual models. The performance of each model is evaluated both in terms of precision and computational time. The induction models are coupled to wake models within the FLOw Redirection and Induction in Steady State framework to provide the full velocity field within a wind farm. Sample wind farm computations are presented, and the impact of including induction effects into wind farm performance predictions is reported. The different codes are publicly available online.

17 WIND ENERGY↗
DOE OSTI2021

Open-Loop Control of Adjustable Tuned Mass Dampers for Floating Wind Turbine Platforms: Preprint

Floating offshore wind turbines have several advantages over their land-based counterparts, including access to stronger, more consistent winds and proximity to population centers. However, increased costs from the platform have been a challenge inhibiting their widespread adoption. New damping technologies with tunable target frequencies and damping ratios promise a greater degree of control over platform motions, allowing hulls to be designed smaller and reducing the overall cost of the turbines. In this work, a control strategy is proposed for these adjustable tuned mass dampers (TMDs). A frequency-domain model of the system is developed, from which response amplitude operators (RAOs) for the platform's rigid-body modes can be obtained for different natural frequencies and damping ratios of the dampers. Using these RAOs, and JONSWAP spectrums of operational and extreme sea states, the performance of the various damper settings are compared by evaluating the standard deviation of a rigid-body motion of interest (platform pitch or heave). By finding the optimal damper setting for a range of representative design load cases (DLCs), a lookup function is made to return the damper target frequency given the peak period of the sea state. To determine the current sea state, we propose a simple estimator that uses wave measurements (e.g., from a measurement buoy) to determine the peak period and significant wave height. The significant wave height is determined using the statistics of the past 100 seconds of wave elevation information and the peak period is computed using a frequency locked loop. Initial results show that we can use these estimated values to control the TMD natural frequency with an open loop controller. The controlled system is tested in a range of environmental conditions determined by the International Electrotechnical Commission design load cases (DLCs), which include normal and extreme wind and wave models. In these tests, we compare the performance of 4 cases: (1) no TMD, (2) a constant TMD based on the worst case DLC, (3) a controlled TMD based on known wind and wave environments, and (4) a real-time controlled TMD using estimated wind and wave environments. The effect of hull-based TMD control is also compared to changes in traditional wind turbine control via blade pitch.

control↗
DOE OSTI2024

FARM User Guidance and Instructions

The FARM (Feasible Actuator Range Modifier) module is a component of the RAVEN-based FORCE framework for the analysis of Integrated Energy Systems (IES). FARM aids HERON in the solution of the power dispatch problem by evaluating feasible set-point signals to be issued to the control systems of the different IES unit components. Set-points need to satisfy limits on both production variables (i.e., the variables to be optimized such as the electrical power, etc.) and process variables tied to the service life of equipment (e.g., steam flowrate, vessel pressure, turbine firing temperature, etc.). To enforce all these limits, a two-stage approach is adopted. First, the power dispatcher algorithm in HERON module estimates set-points that meet the constraints on the production variables, e.g., power levels and power ramp rate limits. These constraints are called explicit constraints. Then, if necessary, FARM adjusts these set-points to ensure the respect of the limits on the process variables of interest, given the knowledge of the system dynamics acquired through machine learning algorithms. These constraints are called implicit constraints. From this standpoint, FARM constitutes a bridge between the HERON power dispatcher that adopts a simplified description of the IES unit (low-resolution physics) and the HYBRID high-fidelity models (high-resolution physics). In this report, the general workflow and the software requirements of FARM module are summarized, and the detailed instructions for installing FARM software, running built-in example cases, deriving Linear Parameter-Varying (LPV) state-space models, and using FARM for user-defined power dispatch problems are provided.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

FARM supervisory capabilities for thermal energy storage

The FARM (Feasible Actuator Range Modifier) module is a component of the RAVEN-based FORCE framework for the analysis of Integrated Energy Systems (IES). FARM aids HERON in the solution of the power dispatch problem by evaluating feasible set-point signals to be issued to the control systems of the different IES unit components. Set-points need to satisfy limits on both production variables (i.e., the variables to be optimized such as the electrical power, etc.) and process variables tied to the service life of equipment (e.g., steam flowrate, vessel pressure, turbine firing temperature, etc.). To enforce all these limits, a two-stage approach is adopted. First, the power dispatcher algorithm in HERON module estimates set-points that meet the constraints on the production variables, e.g., power levels and power ramp rate limits. These constraints are called explicit constraints. Then, if necessary, FARM adjusts these set-points to ensure the respect of the limits on the process variables of interest, given the knowledge of the system dynamics acquired through machine learning algorithms. These constraints are called implicit constraints. From this standpoint, FARM constitutes a bridge between the HERON power dispatcher that adopts a simplified description of the IES unit (low-resolution physics) and the HYBRID high-fidelity models (high-resolution physics). In this report, an overview of the major capabilities of the latest release of FARM is provided, along with a summary of the tool demonstration campaign conducted at the Dynamic Energy Technology and Integration Laboratory (DETAIL) facility. These results assess the performance of the control system architecture embedding FARM both as a Validator of the HERON power dispatcher and as a real time Supervisory control scheme. Additionally, the report outlines the areas that FARM might benefit from, along with proposed solutions.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Feasibility of Ocean-Based Renewable Energy in the Gulf of Mexico

This paper summarizes a comprehensive feasibility assessment of six offshore renewable energy sources in the Gulf of Mexico (GOM) to potentially provide utility-scale electricity from the Outer Continental Shelf (federal waters) and state waters to land-based grids. Overall, the primary objective is to inform future energy planning. The authors evaluated offshore wind, wave energy, tidal energy, ocean-based solar photovoltaics (PV), ocean current, and ocean thermal energy conversion. Of these energy resources, offshore wind was the most viable option and was the focus of the second part of the study. The technical challenges of developing offshore wind in the GOM are discussed including hurricane design for turbines and substructures, as well as turbine solutions to overcome lower wind regimes. In addition, advantages to offshore wind development in the GOM are described including proximity to oil and gas supply chains. Economic analysis using established cost models at the National Renewable Energy Laboratory identified hypothetical project locations where net value of offshore wind was the highest, and the levelized cost of energy (LCOE) was calculated for three sites: Port Isabel, Port Arthur, and Pensacola. Offshore wind LCOE in the GOM was found to be higher than those in sites along the north and mid-Atlantic coasts, but decreasing cost trajectories indicate the possibility of economic viability for locations in Texas and west Louisiana after 2030. The extrapolated 2030 LCOE values range from 73 dollars per MWh (Site 1, Port Isabel) and 79 dollars per MWh (Site 3, Port Arthur) to 91 dollars per MWh (Site 5, Pensacola).

16 TIDAL AND WAVE POWER↗
DOE OSTI2026

Development of a Test-Bed for Testing and Refining EarthEn’s Supercritical CO 2 Based Energy Storage System

EarthEn’s energy storage concept leverages supercritical carbon dioxide (sCO 2 ) as a working fluid and relies on compact, high-performance components operating at elevated pressures and temperatures. To accelerate component development and reduce technical risk prior to larger-scale demonstrations, Oak Ridge National Laboratory (ORNL) developed a 100 kW-scale sCO 2 test-bed under a Cooperative Research and Development Agreement with EarthEn (CRADA NO. NFE-24-10050). The objective of the work was to design and construct a flexible experimental facility capable of reproducing key thermodynamic state points and heat-transfer conditions relevant to EarthEn’s thermal energy storage (TES) cycle, with particular emphasis on enabling development and evaluation of next-generation heat exchangers and TES concepts. The test-bed consists of a closed-loop sCO 2 circulation system housed within an open-topped enclosure. In its as-installed configuration, dense-phase sCO 2 is recirculated through a printed circuit recuperator, an electrically heated section, a throttling device used to simulate turbine expansion, and a water-cooled printed circuit heat exchanger that rejects heat to the building chilled-water system before returning to the pump. The pump is driven by a variable frequency drive, enabling controlled adjustment of flow and operating point. A comprehensive instrumentation suite was integrated to support both safe operation and high-quality data collection. Installed sensors include Coriolis flow meters for sCO 2 flow rate and density, resistance temperature detectors and thermocouples distributed throughout the loop (including the heated section and key heat exchanger ports), and pressure transducers for absolute and differential pressure measurements. The facility was designed to support high-pressure (19 MPa nominal) and high-temperature (575°C nominal) operation with credited overpressure protection provided by a rupture disk. Nominal operating conditions were selected to support 100 kW-class testing while maintaining flexibility for non-heated and heated shakedown, control development, and future integration of advanced TES test sections. In parallel with facility development, a system-level thermal-hydraulic model was created using Modelica-based tools to support component sizing, anticipate performance over targeted test conditions, and establish a framework for future model calibration against experimental data. At the conclusion of the project performance period, the facility was in final assembly, and the pressure boundary was nearly completed. However, several practical challenges associated with high-pressure/high-temperature systems and specialized component procurement impacted schedule and prevented initial pump-driven operation and full commissioning within the available resources. This report documents the as-built design, operating capabilities, and instrumentation, and it summarizes key lessons learned related to heater fabrication and testing, first-of-a-kind assembly factors, specialty flange supply constraints, and fill pump corrective actions. Finally, it outlines a phased plan for future commissioning and experimental campaigns, including control and instrumentation shakedown, heater characterization, model calibration, and testing at state points representative of EarthEn’s TES cycle.

25 ENERGY STORAGE↗
DOE OSTI2024

The value of wake steering wind farm flow control in US energy markets

Abstract. Wind farm flow control represents a category of control strategies for achieving wind-plant-level objectives, such as increasing wind plant power production and/or reducing structural loads, by mitigating the impact of wake interactions between wind turbines. Wake steering is a wind farm flow control technology in which specific turbines are misaligned with the wind to deflect their wakes away from downstream turbines, thus increasing overall wind plant power production. In addition to promising results from simulation studies, wake steering has been shown to successfully increase energy production through several recent field trials. However, to better understand the benefits of wind farm flow control strategies such as wake steering, the value of the additional energy to the electrical grid should be evaluated – for example, by considering the price of electricity when the additional energy is produced. In this study, we investigate the potential for wake steering to increase the value of wind plant energy production by combining model predictions of power gains using the FLOw Redirection and Induction in Steady State (FLORIS) engineering wind farm flow control tool with historical electricity price data for 15 existing US wind plants in four different electricity market regions. Specifically, for each wind plant, we use FLORIS to estimate power gains from wake steering for a time series of hourly wind speeds and wind directions spanning the years 2018–2020, obtained from the ERA5 reanalysis dataset. The modeled power gains are then correlated with hourly electricity prices for the nearest transmission node. Through this process we find that wake steering increases annual energy production (AEP) between 0.4 % and 1.7 %, depending on the wind plant, with average increases in potential annual revenue (i.e., annual revenue of production, ARP) 4 % higher than the AEP gains. For most wind plants, ARP gain was found to exceed AEP gain. But the ratio between ARP gain and AEP gain is greater for wind plants in regions with high wind penetration because electricity prices tend to be relatively higher during periods with below-rated wind plant power production, when wake losses occur and wake steering is active; for wind plants in the Southwest Power Pool – the region with the highest wind penetration analyzed (31 %) – the increase in ARP from wake steering is 11 % higher than the AEP gain. Consequently, we expect the value of wake steering, and other types of wind farm flow control, to increase as wind penetration continues to grow.

17 WIND ENERGY↗
DOE OSTI2022

Investigation of Multiple Data Streams for Gearbox Bearing Fault Prediction Through Machine-Learning Models

Operations and maintenance (O&M) cost of wind plant accounts up to 30% of total energy cost, which can be reduced through continuous monitoring and successfully detecting incipient wind turbine failures. To accomplish this, condition monitoring and predictive maintenance systems are being implemented in wind industry to support O&M decision making. A wide range of approaches for condition monitoring and fault prediction have been developed. These approaches generally use historical data of wind turbines collected by Supervisory Control and Data Acquisition (SCADA) system to identify patterns that lead to failure. These SCADA data show the overall condition of a wind turbine and can be leveraged to detect when the turbine's performance is degrading and to identify if a fault is developing. However, it becomes challenging to predict the failure of a specific wind turbine gearbox bearing, because the SCADA data are often not directly linked to the component. To bridge the gap, we have investigated features calculated from SCADA data using physics-based models and the gearbox design over the years. The damaged metric we used in the physics domain is frictional energy. Combining these physics domain variables with SCADA data as inputs to various machine learning models for gearbox bearing fault prediction, we have demonstrated the benefits of leveraging both physics and data domain models. It was an attempt to improve frictional-energy-based damage metric by adding data domain inputs, as we had learned that the frictional-energy-based damage metric alone is not sufficient to single out failed bearings from healthy. As condition monitoring data (either vibration or oil debris data) has become available at more and more wind plants, we would like to evaluate whether by adding the condition monitoring data can help further improve the performance of frictional-energy-based damage metric for gearbox bearing fault prediction. Both cases by modeling through various machine learning algorithms are discussed in this study along with some observations.

fault prediction↗
DOE OSTI2023

Exploring the Impact of Near-Term Innovations on the Technical Potential of Land-Based Wind Energy

Land based wind may play a critical role in reaching emissions reductions goals and high renewable contribution scenarios with capacity expansion modeling results estimating over 1 terawatt of land-based wind by 2035 to reach 100% clean electricity. Deployment of land-based wind at this magnitude may require significant investments in transmission infrastructure and will require significant land area for new wind and transmission. Cost reductions via technological advancements in wind turbine design, construction, and maintenance will have a major role in enabling the scale of deployment required. Since 1998, the levelized cost of wind energy has fallen by over 60% due to improvements in capacity factors, advancements in turbine controls, and cost reductions in installation, operation, and maintenance. These cost reduction pathways, generally referred to as wind technology "innovations", have enabled significant increases in the capacity and electric generation share of wind power in the United States. Nevertheless, achievements of past wind innovations have not led to widespread wind deployment outside of high wind speed geographies. This study evaluates the potential of near-term innovations to expand the geographic range of economically viable land-based wind power production in the United States. Many challenges to future deployment of wind power can be associated with increasing concentration in high-wind areas. As more wind power is deployed in these same areas, it is likely that residential and regulatory resistance to further deployment will increase, access to transmission will diminish, and options for distant companies and governments with renewable energy goals will remain limited. Therefore, this analysis aims to emphasize the potential for innovations to enable land-based wind in regions with limited wind deployment and with lower wind resource and better access to transmission.

17 WIND ENERGY↗
DOE OSTI2024

Front End Engineering Design Study on Gasification of Coal and Biomass to Generate Carbon- Free Electric Power and Hydrogen

A 2nd Phase Front End Engineering Design study of a gasification plant concept to co-produce electric power and hydrogen with net-negative CO2 emissions is being completed under the U.S. Department of Energy’s (DOE’s) 21st Century Power Plants initiative, whose goal is to advance innovative power plant concepts that are capable of flexible, net-zero carbon emission operations while producing cost-effective hydrogen to support economy-wide decarbonization goals. The proposed standalone plant would be constructed in Nebraska, USA. The specified design feedstock is a hybrid blend of Powder River Basin (PRB) subbituminous coal from Wyoming and local Nebraska biomass (corn stover), 50% each by weight (dry basis). Other potential feedstocks, including woody biomass (eastern red cedar) and waste plastic (auto shredder residue) were evaluated as alternates. The process block comprises a high-pressure, oxygen-blown fluidized bed gasifier coupled with water-gas shift, Selexol process for acid gas (H2S and CO2) removal, and pressure-swing adsorption (PSA) to yield 8,500 kg/h of high-purity hydrogen. Off-gas from the PSA unit is used in a gas turbine combined cycle plant (the power block) to supply 50 MWe net electric power to the grid. Overall thermal efficiency of the plant is 50% (HHV) with net atmospheric CO2 removal at a rate of 32 t/h. Design activities necessary to provide input to the current front-end engineering design (FEED) study, including, site selection, gasifier technology selection, investment case preparation, and the development of the Environmental Information Volume (EIV) for the host site, have been completed. These, as well as the current FEED activities, are described in this presentation.

gasification, biomass, coal, hydrogen, power gener↗
DOE OSTI2022

Flutter behavior of highly flexible blades for two- and three-bladed wind turbines

Abstract. With the progression of novel design, material, and manufacturing technologies, the wind energy industry has successfully produced larger and larger wind turbine rotor blades while driving down the levelized cost of energy (LCOE). Though the benefits of larger turbine blades are appealing, larger blades are prone to aeroelastic instabilities due to their long, slender, highly flexible nature, and this effect is accentuated as rotors further grow in size. In addition to the trend of larger rotors, non-traditional rotor concepts are emerging including two-bladed rotors and downwind configurations. In this work, we introduce a comprehensive evaluation of flutter behavior including classical flutter, edgewise vibration, and flutter mode characteristics for two-bladed, downwind rotors. Flutter speed trends and characteristics for a series of both two- and three-bladed rotors are analyzed and compared in order to illustrate the flutter behavior of two-bladed rotors relative to more well-known flutter characteristics of three-bladed rotors. In addition, we examine the important problem of blade design to mitigate flutter and present a solution to mitigate flutter in the structural design process. A study is carried out evaluating the effect of leading edge and trailing edge reinforcement on flutter speed and hence demonstrates the ability to increase the flutter speed and satisfy structural design requirements (such as fatigue) while maintaining or even reducing blade mass.

Chetan, Mayank (ORCID:0000000241978801)↗
DOE OSTI2025

Computational materials reliability assessment of hydrogen fueled gas turbine power generation engines

The use of blended fuel sources in land based gas turbine engines drives variations in the resulting operational profile (temperatures and pressures) which can impact engine reliability. Furthermore, variability in the manufacture of components affects the resulting microstructure which directly impacts material performance and reliability. Currently, data-driven models are typically used for maintaining and inspecting fleets of engines. Without explicitly capturing material and operational sources of variability conservatism must be used in developing component-level reliability models. Therefore, there exists an opportunity to use information from materials-scale physics models to better inform reliability modeling and reduce conservatism; the impact is more cost-efficient operation and maintenance of current and future fleets. Specifically, this work establishes a computational framework for evaluating the probabilistic high temperature creep performance of hot-section Ni-based superalloys where uncertainty comes from both microstructural and operational variability. A novel high-fidelity physics model which phenomenologically captures grain-boundary sensitive phenomena has been established. A probabilistic calibration procedure was used to calibrate the model and capture uncertainty in the parameterized model coefficients. A design of experiments methodology was established for identifying informative microstructural digital representations for suitable for forward model evaluation. Results show that training a machine-learning surrogate using this design criteria outperforms random selection of microstructural representations. Finally, two surrogate models were developed: (1) a deterministic surrogate model which predicts the local field response given microstructure, constitutive model parameters, and operating conditions (stress, temperature) and (2) a probabilistic model, where uncertainty comes from constitutive law uncertainty, built using denoising diffusion probabilistic models which samples responses given (1) microstructure and (2) operating conditions. These surrogate models enable partner Siemens Energy to rapidly perform UQ analysis specific to creep deformation across a range of microstructures and operating conditions. The impact is that these ML and physics codes can be used to establish more advanced reliability models for the inspection, servicing, and maintenance of land based gas turbine engines.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Evaluating the tidal energy resource for smooth power output and grid integration in the United States

In comparison to wind and solar energy, tidal resources are predictable with a high degree of certainty. Although tides are inherently variable, their periodicity and predictability create the possibility of providing smooth power output to the grid. By spatially diversifying tidal devices to capture the tidal wave as it propagates through a system, aggregate power becomes smoother. Tidal energy assessments have indicated that energy extraction is viable in several regions around the world, leading to the development and testing of many devices. However, less attention has been given to the interface between energy production and grid integration, particularly in the United States. We evaluate tidal phases for several regions across the United States to determine if there is enough diversity within relatively close distances of one another. By calculating the cross correlations of estimated tidal current velocity time series between representative locations in defined regions, we show three regions in the United States that have the potential to aggregate power output from geographically diversified turbines to generate a smoother, baseload-like power profile.

Preziuso, Danielle C.↗