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At least 343 records · Page 19

Engine cyclic durability by analysis and material testing

The problem of calculating turbine engine component durability is addressed. Nonlinear, finite-element structural analyses, cyclic constitutive behavior models, and an advanced creep-fatigue life prediction method called strainrange partitioning were assessed for their applicability to the solution of durability problems in hot-section components of gas turbine engines. Three different component or subcomponent geometries are examined: a stress concentration in a turbine disk; a louver lip of a half-scale combustor liner; and a squealer tip of a first-stage high-pressure turbine blade. Cyclic structural analyses were performed for all three problems. The computed strain-temperature histories at the critical locations of the combustor linear and turbine blade components were imposed on smooth specimens in uniaxial, strain-controlled, thermomechanical fatigue tests of evaluate the structural and life analysis methods.

Kaufman, A.↗

Engine cyclic durability by analysis and material testing

The problem of calculating turbine engine component durability is addressed. Nonlinear, finite-element structural analyses, cyclic constitutive behavior models, and an advanced creep-fatigue life prediction method called strainrange partitioning were assessed for their applicability to the solution of durability problems in hot-section components of gas turbine engines. Three different component or subcomponent geometries are examined: a stress concentration in a turbine disk; a louver lip of a half-scale combustor linear; and a squealer tip of a first-stage high-pressure turbine blade. Cyclic structural analyses were performed for all three problems. The computed strain-temperature histories at the critical locations of the combustor linear and turbine blade components were imposed on smooth specimens in uniaxial, strain-controlled, thermomechanical fatigue tests of evaluate the structural and life analysis methods.

Kaufman, A.↗

Public Reference Data for Megawatt-Scale Hydrogen Electrolysis - NLR Historical Wind

The U.S. Department of Energy and the National Laboratory of the Rockies (NLR) demonstrate hydrogen electrolysis from variable sources, hydrogen compression and storage, and hydrogen fuel cell power production using megawatt-scale equipment at NLR’s Flatirons Campus as part of the Advanced Research on Integrated Energy Systems (ARIES) initiative. This dataset represents part of that effort and is intended for academic, national laboratory, industrial, and other stakeholders to plan, design, and validate models of megawatt-scale hydrogen technologies and diverse energy infrastructure nationwide. These data provide a baseline for how existing hydrogen electrolysis technologies perform when coupled with various energy technologies. Future datasets will demonstrate how existing hydrogen fuel cell technologies can provide controllable, dispatchable, and variable power output for artificial intelligence (AI) data centers and other variable loads. This dataset entry describes hydrogen production by conducting a statistical analysis of historical wind data over a five-year period (2020-2025) from a single 1.5MW turbine manufactured by General Electric (GE) located at NLR’s Flatirons Campus, to generate an experimental test profile that was deployed on a 1.25-MW proton exchange membrane type MC250 electrolyzer system manufactured by Nel Hydrogen . [1] While the electrolyzer balance-of-plant supports up to 2.5 MW of electrolysis, NLR only has a single 1.25-MW electrolysis stack. The historical wind data provided several metrics, however, the analysis particularly focused on the measured power output by the wind turbine. The power output time series of data for each day was categorized by total energy generation and standard deviation, and the day that represented the highest combination of these two metrics was chosen – December 25th, 2022. This process was then repeated for a moving four-hour window within this day to identify the most statistically variable period. Finally, this four-hour period was scaled by 65% to match the 1.25 MW electrolyzer. The electrolysis system controls hydrogen production by varying DC current applied to the stack, from a maximum of 3000 A to a minimum safe operation of 300 A, or 10%. Because the current – voltage characteristic changes as the stack ages and efficiency degrades, the actual minimum safe operating power changes over time. The historical wind profiles were translated from power (kilowatts) to current (amperes) using a curve fit with calibration data and sent to the electrolyzer power supply at 1 Hz frequency. For more details on the statistical analysis process, see the presentation labeled “ Public Reference Data for Megawatt-Scale Hydrogen Electrolysis” provided with each data entry. These datasets report relevant hydrogen balance-of-plant and system data, all captured at 1 Hz, including hydrogen mass production measured with an Emerson Coriolis flow meter. Each .zip file represents a single wind turbine electrolysis experiment and is formatted as follows: {technology}_{scaling factor}-{electrolyzer ramp rate in amperes/second} For instance, “wind-GE1.5MW_0.65-400.zip” represents the hour-long experiment using historical data from the wind-GE1.5MW turbine, scaled to 65%, with the electrolyzer power supply set to a maximum ramp rate (gain and slew) of 400 A/s. Each .zip folder contains the following files: A .csv file containing raw data An .xlsx file explaining all the fields in the raw data. A .png plot showing the time series of hydrogen production, electrolysis power consumption, and wind power input. A PDF file detailing the historical wind data statistical analysis used to generate the wind profile. An experiment labeled “characterization_200.zip” demonstrates the MC250 electrolyzer steady-state response with 30-minute load steps for a total duration of 5 hours. Finally, a .csv file is provided with all simulated wind experiments combined into one dataset labeled "combined_historical_wind_experiments.csv". NLR also built an AI/machine-learning predictive model based on these datasets. The model ingests the electrolyzer current command in amperes, as well as various pressures and temperatures across the system, and predicts hydrogen output in kilograms per hour. The complete model can be found at https://huggingface.co/NatLabRockies/ptmelt-hydrogen-electrolysis [1] nelhydrogen.com/product/mc-series-electrolyser .

08 HYDROGEN↗

OC6 Phase III: Validation of Wind Turbine Aerodynamic Loading During Surge/Pitch Motion

The objective of Phase III of the Offshore Code Comparison Collaboration, Continued, with Correlation and unCertainty (OC6) project was to validate the accuracy of aerodynamic load predictions by offshore wind modeling tools for a floating offshore wind turbine as it experiences large surge-translational and pitch-rotational motion, as would occur during normal operation. The test data considered were generated at Politecnico di Milano – a wind tunnel with a robotic excitation system to emulate wave loading on the wind turbine. Testing was performed using a scaled version of the DTU 10-MW reference model, and motion was prescribed as harmonic oscillations in the surge and pitch directions, independently. A variety of models were examined in the project, performing a three-way validation between engineering-level tools, higher-fidelity tools, and measurement data from two wind tunnel experimental campaigns. The Load Cases (LC) considered in this testing are as follows: LC 1.X - Steady Wind LC 2.X - Unsteady Wind - Surge Motion LC 3.X - Unsteady Wind - Pitch Motion Details on the results of the OC6 Phase III campaign can be found in the following reference: Bergua R., et al. OC6 project Phase III: validation of the aerodynamic loading on a wind turbine rotor undergoing large motion caused by a floating support structure, Wind Energ. Sci., 8, 465–485, https://doi.org/10.5194/wes-8-465-2023, 2023.

17 WIND ENERGY↗

Oxide-dispersion-strengthened turbine blades. Volume 2

The overall objective of Project 4 was to develop and test a high-temperature, uncooled gas turbine blade using MA6000 alloy. Production scale up of the MA6000 alloy was achieved with a fair degree of tolerance to non-optimum processing. The blade manufacturing process was also optimized. The mechanical, environmental, and physical property evaluations of MA6000 were conducted. The ultimate tensile strength, to about 704 C (1300 F), is higher than DS MAR-M 247 but with a corresponding lower tensile elongation. Also, above 982 C (1800 F) MA6000 tensile strength does not decrease as rapidly as MAR-M 247 because the ODS mechanism still remains active. Based on oxidation resistance and diffusional stability considerations, NiCrAlY coatings are recommended. CoCrAlY coating should be applied on top of a thin NiCrAlY coating if hot corrosion is expected. Vibration, whirlpit, and high-rotor-rig tests were conducted to ensure successful completion of the engine test of the MA6000 TFE731 high pressure turbine blades. Test results were acceptable. In production quantities, the cost of the Project 4 MA6000 blade is estimated to be twice that of a cast DS MAR-M 247 blade.

Millan, P. P., Jr.↗

Upwind vs. downwind: loads and acoustics of a 1.5 MW wind turbine

This paper discusses the motivation, preparation, risk mitigation, execution, and results of a full-scale experiment where the conventional upwind rotor of a 1.5 MW wind turbine was operated in a downwind configuration. The experiment took place at the National Renewable Energy Laboratory Flatirons Campus in Colorado, USA, and involved the collection of loads and power together with acoustic measurements from an array of four microphones. To validate the numerical predictions of the aeroelastic solver OpenFAST in terms of loads and performance, 410 min of downwind operation and 960 min of conventional upwind operations were used. In the wind speed range from 4.5 to 12.5 m s−1, the downwind rotor generates higher damage equivalent loads for the blade root flapwise moment, blade root edgewise moment, and tower-base fore-aft moment compared to the upwind rotor. For these metrics of fatigue loads, numerical predictions match the experimental observations well. OpenFAST is, however, also seen underpredicting a power gain in the downwind rotor. In terms of acoustics, the overall sound pressure levels recorded in the field are similar between the upwind and downwind cases, but downwind operation worsens the metrics describing amplitude modulation.

17 WIND ENERGY↗

Scientific challenges to characterizing the wind resource in the marine atmospheric boundary layer

Abstract. With the increasing level of offshore wind energy investment, it is correspondingly important to be able to accurately characterize the wind resource in terms of energy potential as well as operating conditions affecting wind plant performance, maintenance, and lifespan. Accurate resource assessment at a particular site supports investment decisions. Following construction, accurate wind forecasts are needed to support efficient power markets and integration of wind power with the electrical grid. To optimize the design of wind turbines, it is necessary to accurately describe the environmental characteristics, such as precipitation and waves, that erode turbine surfaces and generate structural loads as a complicated response to the combined impact of shear, atmospheric turbulence, and wave stresses. Despite recent considerable progress both in improvements to numerical weather prediction models and in coupling these models to turbulent flows within wind plants, major challenges remain, especially in the offshore environment. Accurately simulating the interactions among winds, waves, wakes, and their structural interactions with offshore wind turbines requires accounting for spatial (and associated temporal) scales from O(1 m) to O(100 km). Computing capabilities for the foreseeable future will not be able to resolve all of these scales simultaneously, necessitating continuing improvement in subgrid-scale parameterizations within highly nonlinear models. In addition, observations to constrain and validate these models, especially in the rotor-swept area of turbines over the ocean, remains largely absent. Thus, gaining sufficient understanding of the physics of atmospheric flow within and around wind plants remains one of the grand challenges of wind energy, particularly in the offshore environment. This paper provides a review of prominent scientific challenges to characterizing the offshore wind resource using as examples phenomena that occur in the rapidly developing wind energy areas off the United States. Such phenomena include horizontal temperature gradients that lead to strong vertical stratification; consequent features such as low-level jets and internal boundary layers; highly nonstationary conditions, which occur with both extratropical storms (e.g., nor'easters) and tropical storms; air–sea interaction, including deformation of conventional wind profiles by the wave boundary layer; and precipitation with its contributions to leading-edge erosion of wind turbine blades. The paper also describes the current state of modeling and observations in the marine atmospheric boundary layer and provides specific recommendations for filling key current knowledge gaps.

17 WIND ENERGY↗

Optimal Wind Turbine Design for H2 Production

The Optimal Wind Turbine Design for Hydrogen Production work seeks to address the H2@Scale program's goal to "advance affordable hydrogen production" by optimizing the wind turbine design specifically for hydrogen (H2) production. The project identifies optimal wind turbine designs made specifically for hydrogen production to advance affordable green hydrogen production. The project also couples wind turbine, wind plant, solar plant, and electrolyzer models to predict hydrogen production from variable, renewable power sources.

electrolyzer↗

Turbojet-engine Starting and Acceleration

From considerations of safety and reliability in performance of gas-turbine aircraft, it is clear that engine starting and acceleration are of utmost importance. For this reason extensive efforts have been devoted to the investigation of the factors involved in the starting and acceleration of engines. In chapter III it is shown that certain basic combustion requirements must be met before ignition can occur; consequently, the design and operation of an engine must be tailored to provide these basic requirements in the combustion zone of the engine, particularly in the vicinity of the ignition source. It is pointed out in chapter III that ignition by electrical discharges is aided by high pressure, high temperature, low gas velocity and turbulence, gaseous fuel-air mixture, proper mixture strength, and-an optimum spark. duration. The simultaneous achievement of all these requirements in an actual turbojet-engine combustor is obviously impossible, yet any attempt to satisfy as many requirements as possible will result in lower ignition energies, lower-weight ignition systems, and greater reliability. These factors together with size and cost considerations determine the acceptability of the final ignition system. It is further shown in chapter III that the problem of wall quenching affects engine starting. For example, the dimensions of the volume to be burned must be larger than the quenching distance at the lowest pressure and the most adverse fuel-air ratio encountered. This fact affects the design of cross-fire tubes between adjacent combustion chambers in a tubular-combustor turbojet engine. Only two chambers in these engines contain spark plugs; therefore, the flame must propagate through small connecting tubes between the chambers. The quenching studies indicate that if the cross-fire tubes are too narrow the flame will not propagate from one chamber to another. In order to better understand the role of the basic factors in actual engine operation, many investigations have been conducted in single combustors from gas-turbine engines and in full-scale engines in altitude tanks and in flight. The purpose of the present chapter is to discuss the results of such studies and, where possible, to interpret these results qualitatively in terms of the basic requirements reported in chapter III. The discussion parallels the three phases of turbojet engine starting: (1) Ignition of the fuel-air mixture (2) Propagation of flame throughout the combustion zone (3) Acceleration of the engine to operating speed.

Mc Cafferty, R. J.↗

Modified Adaptive Control for Region 3 Operation in the Presence of Wind Turbine Structural Modes

Many challenges exist for the operation of wind turbines in an efficient manner that is reliable and avoids component fatigue and failure. Turbines operate in highly turbulent environments resulting in aerodynamic loads that can easily excite turbine structural modes, possibly causing component fatigue and failure. Wind turbine manufacturers are highly motivated to reduce component fatigue and failure that can lead to loss of revenue due to turbine down time and maintenance costs. The trend in wind turbine design is toward larger, more flexible turbines that are ideally suited to adaptive control methods due to the complexity and expense required to create accurate models of their dynamic characteristics. In this paper, we design an adaptive collective pitch controller for a high-fidelity simulation of a utility-scale, variable-speed horizontal axis wind turbine operating in Region 3. The objective of the adaptive pitch controller is to regulate generator speed, accommodate wind gusts, and reduce the excitation of structural modes in the wind turbine. The control objective is accomplished by collectively pitching the turbine blades. The adaptive collective pitch controller for Region 3 was compared in simulations with a baseline classical Proportional Integrator (PI) collective pitch controller. The adaptive controller will demonstrate the ability to regulate generator speed in Region 3, while accommodating gusts, and reducing the excitation of certain structural modes in the wind turbine.

Frost, Susan Alane↗

Observations of marine animal interactions with a small tidal turbine

The risk of collisions between animals and operating tidal turbines remains a concern in the scientific and regulatory communities. A sensor package including optical cameras was deployed to monitor animal interactions with a small-scale (1 m 2 ) cross-flow tidal turbine. The turbine was deployed in Washington State, USA for 141 days at a site with peak flow speeds of 2.5 m/s. We analyze optical camera imagery spanning 109 days of turbine operation. The analyzed images contain 1044 observations of fish, fish schools, seabirds, or seals in the vicinity of the turbine. No instances of collision with seabirds or seals were observed. Seabirds were only observed during daylight hours and while the turbine was stationary. Both seals and fish were observed during both day and night and while the turbine was stationary and rotating. Four fish were observed colliding with the moving turbine and in all but one case the animals swam away following the collision. Over the same period of time, over fifty times more fish (224 individual fish and 5 fish schools) were observed passing the moving turbine without collision. Fish encounters were likely under counted due to the difficulty in discerning small fish from plant matter in the water column. These observations represent the first optical camera imagery showing fish, bird, and marine mammal interactions with a tidal turbine in North America. In addition to quantitative and qualitative discussion of the implications of our observations for collision risk, we discuss lessons learned on sampling schemes and deployment of machine learning for detection of animals to inform future data collection strategies in future monitoring campaigns.

16 TIDAL AND WAVE POWER↗

Hybrid Ceramic-CMC Vane with EBC for Future Coal Derived Syngas Fired 65% Efficient Turbine Combined Cycle

The efficiency of both simple cycle and combined cycle power generation systems scale with the peak temperature at which the gas exits the combustor to drive the turbine. In conventional systems, a substantial fraction of the total turbine core flow exiting the compressor is diverted downstream to cool metallic turbine hardware rather than power the turbine, much of which is used to cool the first-stage turbine vane. The use of coal derived syngas fuels provides an additional challenge to the lifetime of materials utilized in the turbine, as particulate byproducts created in the coal gasification process melt in the combustion gas, and can subsequently deposit and interact with the turbine hardware. The development of durable hot-section materials capable of operating at temperature well above that of single crystal superalloy airfoil/zirconia based thermal barrier coatings is critical to realizing 65% efficient coal derived syngas fired gas turbine based power systems. To enable higher turbine inlet temperatures while lowering cooling air requirements, United Technologies Research Center (UTRC), the central R&D laboratory supporting UT Pratt & Whitney, led the conceptual design of a new type of ceramic composite turbine hot section materials system. The design focused on a novel hybrid monolithic ceramic-fiber reinforced ceramic matrix composite (CMC) first stage turbine vane having an environmental barrier coating. By utilizing ceramic construction in the turbine hot-section, the core flow normally used to cool metallic components will be substantially reduced, increasing efficiency and reducing emissions. To provide the framework for future demonstration testing, UTRC partnered with University of North Dakota Energy and Environmental Research Center (UNDEERC) to provide a conceptual design for a gasified coal fed high-pressure turbine combustor system designed to mimic the conditions expected in a future 65% fuel to busbar efficient syngas fueled gas turbine based combined cycle. The UNDEERC and UTRC collaborated on characterizing dusts from coal gasifier filtration systems.

10 SYNTHETIC FUELS↗

Detailed measurements in the SSME high pressure fuel turbine with smooth rotor blades

Several tests of the Rocketdyne configuration of the Space Shuttle Main Engine (SSME) High Pressure Fuel Turbopump (HPFTP) Turbine have been completed in the Turbine Test Equipment (TTE) at Marshall Space Flight Center. The tests involved using scaled performance parameters and model measurements to predict the performance of the turbine. The overall performance has been the primary objective of the tests to date, but more detailed measurements are also of interest. During the most recent test of the Rocketdyne configuration of the HPFTP turbine with smooth rotor blades, several different measurement techniques were used to study the turbine inlet and exit velocity profiles, boundary layer thicknesses, turbulence intensities, etc. Data has been obtained using various hot film probes and three-hole cobra probes. Laser Velocimeter measurements were also made. The test plan and test data will be presented and discussed as well as lessons learned on how to obtain the various types of data.

Hudson, Susan T.↗

Correlating Time-Resolved Pressure Measurements With Rim Sealing Effectiveness for Real-Time Turbine Health Monitoring

Purge flow is bled from the upstream compressor and supplied to the under-platform region to prevent hot main gas path ingress that damages vulnerable under-platform hardware components. A majority of turbine rim seal research has sought to identify methods of improving sealing technologies and understanding the physical mechanisms that drive ingress. While these studies directly support the design and analysis of advanced rim seal geometries and purge flow systems, the studies are limited in their applicability to real-time monitoring required for condition-based operation and maintenance. As operational hours increase for in-service engines, this lack of rim seal performance feedback results in progressive degradation of sealing effectiveness, thereby leading to reduced hardware life. To address this need for rim seal performance monitoring, this study utilizes measurements from a one-stage turbine research facility operating with true-scale engine hardware at engine-relevant conditions. Time-resolved pressure measurements collected from the rim seal region are regressed with sealing effectiveness through the use of common machine learning techniques to provide real-time feedback of sealing effectiveness. Two modeling approaches are presented that use a single sensor to predict sealing effectiveness accurately over a range of two turbine operating conditions. Here, the results show that an initial purely data-driven model can be further improved using domain knowledge of relevant turbine operations, which yields sealing effectiveness predictions within 3% of measured values.

42 ENGINEERING↗

Correlating Time-Resolved Pressure Measurements With Rim Sealing Effectiveness for Real-Time Turbine Health Monitoring

Purge flow is bled from the upstream compressor and supplied to the under-platform region to prevent hot main gas path ingress that damages vulnerable under-platform hardware components. A majority of turbine rim seal research has sought to identify methods of improving sealing technologies and understanding the physical mechanisms that drive ingress. While these studies directly support the design and analysis of advanced rim seal geometries and purge flow systems, the studies are limited in their applicability to real-time monitoring required for condition-based operation and maintenance. As operational hours increase for in-service engines, this lack of rim seal performance feedback results in progressive degradation of sealing effectiveness, thereby leading to reduced hardware life. To address this need for rim seal performance monitoring, the present study utilizes measurements from a one-stage turbine research facility operating with true-scale engine hardware at engine-relevant conditions. Time-resolved pressure measurements collected from the rim seal region are regressed with sealing effectiveness through the use of common machine learning techniques to provide real-time feedback of sealing effectiveness. Two modelling approaches are presented that use a single sensor to predict sealing effectiveness accurately over a range of two turbine operating conditions. Results show that an initial purely data-driven model can be further improved using domain knowledge of relevant turbine operations, which yields sealing effectiveness predictions within three percent of measured values.

Compressors↗