SEARCH · Search NASA

Results for “rig and engine 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.

SourceResearch connectionFrom yearThrough year

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

At least 19 records

All sources NASA NTRS DOE OSTI

DOE OSTI2022

Ultra-High Temperature Thermal Barrier Coating Development and Validation

The most effective method to improve industrial gas turbine power is to increase firing temperature. To maintain component durability at these higher temperatures, thermal barrier coatings (TBC’s) are playing an increasing role in protecting turbine hardware. TBC’s have been successfully used on Solar Turbines’ combustor liners and turbine airfoils, but there is a need for TBC’s that can operate at higher temperatures. Based on recent, favorable rig testing experience, Solar recognized that yttrium aluminum garnet (YAG) TBC’s made by the Solution Precursor Plasma Spray Process (SPPS) has great potential for higher turbine temperatures. This testing verified the thermal cycle durability of the SPPS YAG TBC’s, as well as demonstrated that the temperature drop through the SPPS YAG TBC was twice that measured across a companion APS YSZ TBC. The SPPS YAG TBC with the potential for a 200°C improvement in temperature capability represents a materials breakthrough. The SPPS process also produces a number of unique microstructural features that confer superior properties. SPPC TBC’s have ultra-fine splats that increase toughness and erosion resistance, and the process can be tailored to produce through-thickness cracks for strain-tolerance and control porosity for lower thermal conductivity and increase coating abradability. This proposal would include further development of SPPS YAG density-graded coatings, optimization of the application process, and validation of higher temperature capability and durability through rig and engine testing of coated combustion liners and turbine outer air seals. The technology would be advanced from a TRL 3 to a proposed TRL 6 by overcoming processing concerns on efficiency, application distance and optimization of a graded coating without impacting coating durability by demonstrating the coating performance on components in rig and development gas turbine engine testing.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Development of Ionic Liquid-Additized, GF-5/6 Compatible Low-Viscosity Oils for Automotive Engine and Rear Axle Lubrication for 4% Improved Fuel Economy

This joint project among ORNL, GM, and DRO successfully developed ionic liquid-additized low viscosity lubricants, SAE 0W-12 and 70W-80, for both IC engine and rear axle lubrication, respectively, and demonstrated combined vehicle fuel economy improvement (FEI). Phosphonium-alkylphosphate ILs have been found to be the most effective among the candidates in protecting surface damage from both sliding wear and rolling contact fatigue, and optimal IL concentrations have been determined. The IL’s impact on three-way catalyst seems to be significantly less adverse than the conventional ZDDP. Oil formulations were optimized for both energy efficiency and wear protection. Tribological bench testing of the IL-additized low-viscosity oils showed at least 40% lower boundary friction, more than 60% lower elastohydrodynamic friction, and greater than 50% less wear compared with commercial baselines. IL-additized lubricants have demonstrated FEI by 9.9% in engine dynamometer tests under extreme conditions and 6.9% increased power output in gear rig tests. Prototype IL-additized engine oil and rear axle fluid exhibited combined FEI of 1.39% and 3.24% benchmarked against the state-of-the-art baselines in vehicle testing of fresh oils under the Federal Test Procedure (FTP) city cycle and Highway Fuel Economy Driving Schedule (HWFET), respectively. Used oil analysis suggested that the IL-additized low-viscosity oils produced less wear than the commercial baselines. The gained fundamental understanding and demonstrated FEI in this work pave the way for future development and implementation of the ionic liquid technology.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Development of Hydrogen Burner for FT4000® Aeroderivative Engine - Final Report

This report details an effort to develop a retrofittable fuel/air injector for the FT4000® aeroderivative gas turbine that enables use of hydrogen as a carbon-free fuel for efficient power generation. The FT4000 engine’s low-NOx combustor was developed by Pratt & Whitney and RTX Technology Research Center with core technology from the Pratt & Whitney PW4000 turbofan aircraft engine. The current FT4000 production engine operates on either natural gas or No. 2 fuel oil with water injection to achieve high thermal efficiency and low emissions. This engine is fielded by Mitsubishi Power Aero and delivers 70 MW of power with a simple-cycle efficiency of over 41% when operating with wet compression. The work reported here advances the technology readiness level of the FT4000 combustor for operation with hydrogen, starting with an experimental assessment of the current production hardware with increasing hydrogen content mixed with natural gas and ending with improved nozzle concepts for fully robust operation with 100% hydrogen. High-pressure single-sector combustor rig tests have been completed, demonstrating the ability for the dual fuel nozzle to operate an FT4000 combustor on 100% hydrogen with low nitrogen oxide (NOx) emissions. Metal temperature measurements and video images of the flame structure from zero to 100% hydrogen highlight opportunities to improve the fuel nozzle robustness for high hydrogen conditions. The design of new fuel/air mixer concepts to improve durability and operability with high hydrogen levels was also completed. A total of eleven new concepts were developed and analyzed, ranging from modifications to the bill-of-materials nozzle to fully clean sheet designs. The concepts were evaluated with non-reacting and reacting flow evaluations to assess the performance of the new hardware designs. Non-reacting tests included Phase Doppler Particle Analysis (PDPA) for droplet size and velocity, mechanical patternation for liquid water flux, and planar laser induced fluorescence (PLIF) with acetone-seeding for gaseous fuel/air mixing characterization. Five scaled candidate fuel nozzle designs, in addition to a scaled bill-of-materials nozzle, were then successfully evaluated in an atmospheric pressure burner rig. The nozzles were evaluated for performance with natural gas, hydrogen/natural gas blends, and pure hydrogen. For 100% hydrogen, the nozzles were evaluated with and without water injection. Optical and infrared imaging of the flame and fuel nozzle was captured. NOx emissions were sampled from fixed emissions probes. The results show measurable differences between the various designs, and the data was used to down-select the two most promising designs to advance to future full pressure rig testing. Results from this study have cleared the current production FT4000 engines with dual fuel nozzles to operate at baseload power on blends of hydrogen mixed with natural gas and water. Two promising nozzle designs have been developed to enable fully robust operation with up to 100% hydrogen. These nozzles require validation at full baseload operating conditions before they can be introduced to the field.

03 NATURAL GAS↗

DOE OSTI2022

INVESTIGATION OF TURBULENT JETS, SPRAYS, AND SUPERCRITICAL MIXING BY TIME RESOLVED RAINBOW SCHLIEREN DEFLECTOMETRY

As technological advancements have enabled higher efficiency compression ignition (CI) engines (diesel engines) by operating at higher pressures and temperatures, the mechanisms of fuel-air mixing are postulated to change. Thus, there is a greater need for experimental data to develop and verify new phenomena. However, the fast time scales and harsh environments associated with CI engines present many experimental difficulties and requires high quality non-intrusive diagnostics to obtain useful data. The diagnostics itself must be validated prior to its implementation in an engine environment. The purpose of this research is to advance rainbow schlieren deflectometry (RSD) to study turbulent fuel sprays including the effects of supercritical mixing in CI engine environments. This objective is met by developing and applying quantitative RSD, for the first time, to three separate aspects of fuel sprays: 1) turbulent mixing, 2) phase boundaries, and 3) non-ideal gas mixing. First, quantitative RSD is demonstrated for turbulent mixing in a canonical helium jet. Rayleigh scattering data in the literature is used to validate the concentration measurements obtained by RSD. The results also provide explanations for phenomena occurring in the helium jet and provide data not yet present in the literature. Second, RSD is applied to high pressure multi-phase fuel sprays and new methodologies are developed to distinguish the liquid region from the vapor region and to quantify the in-between region on a probabilistic basis. Isolating liquid and vapor regions generally requires two separate diagnostics, e.g., Mie scattering (liquid region) and Rayleigh scattering (vapor region). However, the results of this study demonstrate that RSD can be used as a single diagnostic to measure both liquid and vapor boundaries. Third, the optical-to-thermodynamic relations associated with refrac-tometry are investigated under non-ideal gas mixing conditions to develop a generalized relationship valid for both ideal or non-ideal gas mixing. The last part of this research develops the theoretical tools to understand and experimentally realize supercritical mixing at diesel conditions. Guided by the theoretical analysis, RSD is applied to compare supercritical versus transcritical mixing at CI conditions using a constant pressure test rig. It is found that while fully supercritical mixing ers benefits in diesel engines, i.e, faster mixing times (50% higher velocities), the absence of droplets which cause high levels of particulate emissions, etc., it would be difficult to achieve in practice because of the requirements of fuels with low critical temperature and/or substantial fuel preheating.

02 PETROLEUM↗

DOE OSTI2021

Real-time Data Analytics for Condition Monitoring of Complex Industrial Systems

Modern industrial systems are now fitted with several sensors for condition monitoring. This is advantageous because these sensors can provide mass amounts of data that have the potential for aiding in tasks such as fault detection, diagnosis, and prognostics. However, the information valuable for performing these tasks is often clouded in noise and must be mined from high-dimensional data structures. Therefore, this dissertation presents a data analytics framework for performing these condition monitoring tasks using high-dimensional data. Demonstrations of this framework are detailed for challenges related to power generation systems in automobiles, power plants, and aircraft engines. These implementations leverage data collected from state-of-the-art, industry class test-rigs. Results indicate the ability of this framework to develop effective methodologies for condition monitoring of complex systems.

Peters, Benjamin↗

DOE OSTI2022

Evaluation of High-Temperature Martensitic Steels for Heavy-Duty Diesel Piston Applications

Five different commercially available high-temperature martensitic steels were evaluated for use in a heavy-duty diesel engine piston application and compared to existing piston alloys 4140 and microalloyed steel 38MnSiVS5 (MAS). Finite element analyses (FEA) were performed to predict the temperature and stress distributions for severe engine operating conditions of interest, and thus aid in the selection of the candidate steels. Complementary material testing was conducted to evaluate the properties relevant to the material performance in a piston. The elevated temperature strength, strength evolution during thermal aging, and thermal property data were used as inputs into the FEA piston models. Additionally, the long-term oxidation performance was assessed relative to the predicted maximum operating temperature for each material using coupon samples in a controlled-atmosphere cyclic-oxidation test rig. A current commercial steel piston alloy, quenched and tempered martensitic steel 4140, was tested in a single-cylinder research engine for a baseline oxidation and mechanical performance assessment using an abbreviated (50h) durability test plan. The predicted suitability of a candidate piston material in an engine is primarily based on its elevated temperature strength, oxidation resistance, and the complex influence of thermal conductivity, the latter of which is substantially lower for the candidate materials considered in this research relative to the traditional alloys. Although the lower thermal conductivity causes the candidate alloys to operate in higher temperature ranges under identical engine operating conditions and piston geometries, increasing the likelihood of partially or completely negating their strength and oxidation resistance advantages relative to 4140 and MAS steels, this evaluation indicates that several of the candidate piston alloys are predicted to enable improved oxidation resistance under more severe engine operating conditions relative to the current piston materials. However, further evaluation is required to determine if the elevated temperature fatigue strength and durability of these alloys are suitable for more severe engine conditions.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Heat Transfer Experiments of Ribbed, Serpentine Cooling Passages with Supercritical CO2

The results of heat transfer experiments with supercritical CO2 (sCO2) to capture the performance of ribbed, serpentine cooling passages for Reynolds numbers in the range of 100,000 - 400,000 are presented. The oxy-combustion turbine operating in an Allam-Fetvedt cycle has a turbine inlet temperature exceeding 1100°C, necessitating internally cooled turbine blades due to material creep strength limits. Reynolds numbers for sCO2, with its combination of high fluid density and low viscosity, can be up to an order of magnitude higher than comparable internal cooling conditions for an air-breathing engine where the majority of experimental data exists. To improve the prediction of cooling performance through turbulated passages, a test rig was designed and constructed with interchangeable insert capability for operation in sCO2 with heat transfer from a heater outlet flow stream to a lower temperature recuperator outlet flow stream. The inserts included serpentine passage geometry with five passes, one of the inserts including chevron ribs and the other a plain wall. The multi-pass serpentine geometry allowed for the evaluation of the effects 180 deg. tip turns have on the return passage flow characteristics, as they can depart significantly from fully-developed flow characteristics. The test procedure included the use of a modified Wilson plot method, with hot flow stream conditions kept effectively constant so that monitored changes in the overall thermal resistance could be attributed to manipulations in cooling flow stream conditions. Conditions during testing consisted of test section pressures of approximately 180 bar, cooling flow stream temperature of 175°C and hot flow stream temperature of 410°C. Test points at discrete cool flow Reynolds numbers up to 400,000 demonstrated an expected trend of decreased fluid thermal resistance with increasing Reynolds number, while at comparable Reynolds number there was an exhibited lower thermal resistance and higher passage pressure drop for the ribbed insert compared to the plain-walled insert. Processing of test data included establishment of Nusselt number enhancement ratios, so that for different internal cooling passage dimensions in the actual turbine blade at comparable Reynolds number the ratio could be applied to predict cooling performance.

Marshall, Michael↗

DOE OSTI2021

Novel Temperature Sensors and Wireless Telemetry for Active Condition Monitoring of Advanced Gas Turbines

The objective of the program is to develop and engine test hardware and software technologies that will enable active condition monitoring to be implemented on hot gas path turbine blades in large industrial gas turbines. The specific objectives are (1) to fabricate and install Smart Turbine Blades with thermally sprayed sensors and high temperature wireless telemetry systems in a gas turbine engine, (2) to integrate the component engine test data with remaining useful life (RUL) models and develop an approach for networking the component RUL data with Siemens' Power Diagnostics® engine monitoring system. These significant advances carried out in Phase 1 in temperature wide bandgap telemetry, along with new induced power driver and receiver geometry combined with an innovative approach to transmit digital data wirelessly will enable the opportunity to proceed with more technical innovation. The Phase 2 program focused on validation testing of sensor-wireless telemetry package in spin rig and advanced operation-based assessment (OBA) model utilizing artificial intelligence. Significant efforts were dedicated on the download of the technology onto components to be tested an actual gas turbine engine for full realization of active condition monitoring for Smart Turbine Blades.

03 NATURAL GAS↗

DOE OSTI2026

Novel Modular Heat Engines with sCO 2 Bottoming Cycle Utilizing Advanced Oil-Free Turbomachinery

This report presents the thermal, mechanical, and electric machine design of a 27krpm rotating test rig aimed at reducing technical risks with hermetic oil-free super-critical carbon dioxide (sCO 2 ) turbomachinery. The test rig rotor system is based on a conceptual turbomachine design discussed that evaluates a sCO 2 waste heat recovery (WHR) unit for land-based gas turbines at natural gas (NG) compressor stations. The key novelty of the hermetic sCO 2 turbomachine concept is the utilization of additively manufactured CO 2 gas bearings and a CO 2 -immersed direct-drive permanent magnet (PM) electric machine. The previous effort on conceptual design identified 3 main technical risks, which included thrust bearing load capacity, rotordynamics, and thermal performance of the system. Therefore, key requirements of the test vehicle include the ability to test the rotor system in a 400psi (27.6 bar) hermetic CO 2 operating environment, apply up to 1,500 lbs (6.7 kN) of rotor thrust loads, capability to assess rotordynamics with radial gas bearings, inclusion of instrumentation to assess thrust bearing load capability, and flexibility for varying secondary cooling flows to confirm thermal model predictions. Design topics such as rotordynamics, bearing design, and electric machine design are addressed, while highlighting critical elements. In addition, additive build trials for Inconel 718 radial and thrust bearings were performed to prove the manufacturability of the bearing design concepts. The results of the design efforts yield a test rig concept with ability to operate at 27,000 rpm, apply thrust loads to 1,500 lbs, deliver CO 2 up to 800psi, and modulate cooling flows.

03 NATURAL GAS↗

DOE OSTI2023

COMPUTATIONAL MODELING OF IGNITION AND PREMIXED FLAME PROPAGATION INITIATED BY A PRE-CHAMBER TURBULENT JET

Addressing the pressing need for reduced carbon emissions, Turbulent Jet Ignition (TJI) emerges as a promising technology for ultra-lean combustion, offering enhanced thermal efficiencies and minimized cyclic variability in spark-ignited engines. To facilitate rapid testing and integration of this technology, a robust computational modeling framework is crucial. This study delves into the predictive capabilities of computational models for main-chamber ignition and premixed flame propagation using a single-cycle TJI rig measured by Biswas et al. (Applied Thermal Engineering, vol 106, 2016). Employing an open-source compressible flow simulation solver with Large Eddy Simulation (LES) for turbulence modeling, the investigation integrates the conventional Laminar Finite Rate Chemistry (LFRC) model alongside the transported Probability Density Method (PDF) for turbulence-chemistry interaction. A fully-consistent Eulerian Monte-Carlo Fields (EMCF) method is utilized to approximate the transported PDF, while Interaction by Exchange with Mean is employed to close micro-mixing terms in stochastic differential equations. A reduced chemical reaction mechanism with 21 species and 84 reactions (DRM-19) is used for solving chemical kinetics, and a double Gaussian energy deposition model is used to approximate the spark ignition in the pre-chamber. An unstructured O-grid mesh with 0.3 million cells in the prechamber and 1 million cells in the main chamber is employed. Results are divided into two phases: pre-chamber initialization and full TJI simulations. Validation of the predicted pre-chamber flame propagation and the lean ignition in the main-chamber is carried out by using available experimental data. Under quiescent conditions, both the LFRC and transported PDF methods largely underestimate the flame speed and subsequent pressure growth in the pre-chamber. A linear momentum forcing technique is applied to investigate the impact of initial turbulence in the pre-chamber, demonstrating a notable influence on flame propagation. Fine-tuning of the forcing coefficient reproduces the sudden pressure growth observed in the experiment. The experimentally validated pre-chamber simulation serves as the initial condition for the full TJI simulations. It is found that the LFRC model fails to predict lean-ignition in the main-chamber, resulting in a misfiring event. Incorporation of turbulence-chemistry interaction using the transported PDF method substantially improves the prediction of the ignition event in the main-chamber, achieving fair qualitative agreement and quantitative validation of combustion parameters within ±10% of the reported experimental data. The rich simulation results consisting of a full set of statistical description of the thermo-chemical states enable us to gain deep insights into the ignition mechanisms in the main chamber, which is limited when done experimentally. A novel dual ignition phenomenon is revealed in the TJI rig for the first time. Initially, a primary ignition kernel is formed at a downstream location which eventually detaches from the main jet. As the jet momentum decreases, a secondary ignition event follows, this time at a more upstream location which eventually combines with the primary ignition kernel to form a single connected flame front. Investigation of these ignition sequences in chemical composition space reveal distinct differences between the two. The primary ignition event in the main-chamber is followed by a large concentration of active radicals from the pre-chamber jet, accelerating the chain-branching steps, characterizing what has been referred to as flame ignition. In contrast, the secondary ignition occurs in the absence of active radicals in the pre-chamber jet, hence characterized as jet ignition. Further analysis of the effect of pre-chamber jet characteristics on lean ignition in the main-chamber is conducted by setting up cases with different initial pressure ratios (por) between the two chambers, a non-dimensional parameter, ranging from 1.2 to 3.2. As the initial pressure ratio increases, jet momentum increases, with dual ignition observed in cases above por= 2.2. Case with por= 3.2 lead to misfiring. The effect of ignition sequence on global combustion characteristics of TJI is analyzed. Dual ignition events lead to non-monotonicity in combustion characteristics such as global reaction progress variable, flame penetration, and global heat release rate. In dual ignition events, although the rate of fuel consumption and global heat release rate is initially lower, the secondary ignition leads to a sudden increase in flame surface area, resulting in a sudden jump and promoting the overall performance of the TJI system.

42 ENGINEERING↗

DOE OSTI2026

Mu2e Target Thermal Test Project

The Mu2e experiment requires a production target capable of operating under extreme thermal conditions caused by an 8 GeV proton beam. This project’s objective supports the development of the Mu2e Production Target by testing the Stickman model’s thermal behavior. To test this, Angel Flores Luviano has assisted Jonathan Williams in progressing this project by contributing to the development of a Radiative Cooling Test Fixture (RCTF) that will be used to evaluate the thermal behavior of the new production target model. Engineering calculations were performed to analyze thermal performance and pressure drop within the cold well and water cooling circuit, and determine optimal sizing for key components of the water system. An engineering note was made to document the calculations. CAD models of the water circuit piping, thermocouple mount, and radiator chimney were developed, and prototype test rig components were fabricated using 3D printing. Future work will focus on conti nued RCTF development which includes control system integration, heater hardware design, and interfaces that can be scaled up to increase thermal capacity.

Luviano, Angel Flores [Unlisted]↗

DOE OSTI2024

OPERATION OF FT4000® SINGLE NOZZLE COMBUSTOR WITH HIGH HYDROGEN

This paper reports initial results from an effort to develop a retrofittable fuel/air injector for the FT4000® aeroderivative gas turbine that enables use of hydrogen as a carbon-free fuel for efficient power generation. The FT4000 engine’s low-NOx combustor was developed by Pratt & Whitney and RTX Technology Research Center with core technology from the Pratt & Whitney PW4000 turbofan aircraft engine. The work reported here advances the technology readiness level of the FT4000 combustor for operation with hydrogen, starting with an experimental assessment of the current production hardware with increasing hydrogen content mixed with natural gas. High-pressure single-sector combustor rig tests have been completed, demonstrating the ability for the dual fuel nozzle to operate an FT4000 combustor on 100% hydrogen with low nitrogen oxide (NOx) missions. Metal temperature measurements and video images of the flame structure from zero to 100% hydrogen highlight opportunities to improve the fuel nozzle robustness for high hydrogen conditions. The current FT4000 production engine operates on either natural gas or No. 2 fuel oil with water injection to achieve high thermal efficiency and low emissions. This engine is fielded by Mitsubishi Power Aero and delivers 70 MW of power with a simple-cycle efficiency of over 41% when operating with wet compression. Results from this study have cleared the current production FT4000 engines with dual fuel nozzles to operate at baseload power on blends of hydrogen mixed with natural gas and water.

power generation↗

DOE OSTI2026

Mu2e Production Target Thermal Test Project

The Mu2e experiment requires a production target that is capable of operating under extreme thermal conditions caused by an 8 GeV proton beam. This project’s objective supports the development of the Mu2e Pro- duction Target by testing the Stickman model’s thermal behavior. Angel Flores Luviano has assisted Jonathan Williams in progressing this project by contributing to the development of a Radiative Cooling Test Fixture (RCTF) that will be used to evaluate the thermal behavior of the new production target model. Engineering calculations were performed to an- alyze thermal performance and pressure drop within the cold well and wa- ter cooling circuit. These calculations also determined the optimal sizing for key components of the water system. An engineering note was made to document these calculations. CAD models of the water circuit piping, thermocouple mounting bars, and radiator chimney were developed, and prototype test rig components were fabricated using 3D printing. Future work will focus on continued RCTF development which includes control system integration, heater hardware design, and interfaces that can be scaled up to increase thermal capacity.

Flores Luviano, Angel Augusto [Unlisted, US]↗

DOE OSTI2021

Evaluating the Effects of Transient Purge Flow on Stator-Rotor Seal Performance

Abstract As modern engine designs target higher efficiencies through increased turbine inlet temperatures, critical turbine components are at increased risk of damage from conditions exceeding material melting temperatures. In particular, improperly designed underplatform hardware components are susceptible to damage when hot main gas path flow is ingested into the stator-rotor cavity. While all turbines inherently experience transients during operation, a majority of publicly available turbine studies have been executed using steady operating conditions or inherently transient “blowdown” rigs. For this reason, routine transient events are not well understood. To address this need, the present study utilized a combined experimental and computational approach. The test article is a continuous-duration, one-stage test turbine operating with true-scale engine hardware and seal geometries at engine-representative flow conditions. The nature of the continuous-duration facility uniquely supports the direct assessment of transient events through its ability to transition between steady-state operating conditions. The effects of a transient purge flow were investigated in this study to identify general trends for transient events in a full-scale engine. Results from multiple measurement techniques in the wheelspace region show an interdependence of transient purge flow with a thermal lag of the underplatform hardware. Through experiments conducted at different coolant-to-main gas path temperature ratios, the use of pressure measurements as an indicator of fully purged behavior was introduced, and a thermally driven influence on rim seal performance was quantified. The computational results show good agreement with experimental pressure measurements and provide insight into the physical mechanisms that drive the relationship between pressure and sealing effectiveness measurements observed for the tested geometry.

Engineering↗

DOE OSTI2021

Real-Time Health Monitoring for Gas Turbine Components Using Online Learning and High-Dimensional Data (Final Report)

Capital-intensive turbomachinery, such as gas turbines and combined cycle plants, are constantly being monitored for performance anomalies, faults, and physical degradation. Although these power-generating assets are equipped with hundreds of sensors, existing monitoring tools can only handle moderate-sized data. As a result, only a handful of aggregate metrics are used to monitor machine health. At the same time, developing advanced tools suitable for large datasets have been restricted by the lack of appropriate data. The objective of this proposal was to demonstrate a Big Data analytics framework for fault detection and diagnosis in gas turbine applications. We develop a predictive analytics framework methodology guided by these experimental data, industrial data from our collaborators, and physics-based models with engineering domain knowledge. Our analytics framework consists of four key components: (1) a data curation process that addresses data storage, data quality assessments, and integrity checks, (2) a feature engineering component that utilizes statistical methods and transformation algorithms guided by physics-based models to extract high-fidelity fault features that can be leveraged for fault detection and classifying fault severities, (3) a Machine Learning-based fault detection and diagnostics algorithms for detecting operational and hardware faults in the combustion and the turbines section. We utilize two industry-class gas turbine component test rigs to generate first of its kind data for critical gas turbine faults with varying severity levels. Advanced gas turbine test facilities will be interrogated using state-of-the-art instrumentation techniques to build fault signatures and data trends for key combustor and turbine faults. Data generated from a combustor test rig (Georgia Tech) and a turbine test rig (Penn State) during both normal operation and with seeded faults serve as the basis for the Big Data sets. The test conditions in the two test facilities include common, critical events that occur in the operation. Utilizing the combustor test rig, we examine two common combustor faults: lean blowout and centerbody degradation. For the turbine section we develop analytic models for monitoring cooling faults in the gas turbine.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2021

Real-Time Health Monitoring for Gas Turbine Components Using Online Learning and High-Dimensional Data

Capital-intensive turbomachinery, such as gas turbines and combined cycle plants, are constantly being monitored for performance anomalies, faults, and physical degradation. Although these power-generating assets are equipped with hundreds of sensors, existing monitoring tools can only handle moderate-sized data. As a result, only a handful of aggregate metrics are used to monitor machine health. At the same time, developing advanced tools suitable for large datasets have been restricted by the lack of appropriate data. The objective of this proposal was to demonstrate a Big Data analytics framework for fault detection and diagnosis in gas turbine applications. We develop a predictive analytics framework methodology guided by these experimental data, industrial data from our collaborators, and physics-based models with engineering domain knowledge. Our analytics framework consists of four key components (1) a data curation process that addresses data storage, data quality assessments, and integrity checks, (2) a feature engineering component that utilizes statistical methods and transformation algorithms guided by physics-based models to extract high-fidelity fault features that can be leveraged for fault detection and classifying fault severities, (3) a Machine Learning-based fault detection and diagnostics algorithms for detecting operational and hardware faults in the combustion and the turbines section. We utilize two industry-class gas turbine component test rigs to generate first of its kind data for critical gas turbine faults with varying severity levels. Advanced gas turbine test facilities will be interrogated using state-of-the-art instrumentation techniques to build fault signatures and data trends for key combustor and turbine faults. Data generated from a combustor test rig (Georgia Tech) and a turbine test rig (Penn State) during both normal operation and with seeded faults serve as the basis for the Big Data sets. The test conditions in the two test facilities include common, critical events that occur in the operation. Utilizing the combustor test rig, we examine two common combustor faults: lean blowout and centerbody degradation. For the turbine section we develop analytic models for monitoring cooling faults in the gas turbine

03 NATURAL GAS↗

DOE OSTI2022

Demonstration of Improved CHP Systems utilizing Improved Gas Turbine and sCO2 Cycles Using Additive Manufacturing (AM) Components

This project seeks to integrate a sCO2 bottoming cycle with a 5.3 MW gas turbine to develop a CHP system that is able to transition rapidly between 50% and 100% load by engaging or bypassing the bottoming cycle while maintaining electrical system efficiency above 30% at all times. The project team will engineer an optimized design of the power systems. The needed new key components, such as advanced heat exchangers and a steam injection system for the gas turbine, will be developed and their performance demonstrated in rig tests. The feasibility of the whole integrated CHP system will be validated through a cyber-physical approach.

36 MATERIALS SCIENCE↗

DOE OSTI2020

An Analytical Model of Erosive Wear of BioMass Comminution Components

An analytical erosion model that relates critical process parameters (speed and impingement angle) to critical material attributes of inorganic mineral species in feedstock (density, size, aspect ratio) and substrate (hardness, toughness, and fatigue ductility) was applied to model wear in pretreatment milling operations. Results of the model were compared to experimental measurements of wear produced using the Accelerated Wear Test (AWT) rig at Idaho National Laboratory (INL). Results showed that there is good agreement between predicted and measured performance, and that a quality-by-design (QbD) tool can be developed to predict component reliability based on scientific engineering principles in lieu of trial-and-error approaches.

09 BIOMASS FUELS↗