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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

Estimating Helicopter Noise Abatement Information with Machine Learning

Machine learning techniques are applied to the NASA Langley Research Center's expansive database of helicopter noise measurements containing over 1500 steady flight conditions for ten different helicopters. These techniques are then used to develop models capable of predicting the operating conditions under which significant Blade-Vortex Interaction noise will be generated for any conventional helicopter. A measure for quantifying the overall ground noise exposure of a particular helicopter operating condition is developed. This measure is then used to classify the measured flight conditions as noisy or not-noisy. These data are then parameterized on a nondimensional basis that defines the main rotor operating condition and are then scaled to remove bias. Several machine learning methods are then applied to these data. The developed models show good accuracy in identifying the noisy operating region for helicopters not included in the training data set. Noisy regions are accurately identified for a variety of different helicopters. One of these models is applied to estimate changes in the noisy operating region as vehicle drag and ambient atmospheric conditions are varied.

Greenwood, Eric↗
NASA NTRS1991

Study and Development of an Air Conditioning System Operating on a Magnetic Heat Pump Cycle

This report describes the design of a laboratory scale demonstration prototype of an air conditioning system operating on a magnetic heat pump cycle. Design parameters were selected through studies performed by a Kennedy Space Center (KSC) System Simulation Computer Model. The heat pump consists of a rotor turning through four magnetic fields that are created by permanent magnets. Gadolinium was selected as the working material for this demonstration prototype. The rotor was designed to be constructed of flat parallel disks of gadolinium with very little space in between. The rotor rotates in an aluminum housing. The laboratory scale demonstration prototype is designed to provide a theoretical Carnot Cycle efficiency of 62 percent and a Coefficient of Performance of 16.55.

Wang, Pao-Lien↗
DOE OSTI2024

Ducted Fuel Injection And Cooled Spray Technologies For Particulate Control In Heavy-duty Diesel Engines (Final Report)

Cooled Spray (CS) and Ducted Fuel Injection (DFI) are in-cylinder technologies for diesel engines that can reduce particulate matter and soot emissions and data has been published showing that these technologies can reduce soot emissions by 75-100% for some engines at some operating conditions. However, little is known about scaling the devices for engine size. Additionally, the performance of either technology over the engine duty cycle has not been explored. This project addresses both of these points through single-cylinder engine investigations. The objectives of this project are to provide details about dimensional scaling of these devices and to demonstrate 75% PM reduction over a range of operating conditions on a single-cylinder engine. Two engines were used for this project: a 125mm bore optically accessible engine at Sandia National Laboratories and a 168mm bore metal engine at Southwest Research Institute. The optical engine was used to study the performance of DFI and CS inserts for a large injector orifice diameter injector that is characteristic of a locomotive engine and to perform scaling studies for DFI. The metal engine was used to perform scaling and alignment studies for CS and to evaluate the technology for both EGR and non-EGR engines over the engine operating map. Modifications were required for both engines to accept the prototype inserts being tested. The optical engine required a new fuel injector, cylinder head and piston so that tests could be run at the pressures and engine speeds required. Additionally, a novel rotating stage was designed for the optical engine to simplify alignment of the modules. The metal engine required a modified cylinder head to accept CS inserts and a modified piston to provide additional space around the fuel injector for the CS inserts. Tests on the optical engine showed that DFI reduces PM emissions for both small injector orifices (0.170mm diameter) and large injector orifices (0.290mm). For high load testing, the DFI modules were not as effective as at low load testing, but it was acknowledged that minimal geometric optimization was performed and more improvements may be possible. Comparing DFI to CS and conventional diesel combustion (CDC), DFI performed better than CS or CDC. The CS geometries used in these studies may not be ideal for that engine and additional modifications likely would improve performance. Tests on the metal engine showed PM reductions as high has 80% at some operating conditions with duty-cycle PM reductions of ~50% for EGR and non-EGR configurations. The CS testing on the metal engine showed that chamfering of the fuel passage inlet either through hydro-erosion or mechanical grinding provided significant improvements in the PM reduction capabilities of the insert. Additionally, alignment sensitivities were explored and the data show that the tolerance to misalignment is approximately 0.05 to 0.1mm for the inserts that were studied here. Air-fuel ratio was shown to be important in the effectiveness of the CS inserts. In several tests, it was shown that the CS inserts are more effective at reducing the PM for high-AFR operating conditions compared to low AFR conditions. In summary, multiple designs were evaluated on both engines. It was found that for the conditions and configurations studied here, a fuel passage diameter of ~2.5mm performed best overall. Significant duty-cycle PM reductions are possible using these technologies and sensitivities to AFR, alignment fuel passage diameter and inlet fuel passage shaping were explored and are reported here. More PM reduction may be possible with improved geometric design and attention to alignment practices.

02 PETROLEUM↗
NASA NTRS2018

Aeromechanics Analysis of a Distortion-Tolerant Fan with Boundary Layer Ingestion

A propulsion system with Boundary Layer Ingestion (BLI) has the potential to significantly reduce aircraft engine fuel burn. But a critical challenge is to design a fan that can operate continuously with a persistent BLI distortion without aeromechanical failure -- flutter or high cycle fatigue due to forced response. High-fidelity computational aeromechanics analysis can be very valuable to support the design of a fan that has satisfactory aeromechanic characteristics and good aerodynamic performance and operability. Detailed aeromechanics analyses together with careful monitoring of the test article is necessary to avoid unexpected problems or failures during testing. In the present work, an aeromechanics analysis based on a three-dimensional, time-accurate, Reynolds-averaged Navier-Stokes computational fluid dynamics code is used to study the performance and aeromechanical characteristics of the fan in both circumferentially-uniform and circumferentially-varying distorted flows. Pre-test aeromechanics analyses are used to prepare for the wind tunnel test and comparisons are made with measured blade vibration data after the test. The analysis shows that the fan has low levels of aerodynamic damping at various operating conditions examined. In the test, the fan remained free of flutter except at one near-stall operating condition. Analysis could not be performed at this low mass flow rate operating condition since it fell beyond the limit of numerical stability of the analysis code. The measured resonant forced response at a specific low-response crossing indicated that the analysis under-predicted this response and work is in progress to understand possible sources of differences and to analyze other larger resonant responses. Follow-on work is also planned with a coupled inlet-fan aeromechanics analysis that will more accurately represent the interactions between the fan and BLI distortion.

Propulsion Aeroelasticity↗
NASA NTRS2019

Analysis of the Honeywell Uncertified Research Engine (HURE) with Ice Crystal Cloud Ingestion at Simulated Altitudes

The Honeywell Uncertified Research Engine (HURE), a research version of a turbofan engine that never entered production, was tested in the NASA Propulsion System Laboratory (PSL), an altitude test facility at the NASA Glenn Research Center. The PSL is a facility that is equipped with water spray bars capable of producing an ice cloud consisting of ice particles, having a controlled particle diameter and concentration in the air flow. To develop the test matrix of the HURE, numerical analysis of flow and ice particle thermodynamics was performed on the compression system of the turbofan engine to predict operating conditions that could potentially result in a risk of ice accretion due to ice crystal ingestion. The goal of the test matrix was to have ice accrete in two regions of the compression system: region one, which consists of the fan-stator through the inlet guide vane (IGV), and region two which is the first stator within the high pressure compressor. The predictive analyses were performed with the mean line compressor flow modeling code (COMDES-MELT) which includes an ice particle model. The HURE engine was tested in PSL with the ice cloud over the range of operating conditions of altitude, ambient temperature, simulated flight Mach number, and fan speed with guidance from the analytical predictions. The engine was fitted with video cameras at strategic locations within the engine compression system flow path where ice was predicted to accrete, in order to visually confirm ice accretion when it occurred. In addition, traditional compressor instrumentation such as total pressure and temperature probes, static pressure taps, and metal temperature thermocouples were installed in targeted areas where the risk of ice accretion was expected. The current research focuses on the analysis of the data that was obtained after testing the HURE engine in PSL with ice crystal ingestion. The computational method (COMDES-MELT) was enhanced by computing key parameters through the fan- stator at multiple span wise locations, in order to increase the fidelity with the current mean-line method. The Icing Wedge static wet bulb temperature thresholds were applicable for determining the risk of ice accretion in the fan-stator, which is thought to be an adiabatic region. At some operating conditions near the splitter-lip region, other sources of heat (non-adiabatic walls) were suspected to be the cause of accretion, and the Icing Wedge was not applicable to predict accretion at that location. A simple order-of-magnitude heat transfer model was implemented into the COMDES-MELT code to estimate the wall temperature minimum and maximum thresholds that support ice accretion, as observed by video confirmation. The results from this model spanned the range of wall temperatures measured on a previous engine that experienced ice accretion at certain operating conditions.

Veres, Joseph P.↗
NASA NTRS2019

Analysis of the Honeywell Uncertified Research Engine (HURE) with Ice Crystal Cloud Ingestion at Simulated Altitudes

The Honeywell Uncertified Research Engine (HURE), a research version of a turbofan engine that never entered production, was tested in the NASA Propulsion System Laboratory (PSL), an altitude test facility at the NASA Glenn Research Center. The PSL is a facility that is equipped with water spray bars capable of producing an ice cloud consisting of ice particles, having a controlled particle diameter and concentration in the air flow. To develop the test matrix of the HURE, numerical analysis of flow and ice particle thermodynamics was performed on the compression system of the turbofan engine to predict operating conditions that could potentially result in a risk of ice accretion due to ice crystal ingestion. The goal of the test matrix was to have ice accrete in two regions of the compression system: region one, which consists of the fan-stator through the inlet guide vane (IGV), and region two which is the first stator within the high pressure compressor. The predictive analyses were performed with the mean line compressor flow modeling code (COMDES-MELT) which includes an ice particle model. The HURE engine was tested in PSL with the ice cloud over the range of operating conditions of altitude, ambient temperature, simulated flight Mach number, and fan speed with guidance from the analytical predictions. The engine was fitted with video cameras at strategic locations within the engine compression system flow path where ice was predicted to accrete, in order to visually confirm ice accretion when it occurred. In addition, traditional compressor instrumentation such as total pressure and temperature probes, static pressure taps, and metal temperature thermocouples were installed in targeted areas where the risk of ice accretion was expected. The current research focuses on the analysis of the data that was obtained after testing the HURE engine in PSL with ice crystal ingestion. The computational method (COMDES-MELT) was enhanced by computing key parameters through the fan-stator at multiple span wise locations, in order to increase the fidelity with the current mean-line method. The Icing Wedge static wet bulb temperature thresholds were applicable for determining the risk of ice accretion in the fan-stator, which is thought to be an adiabatic region. At some operating conditions near the splitter-lip region, other sources of heat (non-adiabatic walls) were suspected to be the cause of accretion, and the Icing Wedge was not applicable to predict accretion at that location. A simple order-of-magnitude heat transfer model was implemented into the COMDES-MELT code to estimate the wall temperature minimum and maximum thresholds that support ice accretion, as observed by video confirmation. The results from this model spanned the range of wall temperatures measured on a previous engine that experienced ice accretion at certain operating conditions.

Veres, Joseph P.↗
DOE OSTI2023

Computational and Experimental Characterization of the Ligand Environment of a Ni-Oxo Catalyst Supported in the Metal–Organic Framework NU-1000

Heterogeneous catalysts exhibit significant changes in composition due to the influence of operating conditions, and these compositional changes can have dramatic effects on catalytic performance. For traditional bulk metal heterogeneous catalysts, relationships between composition and catalytic operating conditions are well documented. However, the influence of operating conditions on the compositions of single-site heterogeneous catalysts remains largely unresolved. To address this, we report a combined computational and experimental characterization of a Ni oxo catalyst under catalytic hydrogenation conditions. Specifically, pair distribution function (PDF) analysis is combined with ab initio thermodynamic modeling to investigate ligand environments present on a Ni oxo cluster supported in the metal–organic framework NU-1000. Comparisons of the experimentally observed and simulated Ni–O coordination numbers and Ni–O, Ni···Ni, and Ni···Zr distances provide insight into the Ni ligand environment under H 2 (g). These comparisons suggest significant OH and H 2 O content and, further, that different Ni ions within the cluster and/or NU-1000 structure may comprise subtly different numbers of these ligands. Further, the observation of significant H 2 O content under H 2 (g) suggests that the NU-1000 support supplies H 2 O to the cluster. Examples of ligand environments that could lead to the observed PDFs are provided. Furthermore, the combination of simulations and experiments provides new insights into the ligand environment for Ni-NU-1000 catalysts that will be useful for understanding the ligand environments of other single-site Ni catalysts as well.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Selective butene formation in direct ethanol-to-C3+-olefin valorization over Zn-Y/Beta and single-atom alloy composite catalysts using in situ generated hydrogen

The selective production of C3+ olefins from renewable feedstocks, especially via C1 and C2 platform chemicals, is a critical challenge for obtaining economically viable low-carbon middle distillate transportation fuels (i.e., jet and diesel). Here, we report a multifunctional catalyst system composed of Zn-Y/Beta and “single-atom” alloy (SAA) Pt-Cu/Al2O3 which selectively catalyzes ethanol-to-olefins (C3+, ETO) valorization in the absence of cofed hydrogen, forming butenes as the primary olefin products. Beta zeolites containing predominately isolated Zn and Y metal sites catalyze ethanol upgrading steps (588 K, 3.1 kPa ethanol, ambient pressure) regardless of cofed hydrogen partial pressure (0-98.3 kPa H2), forming butadiene as the primary product (60% selectivity at 87% conversion). The Zn-Y/Beta catalyst possesses site-isolated Zn and Y Lewis acid sites (at ~7 wt% Y) and Brønsted acidic Y sites, the latter of which has been previously uncharacterized. A secondary bed of SAA Pt-Cu/Al2O3 selectively hydrogenates butadiene to butene isomers at a consistent reaction temperature using hydrogen generated in situ from ethanol-to-butadiene (ETB) conversion. This unique hydrogenation reactivity at near-stoichiometric hydrogen and butadiene partial pressures is not observed over monometallic Pt or Cu catalysts, highlighting these operating conditions as a critical SAA catalyst application area for conjugated diene selective hydrogenation at high reaction temperatures (>573 K) and low H2/diene ratios (e.g., 1:1). Single-bed steady state selective hydrogenation rates, associated apparent hydrogen and butadiene reaction orders, and DFT calculations of the Horiuti-Polanyi reaction mechanisms indicate that the unique butadiene selective hydrogenation reactivity over SAA Pt-Cu/Al2O3 reflects lower hydrogen scission barriers relative to monometallic Cu surfaces and limited butene binding energies relative to monometallic Pt surfaces. DFT calculations further indicate the preferential desorption of butene isomers over SAA Pt-Cu(111) and Cu(111) surfaces while Pt(111) surface favors subsequent butene hydrogenation reactions to form butane over butene desorption events. Under operating conditions without of hydrogen cofeeding, this combination of Zn-Y/Beta and SAA Pt-Cu catalysts can selectively form butenes (65% butenes, 78% C3+ selectivity at 94% conversion) and avoid butane formation using only in situ generated hydrogen, avoiding costly hydrogen cofeeding requirements that hinder many renewable energy processes.

Cordon, Michael↗
DOE OSTI2020

Highlighting the Impact of Yaw Control by Parsing Atmospheric Conditions Based on Total Variation: Preprint

Identification of atmospheric conditions within a multivariate atmospheric dataset is a necessary step in the validation of wind plant control strategies. Most often, operating conditions are characterized in terms of aggregated observations and assume that the atmosphere is 'quasi-steady'. Aggregation of observations without regard to covariance between time series discounts the dynamical nature of the atmosphere and is not sufficiently representative of wind plant operating conditions. Identification and characterization of continuous time periods with atmospheric conditions that have a high value for analysis or simulation sets the stage for more advanced model validation and the development of real-time control and operation strategies. Controlling observational data for statistical stationarity highlights significant enhancements to the power production of waked turbines under wake steering wind plant control. Considering the combined energy ratio of the turbine to which yaw offsets are prescribed as well as the waked turbine show only moderate improvements when filtering for total validation. The same quality control that highlights wake steering also serves to underpin the off-nominal operation of the controlled turbine.

17 WIND ENERGY↗
DOE OSTI2021

Calibration of the Diffusivity Predictions of Centipede Using Approximate Bayesian Computation and Applications in Nyx (Engineering Scale) and Xolotl-MARMOT (Meso-Scale) Simulations

Fission gas evolution and release in UO 2 nuclear fuel are important fuel performance metrics and occur in several distinct stages: 1) nucleation, growth and resolution of intra-granular bubbles, 2) diffusion to grain boundaries and 3) nucleation and growth of bubbles at grain boundaries, which eventually form a connected network (percolation) enabling release of gas from grain boundaries through connections to triple junctions, grain edges or free surfaces. The NE-SciDAC project is developing several computational tools to model this problem, which are connected in a hierarchical multi-scale framework. The information transfer in the multi-scale framework is a critical step that, in addition to best-estimates, should include uncertainty quantification. Despite taking a first-principles multi-scale approach, there is a need to perform parameter calibration to ensure consistency with available experimental data. In the present study, uncertainty quantification (UQ) and parameter calibration is demonstrated for one of the lower length scale codes in the multi-scale framework (Centipede) and then the results, including instances of the propagated uncertainties, are used in other codes within the framework, specifically Nyx and Xolotl-MARMOT. We calibrated the model parameters in Centipede, a computer code used to predict diffusivities of uranium (U) and xenon (Xe) in the context of the simulation of fission gas in uranium oxide (UO 2 ) nuclear fuel. The Centipede code depends on 183 parameters, all of which are subject to uncertainty. The three data sets used in our calibration effort are taken from the literature. This data is available as a set of measurements, including measurement errors. Our goal is to calibrate a statistical model that predicts both the value of the measurement and the uncertainty associated with the measurement. We perform a Bayesian calibration of the model parameters using a dedicated approximate Bayesian computation (ABC) likelihood function. To avoid excessive computational costs, we replace the expensive Centipede simulation code by a higher-order surrogate model, constructed using only the 9 most important parameters. These important parameters are identified by a preliminary global sensitivity analysis (GSA) study. Among the important parameters are T0 (the temperature at which UO 2 is perfectly stoichiometric) and Hf_pO2 (the temperature dependence of the oxygen (O) partial pressure) that should be considered as operating conditions to be estimated along with the other parameters. We consider two different cases: one where we define one set of these operating conditions for all data sets, and one where we define distinct operating condition parameters for each data set. The Xe diffusivities predicted by the latter case show distinct features that could not be observed in the former. Next, we use the diffusivity predictions by Centipede as input to Nyx, a reduced order fuel performance code focused on gas behavior alone, in order to estimate quantities associated with inter-granular bubble formation at conditions specified by the experiments. Finally, the diffusivities obtained from the calibrated Centipede runs were used in coupled Xolotl-MARMOT simulations of intra- and inter-granular gas evolution. The results are compared to simulations using the baseline diffusivities from Turnbull et al.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2003

Data-Mining Toolset Developed for Determining Turbine Engine Part Life Consumption

The current practice in aerospace turbine engine maintenance is to remove components defined as life-limited parts after a fixed time, on the basis of a predetermined number of flight cycles. Under this schedule-based maintenance practice, the worst-case usage scenario is used to determine the usable life of the component. As shown, this practice often requires removing a part before its useful life is fully consumed, thus leading to higher maintenance cost. To address this issue, the NASA Glenn Research Center, in a collaborative effort with Pratt & Whitney, has developed a generic modular toolset that uses data-mining technology to parameterize life usage models for maintenance purposes. The toolset enables a "condition-based" maintenance approach, where parts are removed on the basis of the cumulative history of the severity of operation they have experienced. The toolset uses data-mining technology to tune life-consumption models on the basis of operating and maintenance histories. The flight operating conditions, represented by measured variables within the engine, are correlated with repair records for the engines, generating a relationship between the operating condition of the part and its service life. As shown, with the condition-based maintenance approach, the lifelimited part is in service until its usable life is fully consumed. This approach will lower maintenance costs while maintaining the safety of the propulsion system. The toolset is a modular program that is easily customizable by users. First, appropriate parametric damage accumulation models, which will be functions of engine variables, must be defined. The tool then optimizes the models to match the historical data by computing an effective-cycle metric that reduces the unexplained variability in component life due to each damage mode by accounting for the variability in operational severity. The damage increment due to operating conditions experienced during each flight is used to compute the effective cycles and ultimately the replacement time. Utilities to handle data problems, such as gaps in the flight data records, are included in the toolset. The tool was demonstrated using the first stage, high-pressure turbine blade of the PW4077 engine (Pratt & Whitney, East Hartford, CT). The damage modes considered were thermomechanical fatigue and oxidation/erosion. Each PW4077 engine contains 82 first-stage, high-pressure turbine blades, and data from a fleet of engines were used to tune the life-consumption models. The models took into account not only measured variables within the engine, but also unmeasured variables such as engine health parameters that are affected by degradation of the engine due to aging. The tool proved effective at predicting the average number of blades scrapped over time due to each damage mode, per engine, given the operating history of the engine. The customizable tools are available to interested parties within the aerospace community.

Litt, Jonathan S.↗
DOE OSTI2024

Identifying Potential Sub-Synchronous Oscillations Using Impedance Scan Approach: Preprint

This paper presents an impedance scan study on the real-world power system in Australia that has observed 17 to 20 Hz intermittent subsynchronous oscillations. Through the impedance scan of each of the IBRs, both individually and collectively, potential resonance modes are identified. The impedance scans were carried out using electromagnetic transient PSCAD models of the network. The network comprises of site-specific, black-boxed models of IBRs supplied by the generators. The impedance scan approach was divided in three major steps: (1) the first step is to identify IBRs where impedance analysis needs to be performed based on the magnitude of oscillations observed at their points of interconnection (POIs); (2) the second step focuses on performing impedance scans at selected IBRs in single-machine infinite-bus (SMIB) configuration to identify internal resonance modes of an IBR and to evaluate if any of these modes become unstable under certain grid conditions; (3) the third step performs impedance scans at a few selected IBRs while connected to the wider network model to obtain the impedance response of both the IBR and the grid - this step evaluates control interactions among IBRs. The impedance scan study found that a few IBRs have an underdamped resonance mode at around 17 Hz, which becomes unstable under a certain operating condition. Another interesting finding was that certain IBRs increase the effective grid impedance seen by another IBR in proximity for a particular operating condition. Under this operating condition, the resulting subsynchronous oscillation mode is more pronounced due to a combination of control interactions among IBRs through the transmission network under study and a resonance mode inside the IBRs.

control interactions↗
NASA NTRS2002

Acoustic Aspects of Active-Twist Rotor Control

The use of an Active Twist Rotor system to provide both vibration reduction and performance enhancement has been explored in recent analytical and experimental studies. Effects of active-twist control on rotor noise, however, had not been determined. During a recent wind tunnel test of an active-twist rotor system, a set of acoustic measurements were obtained to assess the effects of active-twist control on noise produced by the rotor, especially blade-vortex interaction (BVI) noise. It was found that for rotor operating conditions where BVI noise is dominant, active-twist control provided a reduction in BVI noise level. This BVI noise reduction was almost, but not quite, as large as that obtained in a similar test using HHC. However, vibration levels were usually adversely affected at operating conditions favoring minimum BVI noise. Conversely, operating conditions favoring minimum vibration levels affected BVI noise levels, but not always adversely.

Booth, Earl R., Jr.↗
DOE OSTI2021

Desalination metamodels and a framework for cross-comparative performance simulations

There is an opportunity to save energy and reduce operational expenses when choosing a suitable desalination method aided by computational modeling. Existing models are not conducive to generalized comparisons between different desalination methods. Therefore, the work in this study developed metamodels for six desalination methods, grouped them into thermal and molecular transport families, and validated their predictive performance within 9% difference from published data. This validated framework allowed comparisons of desalination methods at their prescribed ranges of operational conditions that they were designed for. These conditions specify feed salinity ranges of 1.6 to 2.4 g/kg for Capacitive Deionization and Reverse Osmosis (RO), 2.8 to 4.2 g/kg for Electrodialysis, 28 to 42 g/kg for Thermovapor Compression and Humidification-Dehumidification, and 37 to 55 g/kg for Multi-Effect Distillation (MED). Despite different operational conditions, all models exhibit non-linear, positive correlation between energy consumption and system size in response to feed salinity and production rate. The framework is also employed in a cross-comparative analysis between MED and RO whose results suggest that energy intensity for MED is an order of magnitude greater than RO for the same operational conditions, but actual operational costs are comparable. Overall, the framework is ready for deployment in case studies of actual desalination plants.

42 ENGINEERING↗
DOE OSTI2022

Learning and Fast Adaptation for Grid Emergency Control via Deep Meta Reinforcement Learning

As power systems are undergoing a significant transformation with more uncertainties, less inertia and closer to operation limits, there is increasing risk of large outages. Thus, there is an imperative need to enhance grid emergency control to maintain system reliability and security. Towards this end, great progress has been made in developing deep reinforcement learning (DRL) based grid control solutions in recent years. However, existing DRL-based solutions have two main limitations: 1) they cannot handle well with a wide range of grid operation conditions, system parameters, and contingencies; 2) they generally lack the ability to fast adapt to new grid operation conditions, system parameters, and contingencies, limiting their applicability for real-world applications. Here, in this paper, we mitigate these limitations by developing a novel deep meta-reinforcement learning (DMRL) algorithm. The DMRL combines the meta strategy optimization together with DRL, and trains policies modulated by a latent space that can quickly adapt to new scenarios. We test the developed DMRL algorithm on the IEEE 300-bus system. We demonstrate fast adaptation of the meta-trained DRL polices with latent variables to new operating conditions and scenarios using the proposed method, which achieves superior performance compared to the state-of-the-art DRL and model predictive control (MPC) methods.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Dynamic study of direct CO 2 capture from indoor air using poly(ethylenimine)-impregnated fiber sorbents

Supported amine adsorbents are promising materials for direct air capture (DAC) of CO 2 due to their high CO 2 capacity and relatively low energy requirement for regeneration. For a DAC process, it is essential to properly define operating parameters to achieve high sorbent productivity (amount of CO 2 captured per unit quantity of sorbent material over unit time). It is furthermore essential to understand the kinetic behavior of the process under the influence of various operating conditions such as the inlet air velocity, sorbent composition, and humidity to select an effective range of operating conditions to maximize sorbent productivity. Here, the dynamic behavior of a DAC process is probed using a fixed fiber sorbent contactor containing poly(ethylenimine) (PEI)-impregnated composite silica/cellulose acetate (CA) fibers. Throughout this study, experiments are conducted using both simulated air (398 ppm CO 2 balanced by N 2 ) and real indoor air (~400–500 ppm CO 2 ). The experimental behavior of the fibers using simulated air and indoor air is compared, and the influence of the inlet air velocity on the breakthrough behavior is assessed. By changing operating conditions, the impact on the fiber sorbent productivity (mmol CO 2 g fiber –1 h –1 ) is quantified to identify conditions that could favor high rates of CO 2 removal. The kinetics of steam-assisted CO 2 desorption are studied, identifying achievable desorption times. Productivities of 1.2 mmol CO 2 g fiber –1 h –1 are obtained using an inlet air velocity of 1.1 m s –1 . Performance trends show that further increasing the inlet air velocity will likely lead to even higher productivities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1976

Stability of elastic bending and torsion of uniform cantilever rotor blades in hover with variable structural coupling

The stability of elastic flap bending, lead-lag bending, and torsion of uniform, untwisted, cantilever rotor blades without chordwise offsets between the elastic, mass, tension, and areodynamic center axes is investigated for the hovering flight condition. The equations of motion are obtained by simplifying the general, nonlinear, partial differential equations of motion of an elastic rotating cantilever blade. The equations are adapted for a linearized stability analysis in the hovering flight condition by prescribing aerodynamic forces, applying Galerkin's method, and linearizing the resulting ordinary differential equations about the equilibrium operating condition. The aerodynamic forces are obtained from strip theory based on a quasi-steady approximation of two-dimensional unsteady airfoil theory. Six coupled mode shapes, calculated from free vibration about the equilibrium operating condition, are used in the linearized stability analysis. The study emphasizes the effects of two types of structural coupling that strongly influence the stability of hingeless rotor blades. The first structural coupling is the linear coupling between flap and lead-lag bending of the rotor blade. The second structural coupling is a nonlinear coupling between flap bending, lead-lag bending, and torsion deflections. Results are obtained for a wide variety of hingeless rotor configurations and operating conditions in order to provide a reasonably complete picture of hingeless rotor blade stability characteristics.

Hodges, D. H., Roberta.↗