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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.
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Designing a collective blade pitch controller for floating offshore wind turbines (FOWTs) poses unique challenges due to the interaction of the controller with the dynamics of the platform. The controller must also handle the competing objectives of power production performance and fatigue load management. Existing solutions either detune the controller with the result of slowed response, make use of complicated tuning methods, or incorporate a nacelle velocity feedback gain. With the goal of developing a simple control tuning method for the general FOWT researcher that is easily extensible to a wide array of turbine and hull configurations, this last idea is built upon by proposing a simple tuning strategy for the feedback gain. This strategy uses a two degree-of-freedom (DoF) turbine model that considers tower-top fore-aft and rotor angular displacements. For evaluation, the nacelle velocity term is added to an existing gain scheduled proportional-integral controller as a proportional gain. The modified controller is then compared to baseline land-based and detuned controllers on an example system for several load cases. First-pass results are favorable, demonstrating how researchers can use the proposed tuning method to efficiently schedule gains for adequate controller performance as they investigate new FOWT configurations.
In high-energy and astroparticle physics, event generators play an essential role, even in the simplest data analyses. As analysis techniques become more sophisticated, e.g. based on deep neural networks, their correct description of the observed event characteristics becomes even more important. Physical processes occurring in hadronic collisions are simulated within a Monte Carlo framework. A major challenge is the modeling of hadron dynamics at low momentum transfer, which includes the initial and final phases of every hadronic collision. QCD-inspired phenomenological models used for these phases cannot guarantee completeness or correctness over the full phase space. These models usually include parameters which must be tuned to suitable experimental data. Until now, event generators have been developed and tuned mainly on the basis of data from high-energy physics experiments at accelerators. The wealth of data available from the latest generation of astroparticle experiments has not yet been fully exploited, and in many cases is not satisfactorily described. Both kinds of data sets are complementary as astroparticle experiments provide sensitivity especially to hadrons produced nearly parallel to the collision axis and cover center-of-mass energies up to several hundred TeV, well beyond those reached at colliders so far. In this report, we provide an overview of state-of-the-art event generators and their tuning, including the most relevant inputs from high-energy accelerator and astroparticle experiments. We present a road map that shows, for the first time, how the unified tuning of event generators with accelerator-based and astroparticle data can be performed.
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Island tune spectra are introduced, beginning with curves of resonance trajectories plotted in the (Q x , Q I ) tune domain plane (where Q x is horizontal tune and Q I is island tune) for many resonance orders N. A slice in the (Q x , Q I ) plane delivers a Q I -spectrum at a fixed horizontal tune, with one spectral line for every appropriate value of N.
Using parallel file systems efficiently is a tricky problem due to inter-dependencies among multiple layers of I/O software, including high-level I/O libraries (HDF5, netCDF, etc.), MPI-IO, POSIX, and file systems (GPFS, Lustre, etc.). Profiling tools such as Darshan collect traces to help understand the I/O performance behavior. However, there are significant gaps in analyzing the collected traces and then applying tuning options offered by various layers of I/O software. Seeking to connect the dots between I/O bottleneck detection and tuning, we propose DXT Explorer, an interactive log analysis tool. In this paper, we present a case study using our interactive log analysis tool to identify and apply various I/O optimizations. We report an evaluation of performance improvement achieved for four I/O kernels extracted from science applications.
Many U.S. cities are implementing policies to reduce greenhouse gas (GHG) emissions of their buildings. These range from building energy benchmarking and disclosure to building performance standards (BPS) that require buildings to meet specific targets of energy use or emissions. The City of Seattle adopted a climate action plan in 2013 that set a goal of zero net GHG emissions in the road transportation, buildings, and waste sectors by 2050, with a number of near and long term actions. Seattle implemented mandatory building tune-ups in 2016, applying to commercial buildings larger than 50,000 sqft. Building tune-ups1 involve assessment and implementation of operational and maintenance (O + M) improvements to achieve energy and water efficiency, such as changes to thermostat set points or adjusting lighting or irrigation schedules. Seattle's tune-ups program covered 27 such improvements in HVAC, lighting, domestic hot water, and envelope systems.
Highly active and selective CO 2 methanation catalysts are critical to CO 2 upgrading, synthetic natural gas production, and CO 2 emission reduction. Wet impregnation is widely used to synthesize oxide-supported metallic nanoparticles as the catalyst for CO 2 methanation. However, as the reagents cannot be homogeneously mixed at an atomic level, it is challenging to modulate the microstructure, crystal structure, chemical composition, and electronic structure of catalysts via wet impregnation. In this work, a scalable and straightforward catalyst fabrication approach has been designed and validated to produce Sm 0.25 Ce 0.75 O 2-δ -supported Ni (SDC–Ni) as the CO 2 methanation catalyst. By varying the chelating agents-to-total metal cations ratio (C/I ratio) during the catalyst synthesis, we can readily and simultaneously modulate the microstructure, metallic surface area, crystal structure, chemical composition, and electronic structure of SDC–Ni, consequently fine-tuning the oxide–support interactions and CO 2 methanation activity. The optimal C/I ratio (0.1) leads to an SDC–Ni catalyst that facilitates C–O bond cleavage and significantly improves CO 2 conversion at 250 °C. A CO 2 -to-CH 4 yield of >73% has been achieved at 250 °C. Furthermore, a stable operation of >1500 hours has been demonstrated, and no degradation is observed. Extensive characterizations were performed to fundamentally understand how to tune and enhance CO 2 methanation activity of SDC–Ni by modulating the C/I ratio. The correlation of physical, chemical, and catalytic properties of SDC–Ni with the C/I ratio is established and thoroughly elaborated in this work. This study could be applied to tune the oxide–support interactions of various catalysts for enhancing the catalytic activity.
GCAM assumptions typically generate scenarios that are designed to be internally consistent and globally coherent. The gcamdata tool which facilitates the compilation of data sets and user assumptions is not well suited to tailoring to specific country or regional realities, sponsor requirements, or perform harmonization for model intercomparison needs. As described in this report, the GCAM Regional Tuning project develops a computational framework that enables users to adjust GCAM parameters, so model outputs match targeted outcomes at user-defined spatial, temporal, and sectoral resolutions. The framework integrates GCAM, gcamdata, and gcamwrapper with a set of flexible “tuning directives” and an iterative numerical solver. Users can define targets (e.g., technology shares in power generation, BEV uptake, sectoral service demands), select tuners that manipulate relevant GCAM parameters (e.g., share weights, cost adders, elasticities), and export tuned parameters as reusable GCAM XML inputs for future runs. We demonstrate the approach and document usage, diagnostics, and known limitations, and we outline potential future directions.
Ferredoxins (Fds) are small proteins which shuttle electrons to pathways like biological nitrogen fixation. Physical properties tune the reactivity of Fds with different pathways, but knowledge on how these properties can be manipulated to engineer new electron transfer pathways is lacking. Recently, we showed that an evolved strain of Rhodopseudomonas palustris uses a new electron transfer pathway for nitrogen fixation. This pathway involves a variant of the primary Fd of nitrogen fixation in R. palustris, Fer1, in which threonine at position 11 is substituted for isoleucine (Fer1 T11I ). To understand why this substitution in Fer1 enables more efficient electron transfer, we used in vivo and in vitro methods to characterize Fer1 and Fer1 T11I . Electrochemical characterization revealed both Fer1 and Fer1 T11I have similar redox transitions (–480 mV and – 550 mV), indicating the reduction potential was unaffected despite the proximity of T11 to an iron-sulfur (Fe—S) cluster of Fer1. Additionally, disruption of hydrogen bonding around an Fe—S cluster in Fer1 by substituting threonine with alanine (T11A) or valine (T11V) did not increase nitrogenase activity, indicating that disruption of hydrogen bonding does not explain the difference in activity observed for Fer1 T11I . Electron paramagnetic resonance spectroscopy studies revealed key differences in the electronic structure of Fer1 and Fer1 T11I , which indicate changes to the high spin states and/or spin-spin coupling between the Fe—S clusters of Fer1. Finally, our data implicates these electronic structure differences in facilitating electron flow and sets a foundation for further investigations to understand the connection between these properties and intermolecular electron transfer.
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The demand for packaging materials with low gas permeabilities is increasing, but commonly used petroleum-derived single-use plastics are not renewable, biodegradable, or easy to recycle. Nanomaterials composed of chitin and cellulose, which are abundant in nature, have high crystallinities and low oxygen permeabilities (OP), providing a viable alternative. In this work, we explore how deacetylation conditions of crab shell chitin can be used to tune the charge and size of resulting chitin nanowhiskers (ChNWs) and the resulting OP of layered film structures. Three deacetylation factors, the concentration of sodium hydroxide (%NaOH), temperature (T), and reaction time, were explored using a three-factor three-level Taguchi design with an orthogonal array. Furthermore, the resulting ChNW suspensions were sequentially spray-coated with suspensions of cellulose nanocrystals (CNCs) onto cellulose acetate (CA) films to form a multilayer structure. We show that ChNWs prepared under more aggressive deacetylation conditions inside the original orthogonal array (higher %NaOH, T, and time) had shorter lengths but the surface charge was significantly influenced only by more aggressive deacetylation outside of the original design conditions. With only ~10% decrease in the ultimate tensile strength and no significant loss in failure strain, the ChNW-CNC coating resulted in ~20% decrease in WVTR in comparison to uncoated CA films. The optimization of process conditions resulted in CA-ChNW-CNC films with a 91-99% decrease in OP (132-16.7 cm 3 ∙μm/m 2 /day/kPa versus 1553 cm3∙μm/m2/day/kPa for uncoated CA).
Oxygen-containing carbons are promising supports and metal-free catalysts for many reactions. However, distinguishing the role of various oxygen functional groups and quantifying and tuning each functionality is still difficult. Here we investigate the role of Brønsted acidic oxygen-containing functional groups by synthesizing a diverse library of materials. By combining acid-catalyzed elimination probe chemistry, comprehensive surface characterizations, 15N isotopically labeled acetonitrile adsorption coupled with magic-angle spinning nuclear magnetic resonance, machine learning, and density-functional theory calculations, we demonstrate that phenolic is the main acid site in gas-phase chemistries and unexpectedly carboxylic groups are much less acidic than phenolic groups in the graphitized mesoporous carbon due to electron density delocalization induced by the aromatic rings of graphitic carbon. The methodology can identify acidic sites in oxygenated carbon materials in solid acid catalyst-driven chemistry.
This paper presents an optimal preventive control (OPC) method to improve the power system transient stability via tuning the transient parameter of virtual synchronous generators. The novelty of this work is that we formulate the preventive control as an optimization problem so that inverter parameters can be adjusted at the pre-contingency stage. A reinforcement learning (RL)-driven method is proposed to solve the OPC problem with the fault energy-based reward function. An ANDES-based RL environment is also developed. Versatile functions included in the proposed environment have been presented in this paper. The proposed OPC formulation, the RLdriven method, and the fault energy-based reward function are verified on several standard test systems.
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In this study, we report a novel strategy to increase the gas adsorption selectivity of metal organic framework materials by coadsorbing another molecular species. Specifically, we find that addition of tightly bound NH 3 molecules in the well-known metal–organic framework MOF-74 dramatically alters its adsorption behavior of C 2 H 2 and C 2 H 4 . Combining in situ infrared spectroscopy and ab initio calculations, we find that—as a result of coadsorbed NH 3 molecules attaching to the open metal sites—C 2 H 2 binds more strongly and diffuses much faster than C 2 H 4 , occupying the available space adjacent to metal-bound NH 3 molecules. Most remarkably, C 2 H 4 is now almost completely excluded from entering the MOF once C 2 H 2 has been loaded. This finding dispels the widespread belief that strongly coadsorbed species in nanoporous materials always undermine their performance in adsorbing or separating weakly bound target molecules. Furthermore, it suggests a new route to tune the adsorption behavior of MOF materials through harnessing the interactions among coadsorbed guests.
Aqueous zinc batteries are recognized to suffer from H + /Zn 2+ coinsertion in the cathode, but few approaches have been reported to suppress deleterious H + intercalation. We realize this goal by tuning the solvation structure, using LiV 2 (PO 4 ) 3 (LVP) as a model cathode. Phase conversion of LVP induced by H + intercalation is observed in 4 m Zn(OTf) 2 , whereas dominant Zn 2+ insertion is confirmed in a ZnCl 2 water-in-salt electrolyte (WiSE). This disparity is ascribed to the complete absence of free water and a strong Zn 2+ –H 2 O interaction in the latter that interrupts the H 2 O hydrogen bonding network, thus suppressing H + intercalation. On the basis of this strategy, a novel PEG-based hybrid electrolyte is designed to replace the corrosive ZnCl2 WiSE. This system exhibits an optimized Zn 2+ solvation sheath with a similar low free water content, showing not only much better suppression of H + intercalation but also highly reversible Zn plating/stripping with a CE of ~99.7% over 150 cycles.