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Results for “Operational Stability”

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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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Noble metal catalysts and processes for reforming of methane and other hydrocarbons

Processes for converting methane and/or other hydrocarbons to synthesis gas (i.e., a gaseous mixture comprising H 2 and CO) are disclosed, in which at least a portion of the hydrocarbon(s) is reacted with CO 2 . At least a second portion of the methane may be reacted with H 2 O (steam), thereby improving overall thermodynamics of the process, in terms of reducing endothermicity (ΔH) and the required energy input, compared to “pure” dry reforming in which no H2O is present. Catalysts for such processes advantageously possess high activity and thereby can achieve significant levels of methane conversion at temperatures below those used conventionally under comparable conditions. These catalysts also exhibit high sulfur tolerance, in addition to reduced rates of carbon (coke) formation, even in the processing (reforming) of heavier (e.g., naphtha boiling-range or jet fuel boiling-range) hydrocarbons. The robustness of the catalyst translates to high operating stability. A representative catalyst comprises 1 wt-% Pt and 1 wt-% Rh as noble metals, on a cerium oxide support.

Marker, Terry L.↗
DOE OSTI2023

Study of Microphonic Effects on the C100 Cryomodule for High Energy Electron Beam Accelerators

The Continuous Electron Beam Accelerator Facility (CEBAF) at Thomas Jefferson National Laboratory (JLab) is a particle accelerator which can accelerate an electron beam to relativistic speeds and apply the beam onto target samples. The C100 superconducting radio frequency (SRF) cavity is the primary accelerating structure of the C100 cryomodule, one of the many cryomodules which compose the CEBAF linear accelerator. SRF cavities are particularly sensitive to internal and external vibrations that can result in a phenomenon called microphonics which degrade the operational stability of a cryomodule. The purpose of this thesis is to investigate the significance of mechanical disturbances on the electromagnetic resonant frequency of a C100 SRF cavity. Knowledge of the mechanical resonance of the cavities and cryomodule sheds light into how these disturbances are most easily realized as deformation which causes radio frequency (RF) detuning. Three studies were conducted: the development and hammer test calibration of a Finite Element Analysis (FEA) model of a C100 cavity, the development and hammer test calibration of an FEA model of a C100 cavity string, and the hammer test of the C100-10R cryomodule at the Cryomodule Test Facility (CMTF). The cavity FEA model was found to accurately predict two modes found in two real cavities in a simply supported configuration. The cavity string FEA model leveraged the calibrated cavity FEA model but was not found to accurately predict the modal behavior of a real cavity string. Even so, the modal behavior of the cavity string inside the C100-10R cryomodule was captured during a hammer test while it was partially assembled. Finally, the C100-10R cryomodule was placed in the CMTF to study RF detuning. The RF detuning spectra during hammer hits and background noise was captured. The results of the hammer testing indicate two strong peaks at low frequencies (9-10 Hz and 22-23 Hz). These two frequencies were found to be nearly coincident to four instances of mechanical resonance found during the hammer testing done on the partially-assembled C100-10R. Because of this, these two modes are believed to contribute to RF detuning of the cryomodule. This test event also included the testing of the effectiveness of a configuration of BNNT canisters designed to act as dampers. While these tests show promising results, the lurking variables render these tests somewhat inconclusive.

Hull, Caleb James↗
DOE OSTI2023

Metal-assisted delayed fluorescent emitters employing pyrido-pyrrolo-acridine and analogues

Metal-assisted delayed fluorescent (MADF) emitters including cyclic tetradentate platinum (II) and palladium (II) complexes employing 8H-pyrido[3′,2′:4,5]-pyrrolo[3,2,1-de]acridine and its analogues. These complexes provide improved color purity and enhanced operational stability and are suitable for luminescent labels, emitters for organic light emitting diodes (OLEDs), and lighting applications.

Li, Jian↗
DOE OSTI2025

All Kitted Out

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13 HYDRO ENERGY↗
DOE OSTI2025

Identification of a window for quiescent H-mode operation in MHD stability diagram of DIII-D plasmas

A window for quiescent H-mode (QH-mode) operation in DIII-D plasmas in the diagram of pedestal magnetohydrodynamic (MHD) stability was identified through linear MHD stability analysis, accounting for the effects of plasma rotation and ion diamagnetic drift. The operation window lies between the stability boundaries of the kink/peeling mode (K/PM) identified with and without the inclusion of plasma rotation effects. In this region, the mode remains unstable unless rotation effects are considered alongside the ion diamagnetic drift, which is consistently included in the analysis. The stabilization of the MHD mode, facilitated by the coupled effects of plasma rotation and ion diamagnetic drift, plays a crucial role in widening the window, enabling the attainment of the QH-mode state. Furthermore, the suppression of edge localized modes (ELM) can be achieved by controlling the pedestal structure to ensure the plasma state remains within the operation window. The location of the operation window in the stability diagram depends on the K/PM stability properties. Therefore, optimizing conditions for QH-mode requires adjustments based on changes in stability characteristics. A pressure pedestal and its associated bootstrap current density near the last closed flux surface are advantageous for situating the plasma state within the window. However, excessive current density can trigger ELMs. This trend was confirmed through comparisons of MHD stability diagrams between QH-mode and ELMy H-mode plasmas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Asymmetric Bipolar Membrane for High Current Density Electrodialysis Operation with Exceptional Stability

Bipolar membranes (BPMs) enable isolated acidic/alkaline regions in electrochemical devices, facilitating optimized environments for electrochemical separations and catalysis. For economic viability, BPMs must attain stable, high current density operation with low overpotentials in a freestanding configuration. We report an asymmetric, graphene oxide (GrOx)-catalyzed BPM capable of freestanding electrodialysis operation at 1 A cm–2 with overpotentials <250 mV. Use of a thin anion-exchange layer improves water transport while maintaining near unity Faradaic efficiency for acid and base generation. Voltage stability exceeding 1100 h with an average drift of 70 μV/h at 80 mA cm–2 and 100 h with an average drift of −300 μV/h at 500 mA cm–2 and implementation in an electrodialysis stack demonstrate real-world applicability. Continuum modeling reveals that water dissociation in GrOx BPMs is both catalyzed and electric-field enhanced, where low pK a moieties on GrOx enhance local electric fields and high pK a moieties serve as active sites for surface-catalyzed water dissociation. These results establish commercially viable BPM electrodialysis and provide fundamental insight to advance design of next-generation devices.

Lucas, Éowyn↗
DOE OSTI2021

Optical Investigation of a Partial Fuel Stratification Strategy to Stabilize Overall Lean Operation of a DISI Engine Fueled with Gasoline and E30

This paper offers new insights into a partial fuel stratification (PFS) combustion strategy that has proven to be effective at stabilizing overall lean combustion in direct injection spark ignition engines. To this aim, high spatial and temporal resolution optical diagnostics were applied in an optically accessible engine working in PFS mode for two fuels and two different durations of pilot injection at the time of spark: 210 µs and 330 µs for E30 (gasoline blended with ethanol by 30% volume fraction) and gasoline, respectively. In both conditions, early injections during the intake stroke were used to generate a well-mixed lean background. The results were compared to rich, stoichiometric and lean well-mixed combustion with different spark timings. In the PFS combustion process, it was possible to detect a non-spherical and highly wrinkled blue flame, coupled with yellow diffusive flames due to the combustion of rich zones near the spark plug. The initial flame spread for both PFS cases was faster compared to any of the well-mixed cases (lean, stoichiometric and rich), suggesting that the flame propagation for PFS is enhanced by both enrichment and enhanced local turbulence caused by the pilot injection. Different spray evolutions for the two pilot injection durations were found to strongly influence the flame kernel inception and propagation. PFS with pilot durations of 210 µs and 330 µs showed some differences in terms of shapes of the flame front and in terms of extension of diffusive flames. Yet, both cases were highly repeatable.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Comparison of Quinone-Based Catholytes for Aqueous Redox Flow Batteries and Demonstration of Long-Term Stability with Tetrasubstituted Quinones

Quinones are appealing targets as organic electrolytes for aqueous redox flow batteries (RFBs), but their utility continues to be constrained by limited stability under operating conditions. The present study evaluates the stability of a series water-soluble quinones, with redox potentials ranging from 605–885 mV vs. NHE, under acidic aqueous conditions (1 M H2SO4). Four of the quinones are examined as cathodic electrolytes in an aqueous RFB, paired with anthraquinone-2,7-disulfonate (AQDS) as the anodic electrolyte. The RFB data complement the solution stability measures and show that the most stable electrolyte is a tetrasubstituted quinone containing four sulfonated thioether substituents. The results highlight the importance of substituting all C–H positions of the quinone in order to maximize the quinone stability and set the stage for design of improve organic electrolytes for aqueous RFBs. The authors thank Joseph Fourie for assisting in the synthesis of compound 8. Financial support for this work was provided by the Center for Molecular Electrocatalysis, an Energy Frontier Research Center funded by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences (SSS, TWR, JBG, CWA, YP), with supplemental contributions by the Wisconsin Alumni Research Foundation (WARF) through the WARF Accelerator Program (YQ and partial support for JBG, CWA, YP). NMR spectroscopy facilities were partially supported by the NSF (CHE-0342998 and CHE-1048642), a UW Madison Instructional Laboratory Modernization Award, and a gift from Paul J. and Margaret M. Bender.

aqueous flow batteries, quinones, organic, redox m↗
DOE OSTI2020

Stability boundary and optimal operating parameter identification in milling using Bayesian learning

Here, this paper describes a novel Bayesian learning approach for stability boundary and optimal parameter identification in milling without the knowledge of the underlying tool dynamics or material cutting force coefficients. The paper is divided into two parts. First, a Bayesian learning method for stability lobe identification using test results is described. Each axial depth and spindle speed combination is characterized by a probability of stability which is updated using Bayes’ rule when a test result (stable or unstable) is made available. A novel likelihood function is defined which incorporates knowledge of the stability behavior. Numerical results show convergence to the analytical stability lobe diagram. Second, an adaptive experimental strategy to identify optimal operating parameters that maximize material removal rate is described. Numerical evaluation shows convergence to the optimal operating point with error less than 15 % within ten tests on average. The approach is validated using experimental results. Results show that the proposed method is an efficient and robust learning method to identify the stability lobe diagram and optimal operating parameters with a limited number of tests/data points.

Bayesian machine learning↗
DOE OSTI2024

Inverter Intensive Hybrid Power Plant Modeling with Small-Signal Stability Augmentation through Flexible Operation Mode Transition

Hybrid power plants (HPPs) prompt the penetration of inverter-based renewable energy sources (RES) in transmission systems; however, given their low-inertia nature, HPPs are dominated by power electronic inverters, so there are inevitable challenges in system stability when increasing numbers of HPPs are integrated into the modern power grids. To boost the penetration level of HPPs without jeopardizing system stability, it is desirable to equip them with operational characteristics (i.e., grid-forming capabilities) that are comparable to those of conventional power plants dominated by synchronous generators (SGs). In this paper, a holistic model of inverter intensive HPP is derived and a bi-level hierarchical control is developed to allow HPPs to flexibly switch among the designed operation modes (i.e., P-Q, P-V, and isochronous modes). Compared to SGs, which have limited controllability, the operation mode of each HPP could vary as requested. Such flexible mode transitions could be integrated into the secondary plant-level control and be leveraged as an additional control degree to further augment system stability. Further, the system small-signal stability margin is quantified with varying HPP operation modes. More importantly, modal analysis is thereby conducted to quantify the impacts of mode transition on the system oscillatory modes. The effectiveness of the proposed HPP bi-level hierarchical control is verified using extensive case studies based on the simplified real-world island power grid, and the results validate that the system small-signal stability margin can be enhanced with the additional degree of control flexibility enabled by HPP operation mode transition. The real-time hardware-in-the-loop (HIL) results are also provided to verify the proposed method.

grid-forming control↗
DOE OSTI2025

Quantifying CO 2 Plume Stabilization at Carbon Storage Projects, North Dakota, USA

This study presents an approach for quantifying when injected carbon dioxide (CO 2 ) stabilizes pursuant to carbon capture and storage (CCS) project permitting and site closure requirements. The distribution of mobile-phase CO 2 (CO 2 plume) will evolve within the storage reservoir during and after injection through both physical and chemical trapping mechanisms. CCS policies generally agree that the CO 2 plume’s migratory behavior in post-injection should demonstrate nonendangerment to the environment but do not provide specific guidance on how to meet the definition of plume stabilization, generating some uncertainty for operators. Plume stability herein means the CO 2 plume 1) changes size minimally and predictably in the storage reservoir such that it will not cross key boundaries identified in the permit and 2) does not pose a threat to human health, underground sources of drinking water (USDWs), and the environment because of lateral migration to areas where leakage pathways may exist. Published literature on plume metrics was reviewed to determine which metric(s) may be most appropriate for determining CO 2 plume stability. A technical approach that defines plume stabilization by estimating the rate of change in the geographic footprint of the CO 2 plume with respect to time was developed and illustrated using a case study from North Dakota, USA, as a proposed solution for CCS operators to apply at the project permitting stage. Any prospective CCS operator may benefit from using the same approach to inform the selection of pore space lease and monitoring areas and develop post-injection site care plans.

03 NATURAL GAS↗
DOE OSTI2024

A data-driven framework for predicting machining stability: employing simulated data, operational modal analysis, and enhanced transfer learning

Chatter, a self-excited vibration phenomenon, presents a significant challenge in machining operations, particularly in high-speed milling, where it can degrade tool life, reduce material removal efficiency, and compromise workpiece quality. Addressing this challenge requires a reliable predictive model that can accommodate the complex dynamics of various machining scenarios. This study introduces a novel, data-driven approach to predicting machining stability, leveraging over 140,000 simulated datasets and employing advanced techniques such as operational modal analysis (OMA), enhanced transfer learning (TL), and receptance coupling substructure analysis (RCSA). By integrating these methodologies, the framework effectively classifies and predicts chatter across diverse operational modes, achieving robust and accurate outcomes. Our model utilizes a Random Forest (RF) classifier trained with the comprehensive dataset, which demonstrates substantial improvements in both predictive accuracy and robustness. Specifically, the RF model achieved an accuracy rate of 85%, an area under the curve (AUC) of 0.90, and an F1 score of 0.88, underscoring its capability to adapt to varying machining configurations. These results highlight the framework’s potential to enhance operational efficiency and machining quality by providing reliable chatter predictions across a broad range of machining parameters. In conclusion, this research thus offers a significant advancement in predictive maintenance for machining processes, enabling more stable and efficient manufacturing operations.

42 ENGINEERING↗
DOE OSTI2021

Optimal Power Flow in DC Networks with Robust Feasibility and Stability Guarantees

With high penetrations of renewable generation and variable loads, there is significant uncertainty associated with power flows in DC networks such that stability and operational constraint satisfaction are of concern. Most existing DC network optimal power flow (DN-OPF) formulations assume exact knowledge of loading conditions and do not provide stability guarantees. Here, in contrast, this paper studies a DN-OPF formulation which considers both stability and operational constraint satisfaction under uncertainty. The need to account for a range of uncertainty realizations in this paper's robust optimization formulation results in a challenging semi-infinite program (SIP). The proposed solution algorithm reformulates this SIP into a computationally tractable problem by constructing a tight convex inner approximation of the stability set using sufficient conditions for the existence of a feasible and stable power flow solution. Optimal generator set-points are obtained by optimizing over the proposed convex stability set. The validity and effectiveness of the propose algorithm is demonstrated through various DC networks adapted from IEEE test cases.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Development of a medium-duty stoichiometric diesel micro-pilot natural gas engine

Fueling a compression-ignition engine with premixed natural gas offers the potential to combine a clean-burning, low-carbon fuel with a high compression ratio, high-efficiency engine. This work describes the development of a multi-cylinder 6.7 L diesel engine converted to run stoichiometric diesel micro-pilot/ natural gas premix combustion with a maximum diesel contribution target of 5% of the total fuel energy and a three-way catalyst aftertreatment system. Results are given by comparing the stoichiometric combustion to the diesel baseline operation, showing combustion characteristics differences, including the rapid two stage heat release. A high load output of 23 bar brake mean effective pressure was obtained with diesel-like brake thermal efficiency of 41%. This operating condition enabled a brake specific CO 2 emissions reduction of up to 25% when compared to diesel. It was observed that the low load output is limited by combustion stability when operated at stoichiometric condition. The three-way catalyst is observed to run at peak efficiency with an equivalence ratio of 1.01. Injector fouling was observed through the inspection of the nozzle and its internal parts, indicating carbon build-up similar to that seen in injector coking mechanisms. A comparison of the developed engine to other engine technologies is given, showing that the diesel micro-pilot natural gas engine performance is in good standing among other diesel and gas engines in the market.

Engineering↗
DOE OSTI2022

Closo ‐Borate Gel Polymer Electrolyte with Remarkable Electrochemical Stability and a Wide Operating Temperature Window

Abstract A major challenge in the pursuit of higher‐energy‐density lithium batteries for carbon‐neutral‐mobility is electrolyte compatibility with a lithium metal electrode. This study demonstrates the robust and stable nature of a closo ‐borate based gel polymer electrolyte (GPE), which enables outstanding electrochemical stability and capacity retention upon extensive cycling. The GPE developed herein has an ionic conductivity of 7.3 × 10 −4 S cm −2 at room temperature and stability over a wide temperature range from −35 to 80 °C with a high lithium transference number ( = 0.51). Multinuclear nuclear magnetic resonance and Fourier transform infrared are used to understand the solvation environment and interaction between the GPE components. Density functional theory calculations are leveraged to gain additional insight into the coordination environment and support spectroscopic interpretations. The GPE is also established to be a suitable electrolyte for extended cycling with four different active electrode materials when paired with a lithium metal electrode. The GPE can also be incorporated into a flexible battery that is capable of being cut and still functional. The incorporation of a closo ‐borate into a gel polymer matrix represents a new direction for enhancing the electrochemical and physical properties of this class of materials.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Pricing Strategy of Electric Vehicle Aggregators Based on Locational Marginal Price to Minimize Photovoltaic (PV) Curtailment

The global climate crisis demands urgent action to mitigate global warming. Using renewable energy sources, such as solar and wind power, for electricity generation is crucial. This shift from centralized to distributed power systems, however, brings challenges, including voltage fluctuations and renewable energy curtailment. The rapid growth of the electric vehicle (EV) industry adds complexity, increasing overall electricity demand and straining the power supply during peak charging times. This paper proposes a scheduling strategy for EV aggregators to reduce renewable energy curtailment and stabilize grid operation by strategically scheduling EV charging. Using Multi -Agent Transport Simulation (MATSim), a traffic simulation tool, EV driving data in Denver, Colorado, USA, were modeled. The EV aggregator adjusts charging fees based on locational marginal prices, encouraging EVs to charge at different stations according to pricing. Simulations on an IEEE 33-bus system with distributed energy resources and EV charging stations validate the proposed algorithm, demonstrating its effectiveness in reducing curtailment by 12.55% and stabilizing grid operation.

33 ADVANCED PROPULSION SYSTEMS↗