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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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At least 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Compact Peptoid Molecular Brushes for Nanoparticle Stabilization

Controlling the interfaces and interactions of colloidal nanoparticles (NPs) via tethered molecular moieties is crucial for NP applications in engineered nanomaterials, optics, catalysis, and nanomedicine. Despite a broad range of molecular types explored, there is a need for a flexible approach to rationally vary the chemistry and structure of these interfacial molecules for controlling NP stability in diverse environments, while maintaining a small size of the NP molecular shell. Here, we demonstrate that low-molecular-weight, bifunctional comb-shaped, and sequence-defined peptoids can effectively stabilize gold NPs (AuNPs). The generality of this robust functionalization strategy was also demonstrated by coating of silver, platinum, and iron oxide NPs with designed peptoids. Each peptoid (PE) is designed with varied arrangements of a multivalent AuNP-binding domain and a solvation domain consisting of oligo-ethylene glycol (EG) branches. Among designs, a peptoid (PE5) with a diblock structure is demonstrated to provide a superior nanocolloidal stability in diverse aqueous solutions while forming a compact shell (similar to 1.5 nm) on the AuNP surface. We demonstrate by experiments and molecular dynamics simulations that PE5-coated AuNPs (PE5/AuNPs) are stable in select organic solvents owing to the strong PE5 (amine)-Au binding and solubility of the oligo-EG motifs. At the vapor-aqueous interface, we show that PE5/AuNPs remain stable and can self-assemble into ordered 2D lattices. The NP films exhibit strong near-field plasmonic coupling when transferred to solid substrates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Thermal Stability of Silica for Application in Thermal Energy Storage

Thermal energy storage (TES) systems have enabled concentrating solar power (CSP) to remain competitive in the modern energy mix by providing economical load shifting grid services and firming up intermittent solar resource. Free from siting constraints, TES also shows promise as an economical alternative to traditional pumped-storage hydropower (PSH) and compressed air energy storage (CAES). As potential thermal energy storage media, some solid particles demonstrate stability over wide temperature ranges which allows for increased sensible energy storage density and is essential in achieving low-cost storage. Silica sand, in the form of a-quartz, is one such candidate. This work presents a brief review of relevant silica thermophysical properties and further investigates the thermal stability of silica particles as a candidate TES media by subjecting them to two different thermal tests: (1) a 500-hour thermal treatment at 1200 degrees C under varied atmospheres; and (2) cycling 25, 50, and 100 times between 300 degrees C and 1200 degrees C. For both tests, particle stability is examined by means of pre- and post-treatment Mie scattering. An additional XRD analysis is conducted for the 500-hour treatment in air. Results indicate limited changes in both particle distribution and crystallographic structure which is promising for the application as solid particle media for thermal energy storage.

concentrating solar power↗
DOE OSTI2022

The stability of expanding reactive shocks in a van der Waals fluid

Despite the extensive literature accumulated since the pioneering works of D'yakov and Kontorovich in the 1950s, the stability of steady shocks is still an open question when realistic boundary conditions are accounted. The consideration of a supporting mechanism, which is indeed a necessary condition for shock steadiness, modifies the perturbation shock dynamics in the unstable range. The Noh problem is a suitable example to form steady expanding shocks. This configuration is of great interest to the high-energy-density-physics community because of its direct application to inertial confinement fusion and astrophysics, for which the stagnation of a supersonically converging material via an accretion shock front is ubiquitous. Here in this work, we extend the generalized Noh problem, both base-flow solution and linear stability analysis, to conditions where endothermic or exothermic transformations undergo across the shock. Within the spontaneous acoustic emission conditions found for a van der Waals gas, we find that cylindrical and spherical expanding shocks become literally unstable for sufficiently high mode numbers. Counterintuitively, the effect of exothermicity or endothermicity across the shock is found to be stabilizing or destabilizing, respectively.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Omnigenous stellarators with improved ideal and kinetic ballooning stability

Omnigenity is a property of a magnetic field which ensures confinement of trapped particles. It is a necessary requirement for any high-performance stellarator. After creating an omnigenous equilibrium, one must also ensure reduced transport resulting from kinetic and magnetohydrodynamic (MHD) instabilities. To this end, we leverage the GPU-accelerated DESC optimization suite, which is used to design stable, finite-β omnigenous equilibria with poloidal, toroidal, and helical symmetry, achieving Mercier, ideal ballooning, and as a consequence, improved kinetic ballooning stability. We discover stellarators with second stability, a regime of large pressure gradient where an equilibrium becomes ideal ballooning stable, and demonstrate and explore both using theory and gyrokinetic simulations the connection between ideal and kinetic ballooning stability.

optimization↗
DOE OSTI2021

Pedestal stability analysis on MAST in preparation for MAST-U

In preparation for the upcoming MAST-U campaign, pedestal stability of spherical tokamaks is revisited by investigating standard H-mode discharges on MAST. As a step beyond previous studies, both ion and electron profiles are used for obtaining equilibria and a diverse set of pedestals is evaluated. Stability analysis with the ELITE and CGYRO codes shows that MAST pedestals are constrained by kinetic ballooning modes and medium toroidal mode number peeling-ballooning modes, with most unstable modes ranging from n = 25 to n = 45. In discharges with a steep q profile at the edge a larger number of poloidal harmonics is excited for each toroidal mode. In conclusion, a comparison with discharges on DIII-D with matched shape and similar non-dimensional parameters indicates that the increased shear at lower aspect ratio stabilizes low n peeling modes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Development of a neural network model for peeling–ballooning stability analysis in the KSTAR tokamak pedestals

The neural network model, MISHKA-NN is developed to mitigate the computational burden associated with the linear ideal magnetohydrodynamic (MHD) stability analysis of the pedestal based on the peeling–ballooning (P–B) model. By utilizing both 1D plasma profiles (current density, pressure gradient, and safety factor) and 0D parameters (plasma geometry, total current, and toroidal mode number), the model predicts linear growth rate of edge-localized ideal MHD instability in a given equilibrium state. By enabling the prediction of each instability within a second, the model reduces the time required for plotting a pedestal P–B stability diagram (j - α diagram) from approximately 100 CPU hours to a few CPU minutes. Notably, even with the utilization of parametric pressure and current profiles and plasma boundary shapes for the training dataset, the model shows a satisfactory level of performance in benchmarking the j - α diagram for the reconstructed equilibrium from a KSTAR tokamak experiment. We anticipate the model to serve as a versatile alternative to 2D linear MHD stability codes, alleviating numerical costs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Dynamic inflow and unsteady aerodynamics models for modal and stability analyses in OpenFAST

This work presents two aerodynamic models that are used to perform modal and stability analyses of wind turbines. Including aerodynamic effects in stability analyses is important to capture aerodynamic inertia, stiffness, and damping. The two models consist of a dynamic inflow model based on Øye’s model and an unsteady aerodynamics model based on a simplified Beddoes-Leishman dynamic stall model. Both models are written in a continuous-time state-space form, which is the form needed to perform linearizations within OpenFAST. In this article, we present the new models, perform some simple verifications against HAWC2 results, and then perform stability analyses. We investigate the contribution of the aerodynamic effects on the turbine modes, particularly the flapwise modes, which are the most affected. Because of the development presented in this work, Campbell diagrams accounting for dynamic stall and dynamic wake effects were generated for the first time using OpenFAST.

17 WIND ENERGY↗
DOE OSTI2023

Bioinspired stability enhancement in deuterium-substituted organic–inorganic hybrid perovskite solar cells

Abstract In hybrid perovskite solar cells (PSCs), the reaction of hydrogens (H) located in the amino group of the organic A-site cations with their neighboring halides plays a central role in degradation. Inspired by the retarded biological activities of cells in heavy water, we replaced the light H atom with its abundant, twice-as-heavy, nonradioactive isotope, deuterium (D) to hamper the motion of H. This D substitution retarded the formation kinetics of the detrimental H halides in Pb-based PSCs, as well as the H bond-mediated oxidation of Sn2+ in Sn–Pb-based narrow-bandgap PSCs, evidenced by accelerated stability studies. A computational study indicated that the zero point energy of D-based formamidinium (FA) is lower than that of pristine FA. In addition, the smaller increase in entropy in D-based FA than in pristine FA accounts for the increased formation free energy of the Sn2+ vacancies, which leads to the retarded oxidation kinetics of Sn2+. In this study, we show that substituting active H with D in organic cations is an effective way to enhance the stability of PSCs without sacrificing photovoltaic (PV) performance. This approach is also adaptable to other stabilizing methods.

14 SOLAR ENERGY↗
DOE OSTI2022

Small-Signal Stability Support from Dynamically Configurable Grid-Forming/Following Inverters for Distribution Systems

The growth of inverter-based resources (IBRs) in modern power systems can challenge system stability since they do not natively provide inertia, prompting a need to develop new methods to address the potential instabilities. In this paper, a dynamically configurable grid-forming (GFM) and grid-following (GFL) control is proposed, which enables inverters to flexibly transition to support system needs. The operation mode transition between GFM and GFL controls is adopted as an additional degree of control flexibility to adjust the small-signal stability margin. In addition, a holistic and detailed small-signal model for a distribution feeder that captures the dynamics from both synchronous generators (SGs) and IBRs is also derived and used to evaluate the effectiveness of the proposed GFM/GFL controls to augment the system small-signal stability margin. Case studies with varying levels of IBRs were implemented in MATLAB/Simulink to demonstrate the effectiveness of the proposed approach.

grid-following control↗
DOE OSTI2022

Comparative Small-Signal Stability Analysis of Grid-Forming and Grid-Following Inverters in Low-Inertia Power Systems: Preprint

Inverter-based resources (IBRs) are gradually replacing conventional fossil energy in modern power systems, which could make the system susceptible due to insufficient inertia, especially when moving towards a 100% inverter-based power grid. Grid-forming (GFM) and grid-following (GFL) controls are two common inverter control algorithms. However, the corresponding stability issues along with a comparative study on low-inertia power systems should still be investigated. This paper focuses on small-signal stability and conducts a comprehensive analysis of GFM and GFL controls, with emphases on the interactions between synchronous generators and IBRs. The detailed modeling of GFM and GFL inverters, and synchronous generators (SGs) are established. The coupling mechanism of IBRs and SGs is then conducted through participation factor analysis. The impacts of critical parameters on system stability are finally identified. The theoretical analyses are validated through time-domain simulation in MATLAB/Simulink.

grid-following↗
DOE OSTI2024

On the Stability of Power Transmission Systems Under Persistent Inverter Attacks: A Bi-Linear Matrix Approach

We investigate the stability and robustness properties of a power transmission system under persistent deceiving attacks on inverter-interfaced energy resources. The attacks can corrupt the damping coefficients in the inverters' controllers and measurements of the frequency at the points of coupling. Leveraging tools from hybrid dynamical systems theory, we characterize a broad family of persistent (and not necessarily periodic) attacks acting on the inverters, under which the stability properties of the transmission system can be shown to not be compromised. To address potentially conservative conditions identified through conventional bounding techniques, sufficient conditions on the average activation time of the attacks are identified via Lyapunov theory, as well as the formulation and solution of a class of bilinear matrix inequalities (BMI). The results are obtained for constant and slowly time-varying loads via input-to-state stability (ISS) tools. Numerical simulations on the IEEE 39-bus test system are also presented.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Explainable Bayesian Neural Network for Probabilistic Transient Stability Analysis Considering Wind Energy

While several data-driven models have been developed for transient stability assessment, how to consider the uncertainties from load and renewable generations and provide interpretation of data-driven assessment results are still open. This paper proposes an explainable Bayesian Neural Network (BNN) for probabilistic transient stability assessment (TSA). By extracting the uncertainties from loads and wind farms, the BNN model can make a reliable prediction and quantify the prediction uncertainties. We also develop the Gradient Shap algorithm to make the global and local explanations for the probabilistic TSA model, a significant advantage over existing black-box data-driven methods. Numerical results on the modified IEEE 39-bus system show that the proposed method outperforms the existing methods in terms of prediction accuracy and uncertainty quantification capabilities. The explainability of the proposed method allows system operators to design preventive controls for enhancing system stability.

Bayesian Neural Network↗
DOE OSTI2022

Physics-Informed Sparse Gaussian Process for Probabilistic Stability Analysis of Large-Scale Power System with Dynamic PVs and Loads

This work proposes a physics-informed sparse Gaussian process (SGP) for probabilistic stability assessment of large-scale power systems in the presence of uncertain dynamic PVs and loads. The differential and algebraic equations considering uncertainties from dynamic PVs and loads are reformulated to a nonlinear mapping relationship that allows the application of SGP. Thanks to the nonparametric characteristic of Gaussian process, the proposed framework does not require distributions of uncertain inputs and this distinguishes it from existing approaches. As the original Gaussian process is not scalable to large-scale systems with high dimensional uncertain inputs, this paper develops the SGP with a stochastic variational inference technique. It leads to approximately two orders of complex reduction. A data pre-processing step is also introduced to tackle the coexistence of stable and unstable cases by sample clustering and constructing separate SGPs. The probabilistic transient stability index is analyzed to assess system stability under different uncertain dynamics loads and PVs. Comparisons are performed with the sampling-based, the polynomial chaos expansion-based, and traditional Gaussian process-based methods on the modified IEEE 118-bus and Texas 2000-bus systems under various scenarios, including different levels of uncertainties and the existence of nonlinear correlations among dynamic PVs. The impacts of data quality and quantity issues are also investigated. It is shown that the proposed SGP achieves significantly improved computational efficiency while maintaining high accuracy with a limited number of data.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

A Laplace-Domain Circuit Model for Fault and Stability Analysis Considering Unbalanced Topology

For systems subject to unbalanced faults, analytical model building for stability assessment is a challenging task. This letter presents a straightforward modeling approach. A generalized dynamic circuit representation is achieved by use of the Laplacian transform variable s . Here, we translate the voltage and current relationship at the fault location into the relationship of three subsystems. The final circuit model is an interconnected sequence network with impedances in the Laplace domain. This circuit can be directly converted from a steady-state sequence network. This modeling procedure is illustrated by an example case of an induction motor served by a grid through a series compensated line. Electromagnetic transient simulation results demonstrate that sub-synchronous oscillations can be mitigated when a single-line to ground fault is applied at the motor terminal. Stability analysis results based on the dynamic circuit corroborate the simulation results. What's more, the derived circuit effortlessly reveals why unbalance can enhance stability.

42 ENGINEERING↗
DOE OSTI2023

Power System Recovery from Momentary Cessation with Transient Stability Improvement

Power system dynamics will be significantly changed by integrating wind farms and solar photovoltaic plants into power systems. This study investigates the effect of momentary cessation of inverter-based resources (IBRs) on transient stability and provides a recovery strategy for bulk IBRs in power systems. The theoretical analysis was initially carried out on a one-machine infinite-bus system, demonstrating the IBR impact in a critical group. The analysis was then expanded to a multimachine power system with IBRs using the single-machine equivalent method. The study found that IBRs in critical and noncritical groups exert contrasting effects on transient stability. Finally, a strategy for enhancing transient stability is proposed by controlling IBRs during power system recovery. The proposed strategy was verified by simulation on IEEE 9-bus and IEEE 39-bus power systems with the addition of IBRs. A 39-bus power system simulation demonstrates the scalability of the proposed method. Here, the proposed strategy provides effective and executable measures for improving system security in the presence of IBRs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Safe Reinforcement Learning-Based Transient Stability Control for Islanded Microgrids With Topology Reconfiguration

This paper proposes a safe reinforcement learning (RL)-based transient stability emergency control (TSEC) method for islanded microgrids. RL requires extensive interaction with the environment to learn control strategies, hence, a data-driven approach is used as a substitute for time-consuming time-domain simulation calculations. Deep sigma point processes (DSPP), which is a Gaussian process model, is utilized to predict the normal distribution of transient stability of microgrids and to construct a transient stability chance constraint. Reward-constrained policy optimization (RCPO) can simultaneously achieve objective prediction, policy learning, and constraint cost coefficient update across multiple timescales. RCPO interacts with the DSPP-based microgrid environment through a multi-process parallel manner, greatly increasing the training speed. Case studies on a real islanded microgrid demonstrate that the proposed method can efficiently and quickly obtain the optimal emergency control strategy while adhering to all hard constraints.

14 SOLAR ENERGY↗
DOE OSTI2024

Low-Level Liquid-Bearing Clouds Contribute to Seasonal Lower Atmosphere Stability and Surface Energy Forcing over a High-Mountain Watershed Environment

Measurements of atmospheric structure and surface energy budgets distributed along a high-altitude moun tain watershed environment near Crested Butte, Colorado, from two separate, but coordinated, field campaigns, Surface Atmosphere Integrated field Laboratory (SAIL) and Study of Precipitation, the Lower Atmosphere, and Surface for Hydrometeorology (SPLASH), are analyzed. This study identifies similarities and differences in how clouds influence the radiative budget over one snow-free summer season (2022) and two snow-covered seasons (2021/22; 2022/23) for this alpine location. A relationship between lower-tropospheric stability stratification and longwave radiative flux from the presence or absence of clouds is identified. When low clouds persisted, often with signatures of supercooled liquid in win ter, the lower troposphere experienced weaker stability, while radiatively clear skies that are less likely to be influenced by liquid droplets were associated with appreciably stronger lower-tropospheric stratification. Corresponding surface turbu lent heat fluxes partitioned differently based upon the cloud–stability stratification regime derived from early morning radiosounding profiles. Combined with the differences in the radiative budget largely resulting from dramatic seasonal dif ferences in surface albedo, the lower atmosphere stratification, surface energy budget, and near-surface thermodynamics are shown to be modified by the effective longwave radiative forcing of clouds. The diurnal evolution of thermodynamics and surface energy components varied depending on the early morning stratification state. Thus, the importance of quies cent versus synoptically active large-scale meteorology is hypothesized as a critical forcing for cloud properties and associ ated surface energy budget variations. The physical relationships between clouds, radiation, and stratification can provide a useful suite of metrics for process understanding and to evaluate numerical models in such an undersampled, highly com plex terrain environment.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

G4Boost: a machine learning-based tool for quadruplex identification and stability prediction

Background: G-quadruplexes (G4s), formed within guanine-rich nucleic acids, are secondary structures involved in important biological processes. Although every G4 motif has the potential to form a stable G4 structure, not every G4 motif would, and accurate energy-based methods are needed to assess their structural stability. Here, we present a decision tree-based prediction tool, G4Boost, to identify G4 motifs and predict their secondary structure folding probability and thermodynamic stability based on their sequences, nucleotide compositions, and estimated structural topologies. Results: G4Boost predicted the quadruplex folding state with an accuracy greater then 93% and an F1-score of 0.96, and the folding energy with an RMSE of 4.28 and R 2 of 0.95 only by the means of sequence intrinsic feature. G4Boost was successfully applied and validated to predict the stability of experimentally-determined G4 structures, including for plants and humans. Conclusion: G4Boost outperformed the three machine-learning based prediction tools, DeepG4, Quadron, and G4RNA Screener, in terms of both accuracy and F1-score, and can be highly useful for G4 prediction to understand gene regulation across species including plants and humans.

59 BASIC BIOLOGICAL SCIENCES↗