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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 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

The arbitrary order mixed mimetic finite difference method for the diffusion equation

Here, we propose an arbitrary-order accurate mimetic finite difference (MFD) method for the approximation of diffusion problems in mixed form on unstructured polygonal and polyhedral meshes. As usual in the mimetic numerical technology, the method satisfies local consistency and stability conditions, which determines the accuracy and the well-posedness of the resulting approximation. The method also requires the definition of a high-order discrete divergence operator that is the discrete analog of the divergence operator and is acting on the degrees of freedom. The new family of mimetic methods is proved theoretically to be convergent and optimal error estimates for flux and scalar variable are derived from the convergence analysis. A numerical experiment confirms the high-order accuracy of the method in solving diffusion problems with variable diffusion tensor. It is worth mentioning that the approximation of the scalar variable presents a superconvergence effect.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Transient Stability Preventive Control via Tuning the Parameters of Virtual Synchronous Generators

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.

Inverter-based resources, virtual synchronous gene↗
DOE OSTI2024

A Comprehensive Analysis of PINNs for Power System Transient Stability

The integration of machine learning in power systems, particularly in stability and dynamics, addresses the challenges brought by the integration of renewable energies and distributed energy resources (DERs). Traditional methods for power system transient stability, involving solving differential equations with computational techniques, face limitations due to their time-consuming and computationally demanding nature. This paper introduces physics-informed Neural Networks (PINNs) as a promising solution for these challenges, especially in scenarios with limited data availability and the need for high computational speed. PINNs offer a novel approach for complex power systems by incorporating additional equations and adapting to various system scales, from a single bus to multi-bus networks. Our study presents the first comprehensive evaluation of physics-informed Neural Networks (PINNs) in the context of power system transient stability, addressing various grid complexities. Additionally, we introduce a novel approach for adjusting loss weights to improve the adaptability of PINNs to diverse systems. Our experimental findings reveal that PINNs can be efficiently scaled while maintaining high accuracy. Furthermore, these results suggest that PINNs significantly outperform the traditional ode45 method in terms of efficiency, especially as the system size increases, showcasing a progressive speed advantage over ode45.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

A Comprehensive Analysis of PINNs for Power System Transient Stability

The integration of machine learning in power systems, particularly in stability and dynamics, addresses the challenges brought by the integration of renewable energies and distributed energy resources (DERs). Traditional methods for power system transient stability, involving solving differential equations with computational techniques, face limitations due to their time-consuming and computationally demanding nature. This paper introduces physics-informed Neural Networks (PINNs) as a promising solution for these challenges, especially in scenarios with limited data availability and the need for high computational speed. PINNs offer a novel approach for complex power systems by incorporating additional equations and adapting to various system scales, from a single bus to multi-bus networks. Our study presents the first comprehensive evaluation of physics-informed Neural Networks (PINNs) in the context of power system transient stability, addressing various grid complexities. Additionally, we introduce a novel approach for adjusting loss weights to improve the adaptability of PINNs to diverse systems. Our experimental findings reveal that PINNs can be efficiently scaled while maintaining high accuracy. Furthermore, these results suggest that PINNs significantly outperform the traditional ode45 method in terms of efficiency, especially as the system size increases, showcasing a progressive speed advantage over ode45.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2015

Excess entropy and crystallization in Stillinger-Weber and Lennard-Jones fluids

Molecular dynamics simulations are used to contrast the supercooling and crystallization behaviour of monatomic liquids that exemplify the transition from simple to anomalous, tetrahedral liquids. As examples of simple fluids, we use the Lennard-Jones (LJ) liquid and a pair-dominated Stillinger-Weber liquid (SW{sub 16}). As examples of tetrahedral, water-like fluids, we use the Stillinger-Weber model with variable tetrahedrality parameterized for germanium (SW{sub 20}), silicon (SW{sub 21}), and water (SW{sub 23.15} or mW model). The thermodynamic response functions show clear qualitative differences between simple and water-like liquids. For simple liquids, the compressibility and the heat capacity remain small on isobaric cooling. The tetrahedral liquids in contrast show a very sharp rise in these two response functions as the lower limit of liquid-phase stability is reached. While the thermal expansivity decreases with temperature but never crosses zero in simple liquids, in all three tetrahedral liquids at the studied pressure, there is a temperature of maximum density below which thermal expansivity is negative. In contrast to the thermodynamic response functions, the excess entropy on isobaric cooling does not show qualitatively different features for simple and water-like liquids; however, the slope and curvature of the entropy-temperature plots reflect the heat capacity trends. Two trajectory-based computational estimation methods for the entropy and the heat capacity are compared for possible structural insights into supercooling, with the entropy obtained from thermodynamic integration. The two-phase thermodynamic estimator for the excess entropy proves to be fairly accurate in comparison to the excess entropy values obtained by thermodynamic integration, for all five Lennard-Jones and Stillinger-Weber liquids. The entropy estimator based on the multiparticle correlation expansion that accounts for both pair and triplet correlations, denoted by S{sub trip}, is also studied. S{sub trip} is a good entropy estimator for liquids where pair and triplet correlations are important such as Ge and Si, but loses accuracy for purely pair-dominated liquids, like LJ fluid, or near the crystallization temperature (T{sub thr}). Since local tetrahedral order is compatible with both liquid and crystalline states, the reorganisation of tetrahedral liquids is accompanied by a clear rise in the pair, triplet, and thermodynamic contributions to the heat capacity, resulting in the heat capacity anomaly. In contrast, the pair-dominated liquids show increasing dominance of triplet correlations on approaching crystallization but no sharp rise in either the pair or thermodynamic heat capacities.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Determination of battery stability with advanced diagnostics

The increasing demand of lithium ion batteries for vehicle electrification is changing the typical use conditions that batteries may see. Over time, batteries may develop defects that are difficult to detect with traditional measurements. It is also possible that batteries may be left in an unknown state after failure of the monitoring system, loss of communication, or a potentially damaging event (such as an auto accident). It is therefore useful to explore other monitoring and interrogation methods that can better determine the stability of a battery in an unknown state. This work explores the use of electrochemical impedance spectroscopy as a method to determine the stability of batteries by observing changes in the complex impedance measurement as the cell is exposed to abusive conditions. Very dramatic changes to the internal resistance were observed when single cells were exposed to abusive conditions, suggesting that even single frequency impedance measurements could be effective with single cells. However tests on three cell series and parallel strings yielded smaller changes, primarily to the charge transfer resistance, showing that complex impedance measurements are more appropriate as the system increases in complexity. A rapid impedance tool developed at Idaho National Laboratory was tested and compared to traditional potentiostat tools as well. This was shown to yield similar data to the traditional tools, providing a potential method for continuous monitoring of a battery system. It was observed, however, that shifts in the data are difficult to detect in very transient systems.

25 ENERGY STORAGE↗
DOE OSTI2014

Thermal and mechanical stability of zeolitic imidazolate frameworks polymorphs

Theoretical studies on the experimental feasibility of hypothetical Zeolitic Imidazolate Frameworks (ZIFs) have focused so far on relative energy of various polymorphs by energy minimization at the quantum chemical level. We present here a systematic study of stability of 18 ZIFs as a function of temperature and pressure by molecular dynamics simulations. This approach allows us to better understand the limited stability of some experimental structures upon solvent or guest removal. We also find that many of the hypothetical ZIFs proposed in the literature are not stable at room temperature. Mechanical and thermal stability criteria thus need to be considered for the prediction of new MOF structures. Finally, we predict a variety of thermal expansion behavior for ZIFs as a function of framework topology, with some materials showing large negative volume thermal expansion.

36 MATERIALS SCIENCE↗
DOE OSTI2016

A lithium–oxygen battery based on lithium superoxide

Batteries based on sodium superoxide and on potassium superoxide have recently been reported(1-3). But, there have been no reports of a battery based on lithium superoxide (LiO 2 ), despite much research(4-8) into the lithium-oxygen (Li-O 2 ) battery because of its potential high energy density. Several studies(9-16) of Li-O 2 batteries have found evidence of LiO 2 being formed as one component of the discharge product along with lithium peroxide (Li 2 O 2 ). In addition, theoretical calculations have indicated that some forms of LiO 2 may have a long lifetime(17). Our studies also suggest that it might be possible to form LiO 2 alone for use in a battery. However, solid LiO 2 has been difficult to synthesize in pure form(18) because it is thermodynamically unstable with respect to disproportionation, giving Li 2 O 2 (refs 19, 20). We show that crystalline LiO 2 can be stabilized in a Li-O 2 battery by using a suitable graphene-based cathode. Various characterization techniques reveal no evidence for the presence of Li 2 O 2 . A novel templating growth mechanism involving the use of iridium nanoparticles on the cathode surface may be responsible for the growth of crystalline LiO 2 . Our results demonstrate that the LiO 2 formed in the Li-O 2 battery is stable enough for the battery to be repeatedly charged and discharged with a very low charge potential (about 3.2 volts). We also anticipate that this discovery will lead to methods of synthesizing and stabilizing LiO 2 , which could open the way to high-energy-density batteries based on LiO 2 as well as to other possible uses of this compound, such as oxygen storage.

25 ENERGY STORAGE↗
DOE OSTI2018

Possible Presence of a Third Body in the Kepler K2 Variable EPIC 202073314

We report the presence of an unseen third-body companion in a low-mass-ratio deep contact binary system Kepler K2 EPIC 202073314 as seen by the presence of the light time effect (LITE) on the O–C diagram. The system is found to be exhibiting an increasing period trend along with a sinusoidal behavior of the O–C residuals owing to the LITE variations. The residuals are modeled initially assuming a circular orbit to obtain a third-body orbital period of ∼9.75 years. We further performed a rigorous analysis by allowing the eccentricity to vary, which led to a third-body orbital period of ∼8.66 years with e {sub 3} = 0.51. We also report the photometric study of this variable. The system is found to have a mass ratio of ∼0.15 with an inclination of ∼77°. Monte-Carlo simulations were performed to verify the consistency of the obtained photometric solution. The system is considered to be in significant geometrical contact as seen by the high fill-out factor of ∼57%. Magnetic inactivity of the system is understood in terms of the absence of O’ Connell effect and lack of fill-in effect in the Hα spectral line. The dynamical state of the system is discussed in terms of the Hut’s stability criteria (((J{sub spin})/(J{sub orb}))=(1/3)) as the low-mass and high fill-out factor configuration of the system makes it a promising candidate in the context of stellar mergers. Assuming conservative mass transfer, the system is expected to meet the critical mass ratio of ∼0.07–0.09 in ∼10{sup 6} years.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Grid stabilization using adjusted voltage regulator response to grid characteristics

Apparatus and methods are disclosed for control systems for improving stability of electrical grids by temporarily reducing voltage output of electrical generators responsive to transient events on an electrical grid. In one example of the disclosed technology, a controller is coupled is to an automatic voltage regulator, which in turn adjusts excitation current of an electrical generator responsive to changes in frequency detected for the electrical grid. Reducing the output voltage temporarily allows for smaller generators to provide power to the microgrid. Methods for selecting parameters determining how the controller generates a regulation signal used to adjust the excitation current are further disclosed.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Scalable Programming Workflows for Validation of Quantum Computers

Hybrid quantum-classical workflows have become standard methods for executing variational algorithms and other quantum simulation techniques, which are key applications for noisy intermediate scale quantum (NISQ) computers. Validating these simulations is an important task which helps gauge the progress of quantum computer development, and classical simulation can serve as a tool to this end. Both exact and more scalable approximate methods with quantifiable error bounds can be used in validation tasks where the applicable metrics include the distance from a calculable ground truth, the quality of an error model fit to data, etc. Here we present a library extension that includes methods for validation of quantum simulations based on scalable hybrid workflows executable on high performance computers. We provide examples that use approximate methods based on tensor networks and stabilizer simulators to bound the error of quantum simulations on NISQ hardware.

Nguyen, Thien↗
DOE OSTI2024

Open‐Source Anaerobic Digestion Modeling Platform, Anaerobic Digestion Model No. 1 Fast (ADM1F)

An open‐source modeling platform, called Anaerobic Digestion Model No. 1 Fast (ADM1F), is introduced to achieve fast and numerically stable simulations of anaerobic digestion processes. ADM1F is compatible with an iPython interface to facilitate model configuration, simulation, data analysis, and visualization. Faster simulations and more stable results are accomplished by implementing an advanced open‐source library of numerical methods called Portable Extensive Toolkit for Scientific Computation (PETSc) to solve the ADM1 system of equations. Leveraging PETSc, ADM1F can consistently complete a steady‐state simulation under 0.2 s, over 99% faster than a benchmark ADM1 model implemented with MATLAB while achieving agreement of model outputs within 1% of those obtained with the benchmark model. For dynamic simulations, however, ADM1F has a computational speed advantage only when the influent characteristics update more frequently than every 4 h. The ability of ADM1F to be useful as a tool to study anaerobic digestion systems is demonstrated through two example implementations of ADM1F: (1) a two‐phase co‐digestion scenario evaluating the impact of the organic loading rate and the substrate composition on reactor performance and stability, and (2) a conventional digester scenario assessing the effectiveness of recovery strategies after disruptions that led to instability. These examples demonstrate how the high simulation speed and the convenience of the iPython interface allow ADM1F to complete complex analyses within minutes, much faster than computational strategies currently reported in the literature.

anaerobic co-digestion↗
DOE OSTI2025

Biochemical properties of glycerol kinase from the hypersaline-adapted archaeon Haloferax volcanii

ABSTRACT Extremophilic microorganisms are promising candidates for industrial and analytical biocatalysis.Haloferax volcanii, a halophilic archaeon that prefers glycerol over glucose, channels this substrate into central metabolism through glycerol kinase (GK). Here, we report the biochemical properties ofH. volcaniiGK and its potential for biotechnological applications. An N-terminal His-tagged GK was functionalin vivoand yielded 3 mg/L culture—4.5 times more enzyme than a C-terminal StrepII-tagged version. Size exclusion chromatography revealed a glycerol-induced oligomeric shift from homodimer to a dimer-dominant state with detectable tetramer. The purified enzyme showed robust activity across broad pH and salinity ranges, with optimal activity at 100 mM NaCl and 50°C–60°C. It retained catalytic activity in 5%–10% dimethyl sulfoxide (DMSO) and crude glycerol containing methanol. His-GK was freeze-thaw stable and thermotolerant in 2 M NaCl buffers. In the absence of ligands, the enzyme’s melting temperature (T m ) was 80°C. Glycerol increased the T m to 85°C, and combinations with MgCl₂ (84°C) or ATP (88°C) provided further stabilization. The highest T m (89°C) occurred with all three ligands, suggesting a cumulative stabilizing effect. Kinetic analyses revealed positive cooperativity for glycerol, ATP, and Mg² + ; Mn² + and Co² + also supported the activity.H. volcaniiGK is the first known GK to exhibit positive cooperativity with glycerol and ATP. Its high stability and substrate flexibility support its use in biodiesel waste valorization,in vitrobiocatalysis, and biosensor development—applications demanding robust, specific, and stable enzymes. IMPORTANCE This study reveals thatH. volcaniiGK exhibits positive cooperativity for glycerol, ATP, and Mg² + , a kinetic feature not previously reported for glycerol kinases. This behavior enables steep, switch-like responses to small substrate changes, offering unique advantages for biosensor design. Importantly,H. volcaniiGK also maintains high activity under extreme salinity, temperature, broad pH, and solvent conditions that typically limit enzyme use in industrial and environmental applications. These traits make this GK an ideal candidate for enzyme-based biosensors, which often suffer from poor tolerance to pH, solvent, and thermal stress. Its robustness supports its use in cross-linked enzyme crystals, an immobilization method that enhances enzyme stability and reusability under harsh conditions. Moreover, GKs are already employed in Mg² + detection kits; however,H. volcaniiGK’s ability to tolerate and respond to diverse divalent cations (e.g., Co² + , Mn² + ) broadens their potential for pollutant detection and environmental monitoring. These features collectively positionH. volcaniiGK as a valuable biocatalyst for biosensing,in vitrodiagnostics, and biotechnological applications requiring both precision and durability.

Biotechnology & Applied Microbiology↗
DOE OSTI2018

The influence of synthesis method on the microstructure and catalytic performance of Y0.07Sr0.93Ti0.8Fe0.2O3-δ in synthetic biogas operated solid oxide fuel cells

Highlights: • Fabrication method leads to differences in phase composition and chemical stability. • Grain size and their distribution in a catalytic layer were different. • The best long-term stability in biogas showed a Pechini-method fabricated material. - Abstract: The Y{sub 0.07}Sr{sub 0.93}Ti{sub 0.8}Fe{sub 0.2}O{sub 3-δ} (YSTF) material was fabricated using three different synthesis methods: modified polymer precursor method (MPP), Pechini method and a solid state reaction method. It was applied as an anode catalytic material for biogas reforming in solid oxide fuel cells. Clear differences in the microstructure of fabricated catalytic layers were found, mainly with respect to a grain size and distribution of grains. This led to some differences in biogas diffusion through the layer as well as in an amount of active sites for a biogas reforming. Also different chemical stability of each compound was observed in the fuel cell operating conditions. The best long-term stability in biogas was found for a fuel cell with the YSTF{sub P}echini catalytic layer (sintered in air at 1100 °C for 2 h) and the lowest one for a fuel cell with the YSTF{sub M}PP layer.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Machine learning method for enforcing variable independence in background estimation with LHC data: ABCDisCoTEC

A novel solution is presented for the problem of estimating the backgrounds of a signal search using observed data while simultaneously maximizing the sensitivity of the search to the signal. The 'ABCD method' provides a reliable framework for background estimation by partitioning events into one signal-enhanced region (A) and three background-enhanced control regions (B, C, and D) via two smoothly varying, statistically independent variables. In practice, even slight correlations between the two variables can significantly undermine the method's performance. Thus, choosing appropriate variables by hand can present a formidable challenge, especially when background and signal differ only subtly. To address this issue, the ABCD with distance correlation (ABCDisCo) method was developed to construct two learned variables via a neural network trained to provide strong signal-background discrimination with small values of the distance correlation (DisCo) measure between the two learned variables. However, relying solely on minimizing the DisCo can result in learned variables that may not have distributions of background events that are smoothly varying and localized at extreme values, as necessary for the validity of the background estimation. The ABCDisCo training enhanced with closure (ABCDisCoTEC) method is introduced to solve this issue by directly minimizing the nonclosure, expressed as a dedicated differentiable loss term. This extended method is applied to a data set of proton-proton collisions at a center-of-mass energy of 13 TeV recorded by the CMS detector at the CERN Large Hadron Collider. Additionally, given the complexity of the minimization problem with constraints on multiple loss terms, the modified differential method of multipliers is applied and shown to greatly improve the stability and robustness of the ABCDisCoTEC method, compared to grid search hyperparameter optimization procedures.

Hayrapetyan, Aram [Yerevan Phys. Inst.]↗
DOE OSTI2022

Fast Solution of Fully Implicit Runge--Kutta and Discontinuous Galerkin in Time for Numerical PDEs, Part II: Nonlinearities and DAEs

Fully implicit Runge--Kutta (IRK) methods have many desirable accuracy and stability properties as time integration schemes, but high-order IRK methods are not commonly used in practice with large-scale numerical PDEs because of the difficulty of solving the stage equations. This paper introduces a theoretical and algorithmic framework for solving the nonlinear equations that arise from IRK methods (and discontinuous Galerkin discretizations in time) applied to nonlinear numerical PDEs, including PDEs with algebraic constraints. Several new linearizations of the nonlinear IRK equations are developed, offering faster and more robust convergence than the often-considered simplified Newton, as well as an effective preconditioner for the true Jacobian if exact Newton iterations are desired. Inverting these linearizations requires solving a set of block 2 x 2 systems. Under quite general assumptions, it is proven that the preconditioned 2 x 2 operator's condition number is bounded by a small constant close to one, independent of the spatial discretization, spatial mesh, and time step, and with only weak dependence on the number of stages or integration accuracy. Moreover, the new method is built using the same preconditioners needed for backward Euler-type time stepping schemes, so can be readily added to existing codes. The new methods are applied to several challenging fluid flow problems, including the compressible Euler and Navier--Stokes equations, and the vorticity-streamfunction formulation of the incompressible Euler and Navier--Stokes equations. Up to 10th-order accuracy is demonstrated using Gauss IRK, while in all cases fourth-order Gauss IRK requires roughly half the number of preconditioner applications as required by standard Singly diagonally implicit Runge--Kutta methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Direct implicit and explicit energy-conserving particle-in-cell methods for modeling of capacitively coupled plasma devices

Achieving large-scale kinetic modeling is a crucial task for the development and optimization of modern plasma devices. With the trend of decreasing pressure in applications, such as plasma etching, kinetic simulations are necessary to self-consistently capture the particle dynamics. The standard, explicit, electrostatic, momentum-conserving particle-in-cell method suffers from restrictive stability constraints on spatial cell size and temporal time step, requiring resolution of the electron Debye length and electron plasma period, respectively. This results in a very high computational cost, making the technique prohibitive for large volume device modeling. We investigate the direct implicit algorithm and the explicit energy conserving algorithm as alternatives to the standard approach, both of which can reduce computational cost with a minimal (or controllable) impact on results. These algorithms are implemented into the well-tested EDIPIC-2D and LTP-PIC codes, and their performance is evaluated via 2D capacitively coupled plasma discharge simulations. The investigation reveals that both approaches enable the utilization of cell sizes larger than the Debye length, resulting in a reduced runtime, while incurring only minor inaccuracies in plasma parameters. The direct implicit method also allows for time steps larger than the electron plasma period; however, care must be taken to avoid numerical heating or cooling. It is demonstrated that by appropriately adjusting the ratio of cell size to time step, it is possible to mitigate this effect to an acceptable level.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2014

Magnetic behavior in Cr{sub 2}@Ge{sub n} (1≤n≤12) clusters: A density functional investigation

With a goal to produce magnetic moment in Cr{sub 2} Doped Ge{sub n} clusters which will be useful for practical applications, we have considered the structure and magnetic properties of Pure Germanium clusters and substitutionally doped it with Cr dimer to produce Cr{sub 2}@Ge{sub n} clusters. As the first step of calculation, geometrical optimizations of the nanoclusters have been done. These optimized geometries have been used in calculate the average binding energy per atom (BE), HOMO-LUMO gap and hence the relative stability of the clusters. These parameters have been demonstrated as structural and electronic properties of the clusters. Gap between highest occupied molecular orbital and lowest unoccupied molecular orbital indicate cluster to be a potential motif for generating magnetic cluster assembled materials. Based on these values a comparative study on different sized clusters has been done in order to understand the origin of structures, electronic and magnetic properties of Cr{sub 2}@Ge{sub n} nanoclusters.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗