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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 19 records

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DOE OSTI2020

An Online Search Method for Representative Risky Fault Chains Based on Reinforcement Learning and Knowledge Transfer

In the analysis of cascading outages and blackouts in power systems, risky cascading fault chains should be accurately identified in order to do further block or alleviate blackouts. However, the huge computational burden makes online analysis difficult. In this paper, an online search method for representative risky fault chains based on reinforcement learning and knowledge transfer is proposed. This method aims at promoting efficiency by exploiting similarities of adjacent power flow snapshots in operations. After the “representative risky fault chain” is defined, a framework of tree search based on Markov Decision Process and Q-learning is constructed. The knowledge in past runs is accumulated offline and then applied online, with a mechanism of knowledge transition and extension. The proposed learning based approach is verified on an illustrative 39-bus system with different loading levels, and simulations are carried out on a realworld 1000-bus power grid in China to show the effectiveness and efficiency of the proposed approach.

Blackout↗

DOE OSTI2020

A software package for modeling and simulating fault graphs

This report describes a novel fault graph modeling language and a simulation tool for executing models specified in the language. The modeling language has three primary features that distinguish it from similar reliability analysis tools. These are (1) a random variable modeling several distinct outcomes of a single fault; (2) chains of faults in which one fault triggers another; and (3) time to fail sampled from probability distributions including positive normal, exponential, Weibull with a minimum, or immediate. These features are motivated by their use in a historical analysis of centrifuge reliability.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Fault Graph (fg)

This software package offers a novel fault graph modeling language and a simulation tool for executing models specified in the language. The modeling language has three primary features that distinguish it from similar reliability analysis tools. These are (1) a random variable modeling several distinct outcomes of a single fault; (2) chains of faults in which one fault triggers another; and (3) time to fail sampled from probability distributions including positive normal, exponential, Weibull with a minimum, or immediate.

Nutaro, James↗

DOE OSTI2022

Fault Diagnosis of Double Pitch Time-Sharing Meshing Toothed Conveyor Chain Transmission System Based on Neural Network

With the rapid development of industry, the production and demand of automobiles have increased significantly. The generation of cars often requires tens of thousands of processes, consisting of hundreds of assembly lines to complete. Chain conveyors are widely used in the transportation of automobile assembly lines. The existing conveyor chains are roller chains. With the improvement of the requirements for conveyor reliability, synchronization, and environmental friendliness, the characteristics of roller conveyor chains restrict the further development of chain conveyors. It is urgent to study a new conveyor chain system to improve the synchronization, reliability, and environmental friendliness of chain conveyors on hundreds of assembly lines. In this paper, the mathematical modeling, meshing analysis, reliability, and environmental friendliness of the parameters of the components of the double pitch time-sharing meshing toothed conveyor chain system are studied. In addition, a novel fault diagnosis method of double pitch time-sharing meshing toothed conveyor chain transmission system based on neural network model is proposed in this paper.

Ding, Song↗

DOE OSTI2020

Stacking Faults and Short-Range Magnetic Correlations in Single Crystal Y 5 Ru 2 O 12 : A Structure with Ru +4.5 One-Dimensional Chains

In this paper, the synthesis, structure, and physical properties of Y 5 Ru 2 O 12 , a new member of the Ln 5 B 2 O 12 class (Ln = lanthanide, B = Ru, Re, Mo) are reported. Single crystals of Y 5 Ru 2 O 12 are synthesized using a high-temperature, high-pressure (700 °C, 200 MPa) hydrothermal method. The structure features edge-sharing Ru—O—Ru 1D chains of distorted RuO6 octahedra. The YO n (n = 6 and 7) polyhedral groups bridge Ru—O—Ru chains across the unit cell by forming a complex 3D structure. The Ru—O—Ru chains contain alternating shorter and longer Ru—Ru distances along the chain. Single crystal neutron diffraction shows streak-like diffuse scattering along the H-direction, due to stacking faults. Temperature-dependent anisotropic magnetic measurements reveal a broad feature over a wide temperature range, with a maximum at ≈70 K indicating potential short-range ordering, with canted antiferromagnetic behavior below 30 K. The dominant magnetic interactions are antiferromagnetic with a large negative Weiss temperature θ ≈ –200 K. The compound has an effective magnetic moment that is anomalously large for this class of compounds (≈4 μ B Ru –1 ), and a phenomenological spin Hamiltonian describing the unusual anisotropic magnetization of Y 5 Ru 2 O 12 is proposed.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Anomalous Ferromagnetic Behavior in Orthorhombic Li 3 Co 2 SbO 6

Monoclinic Li 3 Co 2 SbO 6 has been proposed as a Kitaev spin liquid candidate and investigated intensively, whereas the properties of its polymorph, the orthorhombic phase, are less known. In this work, we report the magnetic properties of orthorhombic Li 3 Co 2 SbO 6 as revealed by dc and ac magnetic susceptibility, muon spin relaxation (μSR), and neutron diffraction measurements. Successive magnetic transitions at 115, 89, and 71 K were observed in the low-field dc susceptibility measurements. The transitions below T N (115 K) are suppressed at higher applied fields. However, zero-field ac susceptibility measurements reveal distinct frequency-independent transitions at about 114, 107, 97, 79, and 71 K. A long-range magnetic ordered state was confirmed by specific heat, μSR, and neutron diffraction measurements, all indicating a single transition at about 115 K. The discrepancy between different measurements is attributed to possible stacking faults and/or local disorders of the ferromagnetic zigzag chains, resulting in ferromagnetic boundaries within the overall antiferromagnetic matrix.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Pairwise‐Parallel Entangling Gates on Orthogonal Modes in a Trapped‐Ion Chain

Abstract Parallel operations are important for both near‐term quantum computers and larger‐scale fault‐tolerant machines because they reduce execution time and qubit idling. This study proposes and implements a pairwise‐parallel gate scheme on a trapped‐ion quantum computer. The gates are driven simultaneously on different sets of orthogonal motional modes of a trapped‐ion chain. This work demonstrates the utility of this scheme by creating a Greenberger‐Horne‐Zeilinger (GHZ) state in one step using parallel gates with one overlapping qubit. It also shows its advantage for circuits by implementing a digital quantum simulation of the dynamics of an interacting spin system, the transverse‐field Ising model. This method effectively extends the available gate depth by up to two times with no overhead when no overlapping qubit is involved, apart from additional initial cooling. This scheme can be easily applied to different trapped‐ion qubits and gate schemes, broadly enhancing the capabilities of trapped‐ion quantum computers.

Optics↗

DOE OSTI2026

Wildfire-Power Grid Interactions: Feedback, Impacts, Monitoring, Modeling, and Mitigation Strategies

Wildfires are increasingly interacting with electric power systems through a two-way hazard chain: fires damage grid assets and trigger cascading outages, while grid faults can ignite new fires under hot, dry, and windy conditions. This review synthesizes the state of knowledge across five domains: (i) physical impacts of flames, heat, and smoke on lines, towers, insulators, and substations; (ii) power-infrastructure-initiated ignitions via conductor clash, high-impedance faults, and corona discharge; (iii) widespread blackouts and disproportionate societal impacts; (iv) multi-scale monitoring spanning laboratory tests, in-situ and grid-integrated sensors, and Earth observation; (v) coupled modeling that links fire behavior with grid operations; and (vi) technological and strategic mitigation pathways spanning prevention, response, and recovery. We integrate these domains into a novel 'feedback-aware' socio-technical framework. Through a longitudinal analysis (2005-2025) of global incidents, we identify that while vegetation contact remains the most frequent ignition source, aging infrastructure failure has emerged as a critical driver of catastrophic 'mega-fires'. We further identify persistent gaps, including limited interoperability of high-frequency grid and environmental data, scarce real-time data assimilation, and under-developed equity metrics for outage management. We conclude by outlining a research agenda to (1) deploy interoperable sensing architectures, (2) advance feedback-coupled fire-grid simulations, and (3) evaluate mitigation portfolios through techno-economic and fairness lenses. Recognizing wildfire-grid interactions as coupled socio-technical systems is essential for protecting infrastructure and communities and for ensuring reliable, sustainable electricity in a changing world.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

IC Project: w19_hossfault “Modelling of stick-slip behavior in sheared granular fault gouge & nonlinear elasticity behavior in cracked solid”

Low frequency earthquakes, non-volcanic tremor, and acoustic emissions are examples of weak seismic signals that may help detect major seismic events, i.e., earthquakes. In a laboratory setting, in which stick-slip events are simulated, acoustic emissions are detected far from the stick-slip events. In both, field and laboratory scale cases, the acoustic emission signals are sourced or detected in a volume remote from the volume that spawns the earthquake. Therefore, it is relevant to establish the causal relationship between signals detected on passive, remote monitors and the dynamics of the elastic structures that launch important seismic events. The work conducted under this IC allocation allowed us to utilize a numerical model that let us follow this causality, i.e., examine and connect the dynamics in a granular system (fault gouge), to signals detected on passive remote monitors. It was demonstrated that stress chains are key in the dynamics of granular systems and that their evolution is the source of the acoustic emission.

58 GEOSCIENCES↗

DOE OSTI2022

Development of Fixtures and Methods to Assess the Durability of Balance of Systems Components

The degradation of photovoltaic (PV) balance of systems (BoS) components is not well studied, but the consequences include offline modules, strings, and inverters; system shutdown; arc faults; and fires. A utility provider experienced a ~30% failure rate in their power transfer chain, originally attributed to branch connectors. Field-failed specimen assemblies were, therefore, examined, consisting of cable connector, branch connector, and discrete fuse components. In this study, unused field-vintage specimens are examined using a benchtop prototype fixture to identify the most influential environmental stressors on BoS components as well as the effect of external mechanical perturbation. The prototype fixture was used to develop a perturbation capability for future use in the combined-accelerated stress testing chamber. The benchtop experiments were also used to develop the in-situ data acquisition of specimen current, voltage, and temperature. A significant increase in operating temperature (~100 °C from ~40 °C) and a different failure mode (arcing at the metal pins rather than overheating of the fuse filament) were observed promptly once periodic mechanical perturbation was applied. The current at failure was decreased from 35 A (measured for static specimens, with failure occurring in the fuses) to 15 A (for tests with mechanical perturbation, with failure at the male/female metal pin connection). After initial examination using X-ray computed tomography, the external plastic was machined away from failed specimens to allow for failure analysis, including the extraction of the internal convolute springs for morphological examination (optical and electron microscopy). Chemical composition analysis included energy-dispersive X-ray spectroscopy, differential scanning calorimetry, and Fourier transform infrared spectroscopy.

14 SOLAR ENERGY↗

DOE OSTI2022

Evaluating the Durability of Balance of Systems Components Using Combined-Accelerated Stress Testing

The degradation of photovoltaic (PV) balance of systems (BoS) components is not well-studied, but the consequences include offline modules, strings, and inverters; system shutdown; arc faults; and fires. A utility provider experienced a ~30% failure rate in their power transfer chain, originally attributed to branch connectors. Field-failed specimen assemblies were therefore examined, consisting of cable connector, branch connector, and discrete fuse components. In this study, unused field-vintage specimens are examined using combined-accelerated stress testing (C-AST) to clarify the most influential environmental stressors as well as the effect of external mechanical perturbation. A benchtop prototype fixture was used to develop the perturbation capability for the C-AST chamber. The benchtop experiments were also used to develop the in-situ data acquisition of specimen current, voltage, and temperature. A significant increase in operating temperature (~100 degrees C from ~40 degrees C) and a different failure mode were observed promptly once periodic mechanical perturbation was applied. The current at failure was decreased from 35 A (with failure in the fuses) to 15 A (failure at the male/female metal pin connection). After initial examination using X-ray computed tomography, the external plastic was machined away from failed specimens to allow for failure analysis, including the extraction of the internal convolute springs for morphological examination (optical and electron microscopy).

balance of systems↗

DOE OSTI2022

Evaluating the Durability of Balance of Systems Components Using Combined-Accelerated Stress Testing

The degradation of photovoltaic (PV) balance of systems (BoS) components is not well-studied, but the consequences include: offline-modules, -strings, -inverters; system shutdown; arc-faults; and fires. A utility provider experienced a ~30% failure rate in their power transfer chain, attributed to branch connectors. Field-failed specimen assemblies were therefore examined, consisting of cable connector, branch connector and discrete fuse components. Unused field-vintage specimens are presently being examined using combined-accelerated stress testing (C-AST) to clarify the most influential environmental stressors as well as the effect of external mechanical perturbation. A benchtop prototype fixture was used to develop the perturbation capability for C-AST. The benchtop experiments were also used to develop the in-situ data acquisition of specimen: current, voltage, and temperature. A significant increase in operating temperature, ~100 deg C from ~40 deg C, and a different failure mode was observed immediately once periodic mechanical perturbation was applied. The current at failure was decreased from 35 A (with failure occurring in the fuses) to 15 A (failure at the male/female metal pin connection). After initial examination using X-ray computed tomography, the external plastic was machined away from failed specimens to allow failure analysis, including the extraction of the internal convolute springs for morphological examination (optical- and electron-microscopy). Chemical composition analysis included: energy-dispersive X-ray spectroscopy, differential scanning calorimetry, and Fourier transform infrared spectroscopy.

balance of systems↗

DOE OSTI2022

Evaluating the Durability of Balance of Systems Components Using Combined-Accelerated Stress Testing: Preprint

The degradation of photovoltaic (PV) balance of systems (BoS) components is not well-studied, but the consequences include: offline-modules, -strings, -inverters; system shutdown; arc-faults; and fires. A utility provider experienced a ~30% failure rate in their power transfer chain, originally attributed to branch connectors. Field-failed specimen assemblies were therefore examined, consisting of cable connector, branch connector, and discrete fuse components. Unused field-vintage specimens are presently being examined using combined-accelerated stress testing (C-AST) to clarify the most influential environmental stressors as well as the effect of external mechanical perturbation. A benchtop prototype fixture was used to develop the perturbation capability for the C-AST chamber. The benchtop experiments were also used to develop the in-situ data acquisition of specimen: current, voltage, and temperature. A significant increase in operating temperature, ~100 deg C from ~40 deg C, and a different failure mode was observed promptly once periodic mechanical perturbation was applied. The current at failure was decreased from 35 A (with failure in the fuses) to 15 A (failure at the male/female metal pin connection). After initial examination using X-ray computed tomography, the external plastic was machined away from failed specimens to allow failure analysis, including the extraction of the internal convolute springs for morphological examination (optical- and electron-microscopy).

balance of systems↗

DOE OSTI2022

Evaluating the Durability of Balance of Systems Components Using Combined-Accelerated Stress Testing

balance of systems↗

DOE OSTI2020

Capabilities of multivariate Bayesian inference toward seismic hazard assessment

Multivariate Bayesian analysis can bring significant benefits to seismic hazard analysis: Its multivariate feature enables computing scalar and vector hazard without making any approximations; Correlations between intensity measures are implicitly modeled, permitting direct simulation of ground motion selection tools such as the conditional mean spectrum and the generalized conditioning intensity measure; and Its updating feature enables a seamless integration of new ground motion data into the hazard results. Here, we first develop a multivariate Bayesian ground motion model through the NGA-West2 database. The model functional form considers fault-type, magnitude, and distance dependencies, and also the linear and the rock intensity dependent site response. We use a hybrid Markov Chain Monte Carlo sampling to perform Bayesian inference consisting of Gibbs step and a multilevel Metropolis-Hastings step. We then perform several checks on the model and note that its performance is satisfactory. Finally, we illustrate the merits of this multivariate Bayesian analysis, which include: ground motion model updating with ground motion data recorded in the last four years not part of the NGA-West2 database; computation of scalar and vector seismic hazard using the un-updated and updated ground motion models for Los Angeles, CA; and simulation of the conditional mean spectrum under scalar and vector IM conditioning while accounting for different sources of aleatoric and epistemic uncertainties.

58 GEOSCIENCES↗

DOE OSTI2021

Machine Learning and Economic Models to Enable Risk-Informed Condition Based Maintenance of a Nuclear Plant Asset

The primary objective of this research is to address challenges in the implementation of risk-informed, condition-based predictive maintenance (PdM), which reduces operating costs while still maintaining the safety and reliability of commercial nuclear power plants (NPPs). To achieve the objective, risk models are being developed by taking advantage of advancements in data analytics, deep learning, machine learning (ML), and artificial intelligence (AI). The notable outcomes presented in the report include ? Development of a ML models using heterogeneous plant process and vibration data collected at different spatial and temporal resolutions from the Salem?s CWS to diagnose a circulating water pump (CWP) failure based on salient fault signatures. The developed diagnostic models are extendable to other faults associated with CWPs and CWP motors given associated fault signatures. ? Development of a natural language processing (NLP) technique to automatically classify the WO data into different categories. The developed NLP technique was validated on independent WO data. This automates the tedious and time-consuming activity of mining and classifying WOs by subject matter experts. ? Estimation of mean time between downtime (i.e., time duration between time instances when 1 or more CWPs are not available) and developed an approach to establish reliability of CWS components using unstructured WO data along with CWS plant process data. ? Formulation of economic model based on Markov chain models. The parameters of associated with the transition rate between different states of Markov chain models were estimated using WO data. The economic model formulation and discussion captures both time-independent and time-dependent parameter variation, leading to risk-informed decision-making.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2021

Scalable Technologies Achieving Risk-Informed Condition-Based Predictive Maintenance Enhancing the Economic Performance of Operating Nuclear Power Plants

The primary objective of the research presented in this report is to develop scalable technologies that are deployable across plant assets and across the nuclear fleet to achieve risk-informed predictive maintenance (PdM) strategies at commercial nuclear power plants (NPPs). Over the years, the nuclear fleet has relied on labor-intensive and time-consuming preventive maintenance (PM) programs, driving up operation and maintenance (O&M) costs to achieve high capacity factors. A well-constructed risk-informed PdM approach for an identified plant asset has been developed in this research, taking advantage of advancements in data analytics, machine learning (ML), artificial intelligence (AI), physics-informed modeling, and visualization. These technologies would allow commercial NPPs to reliably transition from current labor-intensive PM programs to a technology driven PdM program, eliminating unnecessary O&M costs. The work presented in the report is being developed as part of a collaborative research effort between Idaho National Laboratory and Public Service Enterprise Group Nuclear, LLC. This report (1) reflects the results of work by LWRS Program researchers with PSEG, Nuclear LLC-owned Salem and Hope Creek Nuclear Power Plants; (2) presents utilization of circulating water system (CWS) heterogeneous data and fault modes from both the Salem and Hope Creek nuclear power plant sites to develop salient fault signatures associated with each fault mode; (3) describes the integration of component-level predictive models into a robust system-level model enabled by the federated-transfer learning; (4) describes the development of physics-informed model of circulating water pump and motor; (5) develops a scalable risk and economic model; and (6) outlines the development of a user-centric visualization application. The outcomes presented in this report lays the foundation and provides a much-needed technical basis to focus on explainability and trustworthiness of ML and AI-based technologies, as part of future research.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2020

Discontinuous Galerkin discretization for quantum simulation of chemistry

All-electron electronic structure methods based on the linear combination of atomic orbitals method with Gaussian basis set discretization offer a well established, compact representation that forms much of the foundation of modern correlated quantum chemistry calculations—on both classical and quantum computers. Despite their ability to describe essential physics with relatively few basis functions, these representations can suffer from a quartic growth of the number of integrals. Recent results have shown that, for some quantum and classical algorithms, moving to representations with diagonal two-body operators can result in dramatically lower asymptotic costs, even if the number of functions required increases significantly. We introduce a way to interpolate between the two regimes in a systematic and controllable manner, such that the number of functions is minimized while maintaining a block-diagonal structure of the two-body operator and desirable properties of an original, primitive basis. Techniques are analyzed for leveraging the structure of this new representation on quantum computers. Empirical results for hydrogen chains suggest a scaling improvement from O(N 4.5 ) in molecular orbital representations to O(N 2.6 ) in our representation for quantum evolution in a fault-tolerant setting, and exhibit a constant factor crossover at 15 to 20 atoms. Moreover, we test these methods using modern density matrix renormalization group methods classically, and achieve excellent accuracy with respect to the complete basis set limit with a speedup of 1–2 orders of magnitude with respect to using the primitive or Gaussian basis sets alone. These results suggest our representation provides significant cost reductions while maintaining accuracy relative to molecular orbital or strictly diagonal approaches for modest-sized systems in both classical and quantum computation for correlated systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗