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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Using Machine Learning for Quantum Annealing Accuracy Prediction

Quantum annealers, such as the device built by D-Wave Systems, Inc., offer a way to compute solutions of NP-hard problems that can be expressed in Ising or quadratic unconstrained binary optimization (QUBO) form. Although such solutions are typically of very high quality, problem instances are usually not solved to optimality due to imperfections of the current generations quantum annealers. In this contribution, we aim to understand some of the factors contributing to the hardness of a problem instance, and to use machine learning models to predict the accuracy of the D-Wave 2000Q annealer for solving specific problems. We focus on the maximum clique problem, a classic NP-hard problem with important applications in network analysis, bioinformatics, and computational chemistry. By training a machine learning classification model on basic problem characteristics such as the number of edges in the graph, or annealing parameters, such as the D-Wave’s chain strength, we are able to rank certain features in the order of their contribution to the solution hardness, and present a simple decision tree which allows to predict whether a problem will be solvable to optimality with the D-Wave 2000Q. We extend these results by training a machine learning regression model that predicts the clique size found by D-Wave.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Fueling the Future: The Emergence of Self-Powered Enzymatic Biofuel Cell Biosensors

Self-powered biosensors are innovative devices that can detect and analyze biological or chemical substances without the need for an external power source. These biosensors can convert energy from the surrounding environment or the analyte itself into electrical signals for sensing and data transmission. The self-powered nature of these biosensors offers several advantages, such as portability, autonomy, and reduced waste generation from disposable batteries. They find applications in various fields, including healthcare, environmental monitoring, food safety, and wearable devices. While self-powered biosensors are a promising technology, there are still challenges to address, such as improving energy efficiency, sensitivity, and stability to make them more practical and widely adopted. This review article focuses on exploring the evolving trends in self-powered biosensor design, outlining potential advantages and limitations. With a focal point on enzymatic biofuel cell power generation, this article describes various sensing mechanisms that employ the analyte as substrate or fuel for the biocatalyst’s ability to generate current. Technical aspects of biofuel cells are also examined. Research and development in the field of self-powered biosensors is ongoing, and this review describes promising areas for further exploration within the field, identifying underexplored areas that could benefit from further investigation.

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

Classification of Photovoltaic Failures with Hidden Markov Modeling, an Unsupervised Statistical Approach

Failure detection methods are of significant interest for photovoltaic (PV) site operators to help reduce gaps between expected and observed energy generation. Current approaches for field-based fault detection, however, rely on multiple data inputs and can suffer from interpretability issues. In contrast, this work offers an unsupervised statistical approach that leverages hidden Markov models (HMM) to identify failures occurring at PV sites. Using performance index data from 104 sites across the United States, individual PV-HMM models are trained and evaluated for failure detection and transition probabilities. This analysis indicates that the trained PV-HMM models have the highest probability of remaining in their current state (87.1% to 93.5%), whereas the transition probability from normal to failure (6.5%) is lower than the transition from failure to normal (12.9%) states. A comparison of these patterns using both threshold levels and operations and maintenance (O&M) tickets indicate high precision rates of PV-HMMs (median = 82.4%) across all of the sites. Although additional work is needed to assess sensitivities, the PV-HMM methodology demonstrates significant potential for real-time failure detection as well as extensions into predictive maintenance capabilities for PV.

classification↗
DOE OSTI2020

One Planet or Two Planets? The Ultra-sensitive Extreme-magnification Microlensing Event KMT-2019-BLG-1953

We present the analysis of a very high-magnification (A ∼ 900) microlensing event KMT-2019-BLG-1953. A single-lens single-source (1L1S) model appears to approximately delineate the observed light curve, but the residuals from the model exhibit small but obvious deviations in the peak region. A binary-lens (2L1S) model with a mass ratio of q ∼ 2 × 10{sup −3} improves the fits by Δχ {sup 2} = 181.8, indicating that the lens possesses a planetary companion. From additional modeling by introducing an extra planetary lens component (3L1S model) and an extra source companion (2L2S model), it is found that the residuals from the 2L1S model further diminish, but claiming these interpretations is difficult due to the weak signals with Δχ {sup 2} = 16.0 and 13.5 for the 3L1S and 2L2L models, respectively. From a Bayesian analysis, we estimate that the host of the planets has a mass of M{sub host}=0.31{sub −0.17}{sup +0.37} M{sub ⊙} and that the planetary system is located at a distance of D{sub L}=7.04{sub −1.33}{sup +1.10} kpc toward the Galactic center. The mass of the securely detected planet is M{sub p}=0.64{sub −0.35}{sup +0.76} M{sub J}. The signal of the potential second planet could have been confirmed if the peak of the light curve had been more densely observed by follow-up observations, and thus the event illustrates the need for intensive follow-up observations for very high-magnification events even in the current generation of high-cadence surveys.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Exoplanet Sciences with Nulling Interferometers and a Single-mode Fiber-fed Spectrograph

Understanding the atmospheres of exoplanets is a milestone to decipher their formation history and potential habitability. High-contrast imaging and spectroscopy of exoplanets is the major pathway toward the goal. Direct imaging of an exoplanet requires high spatial resolution. Interferometry has proven to be an effective way of improving spatial resolution. However, means of combining interferometry, high-contrast imaging, and high-resolution spectroscopy have been rarely explored. To fill in the gap, we present the dual-aperture fiber nuller (FN) for current-generation 8–10 m telescopes, which provides the necessary spatial and spectral resolution to (1) conduct follow-up spectroscopy of known exoplanets and (2) detect planets in debris-disk systems. The concept of feeding an FN to a high-resolution spectrograph can also be used for future space and ground-based missions. We present a case study of using the dual-aperture FN to search for biosignatures in rocky planets around M stars for a future space interferometry mission. Moreover, we discuss how an FN can be equipped on future extremely large telescopes by using the Giant Magellan Telescope as an example.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

On the Short-scale Spatial Variability of Electron Inflows in Electron-only Magnetic Reconnection in the Turbulent Magnetosheath Observed by MMS

We investigate the detailed properties of electron inflow in an electron-only reconnection event observed by the four Magnetospheric Multiscale (MMS) spacecraft in the Earth's turbulent magnetosheath downstream of the quasi-parallel bow shock. The lack of ion coupling was attributed to the small-scale sizes of the current sheets, and the observed bidirectional super-Alfvénic electron jets indicate that the MMS spacecraft crossed the reconnecting current sheet on both sides of an active X-line. Remarkably, the MMS spacecraft observed the presence of large asymmetries in the two electron inflows, with the inflows (normal to the current sheet) on the two sides of the reconnecting current layer differing by as much as a factor of four. Furthermore, even though the four MMS spacecraft were separated by less than seven electron skin depths, the degree of inflow asymmetry was significantly different at the different spacecraft. The asymmetry in the inflow speeds was larger with increasing distances downstream from the reconnection site, and the asymmetry was opposite on the two sides of the X-line. We compare the MMS observations with a 2D kinetic particle-in-cell (PIC) simulation and find that the asymmetry in the inflow speeds stems from in-plane currents generated via the combination of reconnection-mediated inflows and parallel flows along the magnetic separatrices in the presence of a large guide field.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Tearing-mediated Alfvénic Turbulence in a Relativistic Plasma

In astrophysical relativistic plasmas, Alfvénic turbulence exists across a wide range of scales. Similar to a nonrelativistic case, this turbulence can be influenced by the tearing instability. We argue that in an ultrarelativistic pair plasma the tearing effects become significant at the critical scale given by ${a}_{t}\sim {d}_{\mathrm{rel}}{\left({L}_{\perp }/{d}_{\mathrm{rel}}\right)}^{n/(4+5n)}$, where L ⊥ represents the outer scale of the turbulence and d rel the relativistic electron inertial scale. Here n = 1 corresponds to the Harris magnetic configurations, while n = 2 applies to localized (non-Harris) magnetic profiles of turbulence-generated current sheets. Below the critical scale, the energy spectrum of magnetic fluctuations steepens to W(k)dk ∝ k -(7n+2)/3n dk. However, this happens only when $\tilde{\sigma }\ll {\left({L}_{\perp }/{d}_{\mathrm{rel}}\right)}^{(2+4n)/(4+5n)}$, where $\tilde{\sigma }$ is the magnetization parameter based on the magnetic fluctuations. If the opposite inequality holds, the Alfvénic cascade is instead affected by charge starvation at scales below ${a}_{\mathrm{ch}}\sim {d}_{\mathrm{rel}}{\left({d}_{\mathrm{rel}}/{L}_{\perp }\right)}^{1/3}{\tilde{\sigma }}^{2/3}$, and the energy spectrum becomes steeper than W(k)dk ∝ k -3 dk. When d rel is replaced by its nonrelativistic equivalent, our results agree with the nonrelativistic analysis of N. F. Loureiro & S. Boldyrev (2018). In the Harris case n = 1, they agree with the recent relativistic studies by I. Demidov & Y. Lyubarsky.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Interaction of radio frequency waves with cylindrical density filaments -- scattering and radiation pressure

The propagation of radio-frequency (RF) waves in tokamaks can be affected by filamentary structures, or blobs, that are present in the edge plasma and the scrape-off layer. The difference in the permittivity between the surrounding plasma and interior of a filament leads to reflection, refraction and diffraction of the waves. This, in turn, can affect the power flow into the core of the plasma and reduce the efficiency of heating and/or current generation. The scattering of RF waves, lower hybrid, helicon and ion cyclotron waves, by a single cylindrical filament, embedded in a background plasma, is studied using a full-wave analytical theory developed previously (Ram & Hizanidis, Phys. Plasmas, vol. 23, 2016, 022504). The theory assumes that the plasma in and around a filament is homogeneous and cold. A detailed scattering analysis reveals a variety of common features that exist among the three distinctly different RF waves. These common attributes can be inferred intuitively based on an examination of the cold plasma dispersion relation. The physical intuition is a useful step to understanding experimental observations on scattering, as well as results from simulations that include general forms of edge plasma turbulence. While a filament can affect the propagation of RF waves, the radiation force exerted by the waves can influence the filament. The force on a filament is determined using the Maxwell stress tensor. In 1905, Poynting was the first to evaluate and measure the radiation force on an interface separating two different dielectric media (Poynting, London Edinburgh Dublin Philos. Mag. J. Sci., vol. 9, 1905, pp. 393–406). For ordinary light propagating in vacuum and incident on a glass surface, Poynting noted that the surface is ‘pulled’ towards the vacuum. In a magnetized cold plasma, there are two independent wave modes. Even if only one of these modes is excited by an RF antenna, a filament will couple power to the other mode: a consequence of electromagnetic boundary conditions. This facet of scattering has consequences on the radiation force that go beyond Poynting's seminal contribution. The direction of the force depends on the polarization of the incident wave and on the mode structure of the waves inside and in the vicinity of a filament. It can either pull the filament toward the RF source or push it away. For slow lower hybrid waves, filaments with densities greater than the ambient density are pulled in, while filaments with lower densities are pushed out, thereby enhancing the density in front of the antenna. In the case of fast helicon and ion cyclotron waves, the direction of the force depends on the plasma and wave parameters; in particular, on the ambient density. The radiation force, in all three frequency ranges, is large enough to affect the motion of a filament and could be measured experimentally. This also suggests the possibility of modifying the edge turbulence using RF waves.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Reflection and transmission of electromagnetic pulses at a planar dielectric interface -- theory and quantum lattice simulations

There is considerable interest in the application of quantum information science to advance computations in plasma physics. A particular point of curiosity is whether it is possible to take advantage of quantum computers to speed up numerical simulations relative to conventional computers. Many of the topics in fusion plasma physics are classical in nature. In order to implement them on quantum computers it will require couching a classical problem in the language of quantum mechanics. Electromagnetic waves are routinely used in fusion experiments to heat a plasma or to generate currents in the plasma. The propagation of electromagnetic waves is described by Maxwell equations with an appropriate description of the plasma as a dielectric medium. Before advancing to the tensor dielectric of a magnetized plasma, this paper considers electromagnetic wave propagation in a one-dimensional inhomogeneous scalar dielectric. The classic theory of scattering of plane electromagnetic waves at a planar interface, separating two different dielectric media, leads to Fresnel equations for reflection and transmission coefficients. In contrast to plane waves, this paper is on the reflection and transmission of a spatially confined electromagnetic pulse. Following an analytical formulation for the scattering of a Gaussian pulse, it is deduced that the maximum transmission coefficient for a pulse is $\sqrt{n_2/n_1}$ times that for a plane wave; the incident and transmitted pulses propagating in dielectric media with refractive indices $n_1$ and $n_2$, respectively. The analytical theory is complemented by numerical simulations using a quantum lattice algorithm for Maxwell equations. The algorithm, based on the Riemann-Silberstein-Weber representation of the electromagnetic fields and expressed in term of qubits, is an interleaved sequence of entangling operators at each lattice site and unitary streaming operators which transmit information from one site to an adjacent lattice site. Besides substantiating results from the theory for Gaussian pulses, numerical simulations show their validity for non-Gaussian pulses. Apart from their time-asymptotic forms, the simulations display an interplay between the incident, reflected, and transmitted pulses in the vicinity of the transition region between two dielectric media.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Putting Our Industry's Data to Work: A Case Study of Large-Scale Data Aggregation: Preprint

With increasing deployment of Advanced Metering Infrastructure (AMI), Building Automation System (BAS) controls, Internet of Things (IoT) network devices, and data-driven evaluation, measurement, and verification studies, the building sector is currently generating a staggering amount of energy-related data. In the right hands, these data sets can contribute to increased comfort and energy savings for building occupants and a more reliable electrical grid; however, due to a combination of factors, including significant privacy concerns, much of the data that are presently generated and stored are not used outside of basic operational applications. In the past year, our team has dedicated over 2,000 person-hours to accessing building energy data for a project funded by the U.S. Department of Energy (DOE) Building Technologies Office. We sought whole-building or end-use (e.g., lighting) timeseries data at the individual-building or equipment level where possible or aggregated information, such as timeseries averages and quartiles by building type (e.g., office, retail, hospital), where sharing individual building information was not an option. We are additionally working with IoT and BAS data sets to derive information important to the project. We have assembled an extensive data set that will enable the development of publicly available end-use load profiles to benefit the U.S. building and electricity industries. Here we present an overview of the data set that we have assembled to date, the motivators and approaches that got us here, and the lessons we learned through our efforts. We also discuss work underway that presents additional options for future data access.

building energy data↗
DOE OSTI2021

Leveraging Randomized Compiling for the QITE Algorithm

The success of the current generation of Noisy Intermediate-Scale Quantum (NISQ) hardware shows that quantum hardware may be able to tackle complex problems even without error correction. One outstanding issue is that of coherent errors arising from the increased complexity of these devices. These errors can accumulate through a circuit, making their impact on algorithms hard to predict and mitigate. Iterative algorithms like Quantum Imaginary Time Evolution are susceptible to these errors. This article presents the combination of both noise tailoring using Randomized Compiling and error mitigation with a purification. We also show that Cycle Benchmarking gives an estimate of the reliability of the purification. We apply this method to the Quantum Imaginary Time Evolution of a Transverse Field Ising Model and report an energy estimation and a ground state infidelity both below 1\%. Our methodology is general and can be used for other algorithms and platforms. We show how combining noise tailoring and error mitigation will push forward the performance of NISQ devices.

Ville, Jean-Loup↗
DOE OSTI2022

Irradiation Experiments and Thermal Analysis for Reactor System Design and Analysis at INL

Idaho National Laboratory (INL) is the nation's lead nuclear laboratory working to enhance reactor systems' safety, security, economics, and efficiency. Research and development (R&D) programs at INL support the current fleet of nuclear reactors for safer operation and newer reactors technology design, development, demonstration, and deployment. A major focus of INL's mission is the reactor system design and analysis supported by the irradiation experiments and thermal analysis of advanced and current-generation nuclear fuels and materials. The irradiation experiments and thermal analysis provide a deeper understanding of basic radiation damage processes that can determine the basis for performance improvements and verification of modeling assumptions. These experiments and analyses include experiment management: design, fabrication, characterization, irradiation, and post-irradiation examination. This research involves thermal, neutronic, and material investigation using the INL's Advanced Test Reactor (ATR) and Transient Reactor Test (TREAT) facilities. The results from these experiments and analysis are required to develop the regulatory basis for deploying new or modified fuels and materials. This seminar talk will also provide a general overview of the INL's research facilities, ongoing research programs, core capabilities, and opportunities for students and faculties.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Dynamic, resilient sensing system for automatic cyber-attack neutralization

An industrial asset may have monitoring nodes that generate current monitoring node values. An abnormality detection computer may determine that an abnormal monitoring node is currently being attacked or experiencing fault. A dynamic, resilient estimator constructs, using normal monitoring node values, a latent feature space (of lower dimensionality as compared to a temporal space) associated with latent features. The system also constructs, using normal monitoring node values, functions to project values into the latent feature space. Responsive to an indication that a node is currently being attacked or experiencing fault, the system may compute optimal values of the latent features to minimize a reconstruction error of the nodes not currently being attacked or experiencing a fault. The optimal values may then be projected back into the temporal space to provide estimated values and the current monitoring node values from the abnormal monitoring node are replaced with the estimated values.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Hydrogen Fuel Cell Electric Bus (FCEB) Evaluations in US Public Transit Service

The National Renewable Energy Laboratory (NREL) is a Department of Energy (DOE) national laboratory focused on renewable energy and energy efficiency. NREL has evaluated alternative fuel and advanced propulsion transit buses for DOE and the U.S. Department of Transportation's Federal Transit Administration (FTA). These evaluations are focused on determining the status of fuel cell systems and the corresponding infrastructure in transit applications to help DOE and FTA assess the progress toward technology readiness. For the last 19 years NREL has evaluated FCEBs in service around the United States and in Canada. The results of these evaluations have been published in numerous reports that compare FCEB performance to conventional technology as well as document the implementation experience and lessons learned by the transit agencies and their demonstration teams. Currently, 70 fuel cell buses are in active service in the US and 66 FCEBs are in development. NREL is evaluating a subset of the active FCEBs that includes three transit agencies demonstrating 25 fuel cell electric buses in California. One bus has exceeded 35,000 hours in service and 12 have exceeded 25,000 hours. Fuel economy for the current generation of FCEBs has improved 35% over the previous generation and is double that of conventional buses. Maintenance cost for FCEBs is equivalent to diesel and BEBs. The most up-to-date performance results will be presented, including fuel economy, availability, reliability, and operational costs.

bus↗
DOE OSTI2022

Dynamic, resilient virtual sensing system and shadow controller for cyber-attack neutralization

An industrial asset may have monitoring nodes (e.g., sensor or actuator nodes) that generate current monitoring node values. An abnormality detection and localization computer may receive the series of current monitoring node values and output an indication of at least one abnormal monitoring node that is currently being attacked or experiencing a fault. An actor-critic platform may tune a dynamic, resilient state estimator for a sensor node and output tuning parameters for a controller that improve operation of the industrial asset during the current attack or fault. The actor-critic platform may include, for example, a dynamic, resilient state estimator, an actor model, and a critic model. According to some embodiments, a value function of the critic model is updated for each action of the actor model and each action of the actor model is evaluated by the critic model to update a policy of the actor-critic platform.

Roychowdhury, Subhrajit↗
DOE OSTI2023

Virtual sensor supervised learning for cyber-attack neutralization

An industrial asset may have monitoring nodes that generate current monitoring node values. A dynamic, resilient estimator may split a temporal monitoring node space into normal and one or more abnormal subspaces associated with different kinds of attack vectors. According to some embodiments, a neutralization model is constructed and trained for each attack vector using supervised learning and the associated abnormal subspace. In other embodiments, a single model is created using out-of-range values for abnormal monitoring nodes. Responsive to an indication of a particular abnormal monitoring node or nodes, the system may automatically invoke the appropriate neutralization model to determine estimated values of the particular abnormal monitoring node or nodes (e.g., by selecting the correct model or using out-of-range values). The series of current monitoring node values from the abnormal monitoring node or nodes may then be replaced with the estimated values.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Systems and methods for global cyber-attack or fault detection model

An industrial asset may have monitoring nodes that generate current monitoring node values representing a current operation of the industrial asset. An abnormality detection computer may detect when a monitoring node is currently being attacked or experiencing a fault based on a current feature vector, calculated in accordance with current monitoring node values, and a detection model that includes a decision boundary. A model updater (e.g., a continuous learning model updater) may determine an update time-frame (e.g., short-term, mid-term, long-term, etc.) associated with the system based on trigger occurrence detection (e.g., associated with a time-based trigger, a performance-based trigger, an event-based trigger, etc.). The model updater may then update the detection model in accordance with the determined update time-frame (and, in some embodiments, continuous learning).

Xu, Rui↗
DOE OSTI2020

Panel Session 37: The Wants and Needs of Graduating Students and New Engineers: Are Companies Even Listening? (R8.1)

This panel focused on new hires, graduating scientists and engineers having open lines of communication with employers. Considering the projected shortfalls in the workforce, effective communication of wants-and-needs of both the employer and employee must exist. Do these needs differ between industries and/or generations? Currently, it seems that both sides must work harder to achieve this level of communication. With this new approach, both sides can express their wants and needs for a more satisfied workforce and a better work environment. Panelists with presentations: The Future of Work: What Employers Seek From Recent Graduates (Melody Bell); Graduating Students and New Engineers - Wants and Needs - Are Companies Even Listening? (Joseph Aylor); Industry and Education: Bridging the Gap (Arthur Baranovskiy)

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗