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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 91 records · Page 5

Bayesian GAN-Based False Data Injection Attack Detection in Active Distribution Grids With DERs

Advancements in information and communication technologies have revolutionized monitoring and control capabilities within smart grids. However, it also brings new vulnerabilities to data acquisition systems and state estimation functions, which attackers can subtly tamper with the measurement data through compromising the communication network. Moreover, the high penetration of renewable energy sources with the inherited characteristics of uncertainty and variability further complicates the design of effective intrusion detection systems. In this paper, a Bayesian deep learning-based approach is developed to detect cyber attacks and maintain the security of smart grids. Our method specifically addresses the prevalent issue of imbalanced data in real power systems, which arises from the predominance of normal system operations over compromised or attacked states. Employing a novel Bayesian GAN-based technique, our approach successfully discriminates between secure and compromised measurement data, even in scenarios with significant data imbalance. Furthermore, the proposed method accommodates various practical application factors, ensuring accurate intrusion detection despite the presence of measurement noise. The feasibility and effectiveness of the proposed detection mechanism are validated by testing on IEEE 13-node and 123-node test systems. Simulation results and comparisons with literature methods demonstrate the superiority of proposed cybersecurity solutions.

Bayesian GAN↗

Stochastic Trust-Region Algorithm in Random Subspaces with Convergence and Expected Complexity Analyses

Here, this work proposes a framework for large-scale stochastic derivative-free optimization (DFO) by introducing STARS, a trust-region method based on iterative minimization in random subspaces. This framework is both an algorithmic and theoretical extension of a random subspace derivative-free optimization (RSDFO) framework, and an algorithm for stochastic optimization with random models (STORM). Moreover, like RSDFO, STARS achieves scalability by minimizing interpolation models that approximate the objective in low-dimensional affine subspaces, thus significantly reducing per-iteration costs in terms of function evaluations and yielding strong performance on largescale stochastic DFO problems. The user-determined dimension of these subspaces, when the latter are defined, for example, by the columns of so-called Johnson-Lindenstrauss transforms, turns out to be independent of the dimension of the problem. For convergence purposes, inspired by the analyses of RSDFO and STORM, both a particular quality of the subspace and the accuracies of random function estimates and models are required to hold with sufficiently high, but fixed, probabilities. Using martingale theory under the latter assumptions, an almost sure global convergence of STARS to a first-order stationary point is shown, and the expected number of iterations required to reach a desired first-order accuracy is proved to be similar to that of STORM and other stochastic DFO algorithms, up to constants.

97 MATHEMATICS AND COMPUTING↗

Gaussian Process Regression under Computational and Epistemic Misspecification

Gaussian process regression is a classical kernel method for function estimation and data interpolation. In large data applications, computational costs can be reduced using low-rank or sparse approximations of the kernel. This paper investigates the effect of such kernel approximations on the interpolation error. We introduce a unified framework to analyze Gaussian process regression under important classes of computational misspecification: Karhunen-Loève expansions that result in low-rank kernel approximations, multiscale wavelet expansions that induce sparsity in the covariance matrix, and finite element representations that induce sparsity in the precision matrix. Furthermore, our theory also accounts for epistemic misspecification in the choice of kernel parameters.

Gaussian process regression↗

Navigating the Dynamic Noise Landscape of Variational Quantum Algorithms with QISMET

In the Noisy Intermediate Scale Quantum (NISQ) era, the dynamic nature of quantum systems causes noise sources to constantly vary over time. Transient errors from the dynamic NISQ noise landscape are challenging to comprehend and are especially detrimental to classes of applications that are iterative and/or long-running, and therefore their timely mitigation is important for quantum advantage in real-world applications. The most popular examples of iterative long-running quantum applications are variational quantum algorithms (VQAs). Iteratively, VQA’s classical optimizer evaluates circuit candidates on an objective function and picks the best circuits towards achieving the application’s target. Noise fluctuation can cause a significant transient impact on the objective function estimation of the VQA iterations’ tuning candidates. This can severely affect VQA tuning and, by extension, its accuracy and convergence. Furthermore, this paper proposes QISMET: Quantum Iteration Skipping to Mitigate Error Transients, to navigate the dynamic noise landscape of VQAs. QISMET actively avoids instances of high fluctuating noise which are predicted to have a significant transient error impact on specific VQA iterations. To achieve this, QISMET estimates transient error in VQA iterations and designs a controller to keep the VQA tuning faithful to the transient-free scenario. By doing so, QISMET efficiently mitigates a large portion of the transient noise impact on VQAs and is able to improve the fidelity by 1.3x-3x over a traditional VQA baseline, with 1.6-2.4x improvement over alternative approaches, across different applications and machines.

Ravi, Gokul Subramanian↗

Development of a Library for Conducting Monte Carlo Tallies on Heterogeneous Systems

A library is introduced that enables users to conduct Monte Carlo tallies on heterogeneous computing systems. The library can be built with or linked to a Monte Carlo transport code to provide tally capabilities for the project. The library provides a set of tools and an interface for constructing tallies that can be computed on CPUs or GPUs regardless of where the sample data was generated. The library can be incorporated into existing Monte Carlo transport codes at both the research and production level with minimal intrusion into the transport code. The tally library is capable of computing a variety of tallies including track-length histogram (mesh) tallies, collisionbased kernel density estimators, functional expansion tallies, eigenvalue sensitivity coefficients via iterated fission probability, and sensitivities of reaction rates or adjoint-weighted quantities via differential operator sampling. The parallelization methods are discussed and speedups are shown for 2-D and 3-D problems with comparisons to both the tally library CPU implementations as well as the tally capabilities in the host transport code. Performance results and examples are shown for MCNP, MCATK, and OpenMC.

97 MATHEMATICS AND COMPUTING↗

Fracture Toughness Evaluation for Spent Nuclear Fuel Clad Systems Using Spiral Notch Torsion Fracture Toughness Test

Many radioactive materials within the nuclear fuel cycle present a significant hazard. Such materials include spent nuclear fuel, high-level waste, legacy waste and other nuclear materials. These materials are often held in long-term storage as an interim stage within their lifecycle, including reuse or disposal. Safety and security of spent nuclear fuel (SNF) interim storage installations and follow-on SNF transportations to its final repository sites are very important, due to a great concentration of fission products, actinides and activation products. Fracture mechanics approach in applying to SNF system reliability investigation, especially for the high burn up (HBU) SNF, during SNF long term dry storage or SNF transportation is necessary due to the inherited flaws and inhomogeneity structures existed in a SNF system from the reactor operation. For instance, such as hydride and oxide formation, surface flaw induced by SNF assembly contact interactions, or internal flaws induced by pellet-clad mechanical interaction (PCMI). However, none of the existing fracture toughness data deal with fuel cladding specific geometry or SNF material conditions, such as cladding structure with the segment fuel pellets configuration and the PCMI mechanism. Consequently, the application of existing fracture toughness data to SNF system reliability investigation can be error prone; thus, the development of an industry-wide consensus fracture mechanics approach is needed. The objective of this research is to develop an in-situ fracture mechanics testing protocol, including the associated analytical procedure, that is suitable for evaluating the SNF fracture toughness. Fracture toughness data was obtained under quasi-static fracture loading using Oak Ridge National Laboratory (ORNL) developed Spiral Notch Torsion Test (SNTT) technology carried out on a biaxial tension/torsion tester. These data will be used to support SNF reliability investigation during long-tern SNF dry storage stage or in the follow-on SNF system transport to the final repository sites. SNTT has been a recent breakthrough in measuring fracture toughness for different materials, including metals, ceramics, concrete and polymers composites. Due to its high geometry constraint and unique loading condition, SNTT can be used to measure the fracture toughness with smaller specimens without concern of size effects. The application of SNTT to brittle materials has been proved to be successful. The micro-cracks induced by original notches in brittle materials could ensure crack growth in SNTT samples. Therefore, no fatigue pre cracks are needed for brittle materials specimens. The application of SNTT to the ductile material to generate valid toughness data will require a test sample with sufficient pre-crack length to increase the sample localized constraint at crack front. Fatigue pre-crack growth techniques with the associated compliance function estimated was developed for estimating the crack penetration depth to monitor the fatigue crack growth evolution. In order to extend SNTT approach to a thin shell cladding structure material, a new testing protocol and the associated analytical procedure for estimating the SNF fracture toughness was developed. The detailed SNTT approach and its estimated fracture toughness for the Zr-4 cladding structure with segment alumina inserts are presented in this report. The SNTT test results indicate that SNTT method is a reliable test approach with good repeatability in applying to Zr-4 cladding material. For the medium and the short crack length, the estimate J Q upon fracture for the baseline Zr-4 cladding is at 285.7 lb/in with 2-sigma uncertainty of 18.59 lb/in., and the associated K Q is at 61.4 Ksi√in. For a long crack length, the crack initialization orientation is apparently deviated from the principle tensile stress contour – 45° spiral crack front (i.e., Mode I + Mode III failure mechanism); and the estimated J Q is at 108 lb/in., the associated K Q is at 37.7 Ksi√in. The estimate Mode I J Q (along the 45° pitch principle tensile stress contour) is at 200 lb/in.; which indicate a significant reduction in the fracture toughness in a tubing structure under mixed mode loading condition, Mode I + Mode III, compared to that of Mode I (tensile stress dominated) alone.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Computing time- and frequency-domain analysis

Computer program Spectrum Analysis is developed to perform wide range statistical-estimation functions. It is rigorous tool for time-and frequency-domain studies. Program is written in FORTRAN IV.

Brownlow, J. D.↗

Communication architecture for large geostationary platforms

Large platforms have been proposed for supporting multipurpose communication payloads to exploit economy of scale, reduce congestion in the geostationary orbit, provide interconnectivity between diverse earth stations, and obtain significant frequency reuse with large multibeam antennas. This paper addresses a specific system design, starting with traffic projections in the next two decades and discussing tradeoffs and design approaches for major components including: antennas, transponders, and switches. Other issues explored are selection of frequency bands, modulation, multiple access, switching methods, and techniques for servicing areas with nonuniform traffic demands. Three-major services are considered: a high-volume trunking system, a direct-to-user system, and a broadcast system for video distribution and similar functions. Estimates of payload weight and d.c. power requirements are presented. Other subjects treated are: considerations of equipment layout for servicing by an orbit transfer vehicle, mechanical stability requirements for the large antennas, and reliability aspects of the large number of transponders employed.

Bond, F. E.↗

Preliminary rotor wake measurements with a laser velocimeter

A laser velocimeter (LV) was used to determine rotor wake characteristics. The effect of various fuselage widths and rotor-fuselage spacings on time averaged and detailed time dependent rotor wake velocity characteristics was defined. Definition of time dependent velocity characteristics was attempted with the LV by associating a rotor azimuth position with each velocity measurement. Results were discouraging in that no apparent time dependent velocity characteristics could be discerned from the LV measurements. Since the LV is a relatively new instrument in the rotor wake measurement field, the cause of this lack of periodicity is as important as the basic research objectives. An attempt was made to identify the problem by simulated acquisition of LV-type data for a predicted rotor wake velocity time history. Power spectral density and autocorrelation function estimation techniques were used to substantiate the conclusion that the primary cause of the lack of time dependent velocity characteristics was the nonstationary flow condition generated by the periodic turbulence level that currently exists in the open throat configuration of the wind tunnel.

Hoad, D. R.↗

Diagnostic analysis of vibration signals using adaptive digital filtering techniques

Signal enhancement techniques are described using recently developed digital adaptive filtering equipment. Adaptive filtering concepts are not new; however, as a result of recent advances in microprocessor-based electronics, hardware has been developed that has stable characteristics and of a size exceeding 1000th order. Selected data processing examples are presented illustrating spectral line enhancement, adaptive noise cancellation, and transfer function estimation in the presence of corrupting noise.

Jewell, R. E.↗

M dwarfs from the Einstein extended medium sensitivity survey

A complete sample of X-ray selected M dwarfs are presented which were serendipitously detected in the extended Einstein Observatory Medium Sensitivity Survey (MSS). The MSS detected only early M dwarfs (type MO through M5), 84 percent of which were emission stars (i.e., type Me V). It was calculated that the X-ray luminosity function for early M dwarfs with a log Lx greater than 27.6 and, by comparison to optical luminosity functions, find that about 25 percent of all early M dwarfs emit X-rays at a level greater than log Lx = 27.6. This result is compared to luminosity function estimates from optically selected samples and discussed in light of the sample's kinematic and mean age. Also presented is H alpha and Ca II K line fluxes for each member of the sample and it is shown that the surface H alpha and Ca II K luminosities do indeed correlate with Lx. The significance of this effect to theories of chromospheric and coronal heating is explained.

Fleming, Thomas A.↗

A frequency domain identification scheme for flexible structure control

The authors present a novel method called time-varying transfer function estimation (TTFE) in which time-domain parameters are computed through identification in the frequency domain. The method is particularly well suited for flexible structure control problems. An example of a flexible manipulator system is presented for which a self-tuning control law with frequency shaping is derived and demonstrated.

Tzes, Anthony P.↗

Experiments in identification and control of flexible-link manipulators

A report is presented on an ongoing effort for end-point position control of flexible-link manipulators under realistic conditions in laboratory setups consisting of one- and two-link manipulators. The authors treat modeling, identification, and control of flexible-link manipulators that are required to carry payloads, possibly unknown and varying, while undergoing disturbance effects from the environments and the workspace. The various identification and control techniques being investigated are summarized, with emphasis on the ability of the controller to adjust to changes in dynamics, payload, and working environment. It is found that time-domain methods offer identified model structures that are readily available for control design, whereas frequency-domain methods, particularly the time-varying transfer function estimation approach developed for this application, are more desirable when rapid controller tuning is required.

Yurkovich, Stephen↗

Fuzzy associative memories

Mappings between fuzzy cubes are discussed. This level of abstraction provides a surprising and fruitful alternative to the propositional and predicate-calculas reasoning techniques used in expert systems. It allows one to reason with sets instead of propositions. Discussed here are fuzzy and neural function estimators, neural vs. fuzzy representation of structured knowledge, fuzzy vector-matrix multiplication, and fuzzy associative memory (FAM) system architecture.

Kosko, Bart↗

Exact hierarchical clustering in one dimension

The present adhesion model-based one-dimensional simulations of gravitational clustering have yielded bound-object catalogs applicable in tests of analytical approaches to cosmological structure formation. Attention is given to Press-Schechter (1974) type functions, as well as to their density peak-theory modifications and the two-point correlation function estimated from peak theory. The extent to which individual collapsed-object locations can be predicted by linear theory is significant only for objects of near-characteristic nonlinear mass.

Williams, B. G.↗

Multivariable frequency domain identification via 2-norm minimization

The author develops a computational approach to multivariable frequency domain identification, based on 2-norm minimization. In particular, a Gauss-Newton (GN) iteration is developed to minimize the 2-norm of the error between frequency domain data and a matrix fraction transfer function estimate. To improve the global performance of the optimization algorithm, the GN iteration is initialized using the solution to a particular sequentially reweighted least squares problem, denoted as the SK iteration. The least squares problems which arise from both the SK and GN iterations are shown to involve sparse matrices with identical block structure. A sparse matrix QR factorization method is developed to exploit the special block structure, and to efficiently compute the least squares solution. A numerical example involving the identification of a multiple-input multiple-output (MIMO) plant having 286 unknown parameters is given to illustrate the effectiveness of the algorithm.

Bayard, David S.↗

Observed acoustic and aeroelastic spectral responses of a MOD-2 turbine blade to turbulence excitation

Early results from a recent experiment designed to directly evaluate the aeroacoustic/elastic spectral responses of a MOD-2 turbine blade to turbulence-induced unsteady blade loads are discussed. The experimental procedure consisted of flying a hot-film anemometer from a tethered balloon in the turbine inflow and simultaneously measuring the fluctuating airload and aeroelastic response at two blade span stations (65% and 87% spans) using surface-mounted, subminiature pressure transducers and standard strain gage instrumentation. The radiated acoustic pressure field was measured with a triad of very-low-frequency microphones placed at ground level, 1.5 rotor diameters upwind of the disk. Initial transfer function estimates for acoustic radiation, blade normal forces, flapwise acceleration/displacement, and chord/flapwise moments are presented.

Kelley, N. D.↗