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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 55 records · Page 3

Time series anomaly detection in power electronics signals with recurrent and ConvLSTM autoencoders

The anomalies in the high voltage converter modulator (HVCM) remain a major down time for the spallation neutron source facility, that delivers the most intense neutron beam in the world for scientific materials research. In this work, we propose neural network architectures based on Recurrent AutoEncoders (RAE) to detect anomalies ahead of time in the power signals coming from the HVCM. Bi-directional gated recurrent unit, bi-directional long-short term memory (LSTM), and convolutional LSTM (ConvLSTM) are developed, trained, and tested using real experimental signals from the HVCM module. The results show a good performance of the proposed RAE models, achieving precision up to 91%, recall up to 88%, false omission rate as low as 20% (i.e. 80% of the anomalies were detected), and area under the ROC curve up to 0.9. The three RAE models provide very comparable performance, with LSTM showing slightly better performance than GRU and ConvLSTM. The RAE models are benchmarked against other anomaly detection methods, including isolation forest, support vector machine, local outlier factor, feedforward and convolutional autoencoders, and others; showing a better performance. Here, the results of this study demonstrate the promising potential of RAE in anomaly detection for real-world power systems, and for increasing the reliability of the HVCM modules in the spallation neutron source.

42 ENGINEERING↗

Universal scaling of weak localization in graphene due to bias-induced dispersion decoherence

The differential conductance of graphene is shown to exhibit a zero-bias anomaly at low temperatures, arising from a suppression of the quantum corrections due to weak localization and electron interactions. A simple rescaling of these data, free of any adjustable parameters, shows that this anomaly exhibits a universal, temperature- (T) independent form. According to this, the differential conductance is approximately constant at small voltages (V < kBT/e), while at larger voltages it increases logarithmically with the applied bias. For theoretical insight into the origins of this behaviour, which is inconsistent with electron heating, we formulate a model for weak-localization in the presence of nonequilibrium transport. According to this model, the applied voltage causes unavoidable dispersion decoherence, which arises as diffusing electron partial waves, with a spread of energies defined by the value of the applied voltage, gradually decohere with one another as they diffuse through the system. The decoherence yields a universal scaling of the conductance as a function of eV/kBT, with a logarithmic variation for eV/kBT > 1, variations in accordance with the results of experiment. Our theoretical description of nonequilibrium transport in the presence of this source of decoherence exhibits strong similarities with the results of experiment, including the aforementioned rescaling of the conductance and its logarithmic variation as a function of the applied voltage.

42 ENGINEERING↗

Systems and methods for real-time data processing and for emergency planning

Systems and methods are described herein for real-time data processing and for emergency planning. Scenario test data may be collected in real-time based on monitoring local or regional data to ascertain any anomaly phenomenon that may indicate an imminent danger or of concern. A computer-implemented method may include filtering a plurality of different test scenarios to identify a sub-set of test scenarios from the plurality of different test scenarios that may have similar behavior characteristics. A sub-set of test scenarios is provided to a trained neural network to identify one or more sub-set of test scenarios. The one or more identified sub-set of test scenarios may correspond to one or more anomaly test scenarios from the sub-set of test scenarios that is most likely to lead to an undesirable outcome. The neural network may be one of: a conventional neural network and a modular neural network.

Yilmaz, Alper↗

Systems and methods for real-time data processing and for emergency planning

Systems and methods are described herein for real-time data processing and for emergency planning. Scenario test data may be collected in real-time based on monitoring local or regional data to ascertain any anomaly phenomenon that may indicate an imminent danger or of concern. A computer-implemented method may include filtering a plurality of different test scenarios to identify a sub-set of test scenarios from the plurality of different test scenarios that may have similar behavior characteristics. A sub-set of test scenarios is provided to a trained neural network to identify one or more sub-set of test scenarios. The one or more identified sub-set of test scenarios may correspond to one or more anomaly test scenarios from the sub-set of test scenarios that is most likely to lead to an undesirable outcome. The neural network may be one of: a conventional neural network and a modular neural network.

97 MATHEMATICS AND COMPUTING↗

A Vertically Resolved MSE Framework Highlights the Role of the Boundary Layer in Convective Self-Aggregation

Abstract Convective self-aggregation refers to a phenomenon in which random convection can self-organize into large-scale clusters over an ocean surface with uniform temperature in cloud-resolving models. Previous literature studies convective aggregation primarily by analyzing vertically integrated (VI) moist static energy (MSE) variance. That is the global MSE variance, including both the local MSE variance at a given altitude and the covariance of MSE anomalies between different altitudes. Here we present a vertically resolved (VR) MSE framework that focuses on the local MSE variance to study convective self-aggregation. Using a cloud-resolving simulation, we show that the development of self-aggregation is associated with an increase of local MSE variance, and that the diabatic and adiabatic generation of the MSE variance is mainly dominated by the boundary layer (BL; the lowest 2 km). The results agree with recent numerical simulation results and the available potential energy analyses showing that the BL plays a key role in the development of self-aggregation. Additionally, we find that the lower free troposphere (2–4 km) also generates significant MSE variance in the first 15 days. We further present a detailed comparison between the global and local MSE variance frameworks in their mathematical formulation and diagnostic results, highlighting their differences.

54 ENVIRONMENTAL SCIENCES↗

Weakly supervised anomaly detection for resonant new physics in the dijet final state using proton-proton collisions at $\sqrt{s}$ = 13 TeV with the ATLAS detector

An anomaly detection search for narrow-width resonances beyond the Standard Model that decay into a pair of jets is presented. The search is based on 139 fb −1 of proton-proton collisions at $\sqrt{s}$ = 13 TeV recorded during 2015–2018 with the ATLAS detector at the Large Hadron Collider. The analysis is optimized without a particular signal model and aims to be sensitive to a broad range of new physics. It uses two different machine learning strategies to estimate the background in different signal regions. In each region, a weakly supervised classifier is trained to distinguish this background model from data. The analysis focuses on events with high transverse momentum jets reconstructed as large-radius jets. The mass and substructure of these jets are used as inputs to the classifiers. After a classifier-based selection, the distribution of the invariant mass of the two jets is used to search for potential local excesses. The model-independent results of both the anomaly detection methods show no signs of significant local excesses. In addition to model-independent results, a representative set of signal models is injected into the data, and the sensitivity of the methods to these scenarios is reported.

Aad, G. [Aix-Marseille Université] (ORCID:00000002↗

Resistivity and magnetoresistance properties of R 2 NiSi 3 (R = Gd, Dy, Ho, Er, Tm) compounds

The resistivity and magnetoresistance behaviour of the hexagonal intermetallic compounds R 2 NiSi 3 (R = Gd, Dy, Ho, Er, and Tm) are reported here. All the studied polycrystalline compounds exhibit metallic behavior along with additional magnetic anomalies at low temperatures. A well-defined resistivity minima is observed in Gd 2 NiSi 3 and Dy 2 Ni 0.87 Si 2.95 at a temperature much higher than their respective magnetic transition temperatures. The anomaly has been ascribed to the charge carrier localization caused by magnetic precursor effect. Magnetic field induced crossover from positive to negative magnetoresistance (MR) behavior associated with antiferromagnetic ground state is evidenced for Gd 2 NiSi 3 and Er 2 NiSi 3 in the low temperature region. Although Tm 2 Ni 0.93 Si 2.93 does not exhibit any long range magnetic order down to 2 K, a sudden drop in resistivity behavior is observed below ~10 K. Furthermore, presence of short range magnetic correlation observed in a wide temperature range, much beyond their respective magnetic ordering temperatures, has been argued to be responsible for achieving finite negative MR for all the compounds. Additionally, a subtle resemblance between the observed transport anomalies and the magnetic properties of these systems has been discussed.

36 MATERIALS SCIENCE↗

Understanding electronic peculiarities in tetragonal FeSe as local structural symmetry breaking

Traditional band theory of perfect crystalline solids often uses as input the structure deduced from diffraction experiments; when modeled by the minimal unit cell this often produces a spatially averaged model. The present study illustrates that this is not always a safe practice unless one examines if the intrinsic bonding mechanism is capable of benefiting from the formation of a distribution of lower symmetry local environments that differ from the macroscopically averaged structure. This can happen either due to positional or to magnetic symmetry breaking. By removing the constraint of a small crystallographic cell, the energy minimization in the density functional theory finds atomic and spin symmetry breaking, not evident in conventional diffraction experiments but being found by local probes such as atomic pair distribution function analysis. Here in this paper we report that large atomic and electronic anomalies in bulk tetragonal FeSe emerge from the existence of distributions of local positional and magnetic moment motifs. The found symmetry-broken motifs obtained by minimization of the internal energy represent what chemical bonding in the tetragonal phase prefers as intrinsic energy lowering (stabilizing) static distortions. This explains observations of band renormalization, predicts orbital order and enhanced nematicity, and provides unprecedented close agreement with spectral function measured by photoemission and local atomic environment revealed by the pair distribution function. While the symmetry-restricted strong correlation approach has been argued previously to be the exclusive theory needed for describing the main peculiarities of FeSe, we show here that the symmetry-broken mean-field approach addresses numerous aspects of the problem, provides intuitive insight into the electronic structure, and opens the door for large-scale mean-field calculations for similar d -electron quantum materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Efimov-like states and quantum funneling effects on synthetic hyperbolic surfaces

Engineering lattice models with tailored inter-site tunnelings and onsite energies could synthesize essentially arbitrary Riemannian surfaces with highly tunable local curvatures. Here, we point out that discrete synthetic Poincaré half-planes and Poincaré disks, which are created by lattices in flat planes, support infinitely degenerate eigenstates for any nonzero eigenenergies. Such Efimov-like states exhibit a discrete scaling symmetry and imply an unprecedented apparatus for studying quantum anomaly using hyperbolic surfaces. Furthermore, all eigenstates are exponentially localized in the hyperbolic coordinates, signifying the first example of quantum funneling effects in Hermitian systems. As such, any initial wave packet travels towards the edge of the Poincaré half-plane or its equivalent on the Poincaré disk, delivering an efficient scheme to harvest light and atoms in two dimensions. Furthermore, our findings unfold the intriguing properties of hyperbolic spaces and suggest that Efimov states may be regarded as a projection from a curved space with an extra dimension.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Magnetic field induced modification of a first-order ferromagnetic transition in Eu 2 ⁢In

Here, we present a comprehensive study of the temperature-and magnetic-field-dependent magnetization, specific heat, and local crystal structure across the first-order ferromagnetic–paramagnetic transition in Eu 2 ⁢In. Anomalies in the magnetocaloric response are observed near 𝐻 ≈ 25 kOe, including changes in field scaling of magnetic entropy, local entropy exponent, and universal master curve, which suggest an apparent weakening of the first-order character of the transition. However, quantitative analysis of the magnetocaloric parameters together with modified Arrott plots demonstrates that the transition remains first order up to at least 70 kOe. Specific-heat measurements reveal a field-induced splitting of the sharp zero-field anomaly into a doublet, providing a natural explanation for the change in the magnetocaloric response. Magnetic-field-dependent extended x-ray absorption fine structure (EXAFS) measurements show no detectable field-induced changes in the local coordination environment of Eu. We therefore attribute these observations to a magnetic-field-induced two-step transition process in Eu 2 ⁢In.

Kumar, Ajay [Ames Laboratory (AMES), Ames, IA (Uni↗

Local structure study on magnetostrictive material Tb 1–x Dy x Fe 2

Tb 1–x Dy x Fe 2 system has attracted more research interest due to the large magnetostrictive effect. The crystal structures and physical properties have been well studied, but research studies on their local structures are still rare. As such, in this work, the local structure of Tb 1–x Dy x Fe 2 samples was studied using the pair distribution function and x-ray absorption spectroscopy techniques. The results demonstrate that the system owns the same local crystal symmetry with its average structure in the ferromagnetic phase, and the crystal lattice of the system is more ordered with increasing Dy content, indicating that the Dy-rich tetragonal phase is more stable than the Tb-rich rhombohedral phase. The different roles of metallic bonds in affecting the crystal lattice are presented. The weak Fe 1 –Fe 2 bonds influenced by the local environment such as local stress from randomly distributed nanodomains could originate the anomalies in the lattice, resulting in the more ordered and stable Dy-rich phase than the Tb-rich phase.

36 MATERIALS SCIENCE↗

Parametrizations of coupled betatron motion for strongly coupled lattices

The coupling of transverse motion is a natural occurrence in particle accelerators, either in the form of a residual coupling arising from imperfections or originating by design from strong systematic coupling fields. While the first can be treated perturbatively, the latter requires a robust approach adapted to strongly coupled optics, and a parametrization of the linear optics must be performed to explore beam dynamics in such peculiar lattices. This work highlights the key physical interpretations of the main parametrization formalisms to describe linear coupled optics, along with explicit links and comparisons of these parametrizations. Concepts rarely illustrated in other works, such as forced mode flips and local coupling, are explored in detail, clarifying some anomalies that can arise in lattice functions. The analytical methods have been implemented in a reference Python package and connected with ray-tracing and integration codes to explore examples of strongly coupled lattices, which are discussed in detail to highlight the key physical interpretations of the parametrizations and characteristics of the lattices.

47 OTHER INSTRUMENTATION↗

Review of In Situ Sensing for Directed Energy Deposition for Industrial Part Quality Assessment

As the use additive manufacturing (AM) processes continues to grow in critical industries, improved quality assurance methods are becoming increasingly sought after for qualification and certification of AM components. Traditional nondestructive evaluation of printed components is often unable to supply the required confidence in print quality to justify qualification and certification, but the layer-by-layer nature of AM provides unprecedented opportunities for in situ quality inspection. This document summarizes recent developments in process monitoring research specifically related to Directed Energy Deposition (DED). Particular attention is given to three aspects of the highlighted manuscripts: (1) the type of sensors used, (2) features extracted from each sensor modality, and (3) analysis of extracted features for AM quality assessment. Based on the review of the state-of-the-art, several observations have been made. First, none of the reviewed works have applied their trained models to real part geometries, with many of the works relying on single track experiments, thin-walled structures, and cubes. Similarly, there have not been any works demonstrating model generalizability, i.e., a model trained on data from one build allows for fruitful analysis of data from another build. Many works used machine learning techniques to distinguish different process regimes (i.e., normal, keyholing, lack-of-fusion), but very few papers have investigated stochastic variation in an already “optimized” process. Sensor fusion approaches are also limited in the DED sensing literature, but the few works that have employed such techniques have demonstrated the benefits. Finally, registration of in situ data to the build coordinate system is of paramount importance to producing industrially relevant in situ monitoring systems. Data registration allows direct correlations between process anomalies detected in the process monitoring data to localized departures in part quality, but such techniques are generally lacking in the current literature.

36 MATERIALS SCIENCE↗

6D anomaly-free matter spectrum in F-theory on singular spaces

In this paper we study the 6d localized charged matter spectrum of F-theory directly on a singular elliptic Calabi-Yau 3-fold, i.e. without smoothing via resolution or deformation of the entire fibration. Given only the base surface, discriminant locus, and the SL(2, $\mathbb{Z}$) local system, we propose a general prescription for determining the charged matter spectrum localized at intersections of seven-branes, using the technology of string junctions. More precisely, at each codimension-2 collision of seven-branes, we determine the local seven-brane content and compute the number of massless string junctions modulo the action of the SL(2,$\mathbb{Z}$) monodromy. We find agreement with the predicted results from 6d anomaly cancellation in all cases considered. Examples include a generic Weierstrass model with arbitrary Kodaira fiber intersecting an I 1 , as well as cases with jointly charged matter localized at intersections of non-abelian seven-branes.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Remarks on geometric engineering, symmetry TFTs and anomalies

Abstract Geometric engineering is a collection of tools developed to establish dictionaries between local singularities in string theory and (supersymmetric) quantum fields. Extended operators and defects, as well as their higher quantum numbers captured by topological symmetries, can be encoded within geometric engineering dictionaries. In this paper we revisit and clarify aspects of these techniques, with special emphasis on ’t Hooft anomalies, interpreted from the SymTFT perspective as obstructions to the existence of Neumann boundary conditions. These obstructions to gauging higher symmetries are captured via higher link correlators for the SymTFT on spheres. In this work, we give the geometric engineering counterpart of this construction in terms of higher links of topological membranes. We provide a consistency check in the context of 5D SCFTs with anomalous 1-form symmetries, where we give two independent derivations of the anomaly in terms of higher links, one purely field theoretical and the other purely geometrical. Along the way, we also recover the construction of non-invertible duality defects in 4D$$ \mathcal{N} $$ N = 4 SYM from a geometric engineering perspective.

Physics↗

From large to small $$ \mathcal{N} $$ = (4, 4) superconformal surface defects in holographic 6d SCFTs

Abstract Two-dimensional (2d)$$ \mathcal{N} $$ N = (4, 4) Lie superalgebras can be either “small” or “large”, meaning their R-symmetry is either$$ \mathfrak{so} $$ so (4) or$$ \mathfrak{so} $$ so (4) ⊕$$ \mathfrak{so} $$ so (4), respectively. Both cases admit a superconformal extension and fit into the one-parameter family$$ \mathfrak{d} $$ d (2,1;γ) ⊕$$ \mathfrak{d} $$ d (2,1;γ), with parameterγ∈ (−∞,∞). The large algebra corresponds to generic values ofγ, while the small case corresponds to a degeneration limit withγ→ −∞. In 11d supergravity, we study known solutions with superisometry algebra$$ \mathfrak{d} $$ d (2,1;γ) ⊕$$ \mathfrak{d} $$ d (2,1;γ) that are asymptotically locally AdS 7 ×𝕊 4 . These solutions are holographically dual to the 6d maximally superconformal field theory with 2d superconformal defects invariant under$$ \mathfrak{d} $$ d (2,1;γ) ⊕$$ \mathfrak{d} $$ d (2,1;γ). We show that a limit of these solutions, in whichγ→ −∞, reproduces another known class of solutions, holographically dual tosmall$$ \mathcal{N} $$ N = (4, 4) superconformal defects. We then use this limit to generate new small$$ \mathcal{N} $$ N = (4, 4) solutions with finite Ricci scalar, in contrast to the known small$$ \mathcal{N} $$ N = (4, 4) solutions. We then use holography to compute the entanglement entropy of a spherical region centered on these small$$ \mathcal{N} $$ N = (4, 4) defects, which provides a linear combination of defect Weyl anomaly coefficients that characterizes the number of defect-localized degrees of freedom. We also comment on the generalization of our results to include$$ \mathcal{N} $$ N = (0,4) surface defects through orbifolding.

Physics↗

Majorana neutrinos and dark matter from anomaly cancellation

We discuss a simple theory for neutrino masses where the total lepton number is a local gauge symmetry spontaneously broken below the multi-TeV scale. In this context, the neutrino masses are generated through the canonical seesaw mechanism and a Majorana dark matter candidate is predicted from anomaly cancellation. We discuss in great detail the dark matter annihilation channels and find out the upper bound on the symmetry-breaking scale using the cosmological bounds on the relic density. Since in this context the dark matter candidate has suppressed couplings to the Standard Model quarks, one can satisfy the direct detection bounds even if the dark matter mass is close to the electroweak scale. This theory predicts a light pseudo-Nambu-Goldstone boson (the Majoron) associated to the mechanism of neutrino mass. We discuss briefly the properties of the Majoron and the impact of the big bang nucleosynthesis bounds. Published by the American Physical Society 2024

Astronomy & Astrophysics↗

Machine Learning-based False Data Injection Attack Detection and Localization in Power Grids

Cyberattacks on critical infrastructures can be catastrophic and bring nations to their knees. Therefore, detecting these attacks is crucial and challenging. This paper presents a novel approach for detecting and locating cyberattacks affecting an electrical power system. The adversary employs a man-in-the-middle technique to inject false data into the communication between distributed energy resources (DER) and Microgrid Controller (MGC) with the goal of disrupting power delivery. The approach for detection and localization is based on integrating multiple machine learning-based anomaly detection models that combine network traffic data and grid measurements. Experiments are performed to assess the method's performance using a hardware-in-the-loop real-time simulation testbed which includes Modbus TCP/IP communication. Power system topology and operating conditions are based on actual topology and real-world data provided by the Holy Cross Energy utility network. Results confirm that the method can be successfully employed for detecting and localizing cyberattacks.

Leao, Bruno P.↗