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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 631 records · Page 35

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↗

Tachyon field non-minimally coupled to massive neutrino matter

In this paper, we consider rolling tachyon, with steep run-away type of potentials non-minimally coupled to massive neutrino matter. The coupling dynamically builds up at late times as neutrino matter turns non-relativistic. In case of scaling and string inspired potentials, we have shown that non-minimal coupling leads to minimum in the field potential. Given a suitable choice of model parameters, it is shown to give rise to late-time acceleration with the desired equation of state.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Field-Array Benchmark of Commercial Bifacial PV Technologies with Publicly Available Data

We present results for a 75-kW field array deployed with rows of 5 different commercially available bifacial technologies. Four PERC (multi and mono) and 1 Silicon Heterojunction manufacturers are represented. Reference strings of equivalent monofacial PV modules are also installed in the 10-row field. High accuracy string-level DC monitoring and module-level measurements have been recorded for six months. Analysis indicates performance within expectation, with a cumulative model mean error within +/- 2% for both bifacial and monofacial models and cumulative bifacial energy gain between 6-9%. A custom-module to measure shading loss from the torque-tube was installed. One month data shows up to 6% irradiance non-uniformity. A fixed-tilt test-site with 3 years of bifacial data is also presented, with a bifacial gain of 3%.

41 EE - Solar Energy Technologies Office (EE-4S)↗

Searching for axion-like particles through CMB birefringence from string-wall networks

Axion-like particles (ALPs) can form a network of cosmic strings and domain walls that survives after recombination and leads to anisotropic birefringence of the cosmic microwave background (CMB). In addition to studying cosmic strings, we clarify and emphasize how the formation of ALP-field domain walls impacts the cosmic birefringence signal; these observations provide a unique way of probing ALPs with masses in the range 3H 0 ≲ m a ≲ 3H cmb . Using measurements of CMB birefringence from several telescopes, we find no evidence for axion-defect-induced anisotropic birefringence of the CMB. We extract constraints on the model parameters that include the ALP mass ma, ALP-photon coupling Script A ∝ g aγγ f a , the domain wall number N dw , and parameters characterizing the abundance and size of defects in the string-wall network. Considering also recent evidence for isotropic CMB birefringence, we find it difficult to accommodate this with the non-detection of anisotropic birefringence under the assumption that the signal is generated by an ALP defect network.

79 ASTRONOMY AND ASTROPHYSICS↗

Atomistic modeling of metal–nonmetal interphase boundary diffusion

Atomistic computer simulations are applied to investigate the atomic structure, thermal stability, and diffusion processes in Al–Si interphase boundaries as a prototype of metal–ceramic interfaces in composite materials. Some of the most stable orientation relationships between the phases found in this work were previously observed in epitaxy experiments. Here, a non-equilibrium interface can transform to a more stable state by a mechanism that we call interface-induced recrystallization. Diffusion of both Al and Si atoms in stable Al–Si interfaces is surprisingly slow compared with diffusion of both elements in Al grain boundaries but can be accelerated in the presence of interface disconnections. A qualitative explanation of the sluggish interphase boundary diffusion is proposed. Atomic mechanisms of interphase boundary diffusion are similar to those in metallic grain boundaries and are dominated by correlated atomic rearrangements in the form of strings and rings of collectively moving atoms.

36 MATERIALS SCIENCE↗

Experimental targets for dark photon dark matter

Ultralight dark photon dark matter features distinctive cosmological and astrophysical signatures and is also supported by a burgeoning direct-detection program searching for its kinetic mixing with the ordinary photon over a wide mass range. Dark photons, however, cannot necessarily constitute the dark matter in all of this parameter space. In minimal models where the dark photon mass arises from a dark Higgs mechanism, early-Universe dynamics can easily breach the regime of validity of the low-energy effective theory for a massive vector field. In the process, the dark sector can collapse into a cosmic string network, precluding dark photons as viable dark matter. We establish the general conditions under which dark photon production avoids significant backreaction on the dark Higgs and identify regions of parameter space that naturally circumvent these constraints. After surveying implications for known dark photon production mechanisms, we propose novel models that set well-motivated experimental targets across much of the accessible parameter space. We also discuss complementary cosmological and astrophysical signatures that can probe the dark sector physics responsible for dark photon production.

Dark matter↗

Real-time dynamics of the Schwinger model as an open quantum system with Neural Density Operators

Ab-initio simulations of multiple heavy quarks propagating in a Quark-Gluon Plasma are computationally difficult to perform due to the large dimension of the space of density matrices. This work develops machine learning algorithms to overcome this difficulty by approximating exact quantum states with neural network parametrisations, specifically Neural Density Operators. As a proof of principle demonstration in a QCD-like theory, the approach is applied to solve the Lindblad master equation in the 1 + 1d lattice Schwinger Model as an open quantum system. Neural Density Operators enable the study of in-medium dynamics on large lattice volumes, where multiple-string interactions and their effects on string-breaking and recombination phenomena can be studied. Thermal properties of the system at equilibrium can also be probed with these methods by variationally constructing the steady state of the Lindblad master equation. Scaling of this approach with system size is studied, and numerical demonstrations on up to 32 spatial lattice sites and with up to 3 interacting strings are performed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Inflation from nilpotent Kähler corrections

We develop a new class of supergravity cosmological models where inflation is induced by terms in the Kähler potential which mix a nilpotent superfield S with a chiral sector Φ. As the new terms are non-(anti)holomorphic, and hence cannot be removed by a Kähler transformation, these models are intrinsically Kähler potential driven. Such terms could arise for example due to a backreaction of an anti-D3 brane on the string theory bulk geometry. We show that this mechanism is very general and allows for a unified description of inflation and dark energy, with controllable SUSY breaking at the vacuum. When the internal geometry of the bulk field is hyperbolic, we prove that small perturbative Kähler corrections naturally lead to α-attractor behaviour, with inflationary predictions in excellent agreement with the latest Planck data.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

On the Origin of Holes During Polarization Reset in Floating Body Ferroelectric FETs Towards Improving Switching Efficiency

In this article, we performed a comprehensive combined experimental and modeling study on the polarization reset mechanisms of floating body (i.e., channel) ferroelectric FETs, an important class of device with growing interests due to added functionalities and improved reliabilities. Using fully-depleted silicon-on-insulator (FDSOI) FeFET as a classical example, we demonstrate that: 1) without hole generation mechanisms, floating body FeFETs during reset is simply a capacitor divider, with negligible ferroelectric voltage drop for switching; ii) Band-to-band-tunneling (BTBT) around gate-to-S/D overlap even with zero drain bias generates holes to facilitate the reset in FDSOI FeFET, though at a slower speed and hold the reset state; iii) With scaling, S/D inner fringe field can enable fast reset, thus offering a potential efficiency boost approach; iv) a compact FDSOI FeFET model is developed that can capture the BTBT effect and reproduce the observed behaviors; v) the reset mechanism is also validated in a NAND string composed of FDSOI FeFETs, demonstrating its relevant applications. These insights show the strategies in improving reset efficiency, i.e., enhanced BTBT and inner fringe field.

42 ENGINEERING↗

Vertical 2T-nC FeRAM Demonstration: BEOL Read Transistor for 4F 2 Memory Strings and Two-Terminal Selector Design for Polarization Disturb Mitigation

In this work, we demonstrate a vertical 2T-nC FeRAM with a back-end-of-line (BEOL) read transistor (T R ) for 4F 2 string and propose a selector design to mitigate polarization disturb in passive capacitor crossbar arrays. Key contributions include: 1) successful integration and operation composed of a Si MOSFET write transistor (T W ), 3-layer cylindrical ferroelectric capacitors, and Si-doped In 2 O 3 BEOL T R , demonstrating the feasibility of 4F 2 2T−nC string; 2) introducing nonlinearity into the capacitor stack to suppress ferroelectric voltage drop under inhibition biases while maintaining sufficient write voltage, reducing disturbance; 3)modeling and experimental validation of inserting a metalsemiconductor (a-Si)-metal (MSM) selector into the capacitor in mitigating the disturb, particularly achieving 9x reduction of disturb after 10 6 cycles in the V W /2 scheme.

42 ENGINEERING↗

Utilizing 3D-DIC on Mars 2020 Rover Wheel Assembly: Test-Analysis Correlation

Following the successful implementation of full-field photogrammetry, more specifically three-dimensional Digital Image Correlation (3D-DIC), on the Mars 2020 Heat Shield Structural Failure Review assessment, 3D-DIC was selected as one of the primary measurement techniques for the Mars 2020 Rover wheel assembly qualification test at the NASA Jet Propulsion Laboratory (JPL). To validate the Rover wheel landing loads simulations, it was extremely important to have high confidence in the wheel models. Due to the large deformations and strains that the wheel would be subject to during landing, traditional instrumentation such as linear variable displacement transducers (LVDTs), electrical-resistance strain gages and string potentiometers, would not be sufficient on their own to provide all the necessary validation data. Therefore, the NASA Engineering and Safety Center (NESC) provided the 3D-DIC expertise and support to measure the high deformation and strain in the wheel flexures and qualify the overall structural response of the Mars 2020 rover wheel assembly. There were two key objectives for the photogrammetry technique: (1) monitor the wheel response in real-time, guarding against anomalous behavior and failure, and (2) provide test data for test-analysis correlation to validate and/or improve the high-fidelity computational model. The contents of this paper will focus on the challenges of applying 3D-DIC to the Mars 2020 Rover wheel assembly and how these challenges were overcome. Examples of test-analysis correlation during the stiffness characterization and structural qualification will be presented and discussed in detail. Experimental results were compared with the analysis and showed excellent agreement between the predicted behavior and helped validate the high-fidelity models.

Mars 2020 Rover Wheel↗

Features of a SINDA/FLUINT model of a liquid oxygen supply line

The modeling features used in a steady-state heat transfer problem using SINDA/FLUINT are described. The problem modeled is a 125 feet long, 3 inch diameter pipe, filled with liquid oxygen flow driven by a given pressure gradient. The pipe is fully insulated in five sections. Three sections of 1 inch thick spray-on foam and two sections of vacuum jacket. The model evaluates friction, turns losses and convection heat transfer between the fluid and the pipe wall. There is conduction through the foam insulation with temperature dependent thermal conductivity. The vacuum space is modeled with radiation and gas molecular conduction, if present, in the annular gap. Heat is transferred between the outer surface and surrounding ambient by natural convection and radiation; and, by axial conduction along the pipe and through the vacuum jacket spacers and welded seal flanges. The model makes extensive use of SINDA/FLUINT basic capabilities such as the GEN option for nodes and conductors (to generate groups of nodes or conductors), the SIV option (to generate single, temperature varying conductors), the SIM option (for multiple, temperature varying conductors) and the M HX macros for fluids (to generate strings of lumps, paths, and ties representing a diabatic duct). It calls subroutine CONTRN (returns the relative location in the G-array of a network conductor, given an actual conductor number) enabling an extensive manipulation of conductor (calculates an assignment of their values) with DO loops. Models like this illustrate to the new and even to the old SINDA/FLUINT user, features of the program that are not so obvious or known, and that are extremely handy when trying to take advantage of both, the automation of the DATA headers and make surgical modifications to specific parameters of the thermal or fluid elements in the OPERATIONS portion of the model.

Simmonds, Boris G.↗

Curvaton as dark matter with secondary inflation

We consider a novel cosmological scenario in which a curvaton is long-lived and plays the role of cold dark matter (CDM) in the presence of a short, secondary inflation. Non-trivial evolution of the large scale cosmological perturbation in the curvaton scenario can affect the duration of the short term inflation, resulting in the inhomogeneous end of inflation. Non-linear parameters of the curvature perturbation are predicted to be f {sub NL} ≈ 5/4 and g {sub NL} ≈ 0. The curvaton abundance can be well diluted by the short-term inflation and accordingly, it does not have to decay into the Standard Model particles. Then the curvaton can account for the present CDM with the isocurvature perturbation being sufficiently suppressed because both the adiabatic and CDM isocurvature perturbations have the same origin. As an explicit example, we consider the thermal inflation scenario and a string axion as a candidate for this curvaton-dark matter. We further discuss possibilities to identify the curvaton-dark matter with the QCD axion.

79 ASTRONOMY AND ASTROPHYSICS↗

A Variational Autoencoder Model Toward Molecular Structure Representation Learning of Fuels

Here, in this work, a Variational Autoencoder (VAE)-based data-driven modeling framework is developed with the overarching goal of enabling fuel design. The VAE model is trained on a large dataset with several chemical species to learn a compressed latent space molecular representation. Chemical structure in the form of Simplified Molecular Input Line Entry System (SMILES) string is fed as input, encoded into the VAE latent space, and decoded back to the SMILES string using Long Short-Term Memory (LSTM) networks. Complexities of the VAE training loss function are thoroughly examined by varying the weightage (beta (𝜷) parameter) of the latent space regularization term, thereby assessing the balance between reconstruction accuracy and validity, and focusing on both accurate molecular structure reconstruction and latent space consistency. Two different strategies for 𝜷 variation are evaluated: linear annealing and cyclic annealing. In addition, the impact of total correlation adjustment and hierarchical priors is also studied with regard to the balance between reconstruction fidelity and latent space regularization, and potential issues such as posterior collapse, over-regularization, and poor disentanglement of latent variables. Overall, the best performance of the model is achieved with hierarchical priors and incrementally increasing 𝜷 from 0 to a threshold value of 0.25 over 75 epochs. The generative VAE model can be readily coupled with Quantitative Structure–Property Relationship (QSPR) analysis to develop an integrated end-to-end framework for fuel-property prediction and molecular design of novel promising fuels.

fuel design↗

Projective Representations, Bogomolov Multiplier, and Their Applications in Physics

We present a pedagogical review of projective representations of finite groups and their physical applications in quantum many-body systems. Some of our physical results are new. We begin with a self-contained introduction to projective representations, highlighting the role of group cohomology, representation theory, and classification of irreducible projective representations. We then focus on a special subset of cohomology classes, known as the Bogomolov multiplier, which consists of cocycles that are symmetric on commuting pairs but remain nontrivial in group cohomology. Such cocycles have important physical implications: they characterize (1+1)D SPT phases that cannot be detected by string order parameters and give rise, upon gauging, to distinct gapped phases with completely broken non-invertible Rep(G) symmetry. We construct explicit lattice models for these phases and demonstrate how they are distinguished by the fusion rules of local order parameters. We show that a pair of completely broken Rep(G) SSB phases host nontrivial interface modes at their domain walls. As an example, we construct a lattice model where the ground state degeneracy on a ring increases from 32 without interfaces to 56 with interfaces.

Bogomolov multiplier↗

Vibrations of the earth's magnetic tail

The natural vibration period of the tail (regarded as bundle of magnetic line-of-force strings) and the characteristic time of recurrence of magnetospheric substorms are of the same order, suggesting the possibility of a relation between these phenomena. A model of the tail in the form of a plasma cylinder whose free boundary is immersed in the interplanetary plasma is examined. The nature of the natural oscillations of the tail excited by variations of the solar wind pressure is studied in this model. These vibrations have a total energy of approximately 10 to the 22nd power erg, which is sufficient to generate magnetospheric substorms.

Yershkovich, A. I.↗

A Model Based Approach to Extract Health Information from Textual Data

In current nuclear power plants (NPPs) a large amount of condition-based data is being generated and stored to assess and monitor component health and performance. The format of this data can be either numeric (e.g., pump vibration data) or textual (e.g., condition report which assess component health). While assessing component health from numeric data can be performed with a large variety of methods, the extraction of information from textual data still remains a challenge. Natural language processing (NLP) methods are starting to be deployed in current NPPs mainly to filter out incident reports (IRs) that are not safety related by employing supervised machine learning methods. However, these methods do not really provide the quantitative information that might be contained in IRs. This paper presents an approach to extract information from textual data (e.g., from IRs, maintenance reports) that is based on NLP data analytics methods coupled with model-based system engineer (MBSE) models. NLP methods are employed to perform syntactic and semantic analyses. Syntactic analysis analyzes the grammatical structure of a sentence; such analysis includes: part of speech (POS) tagging (i.e., identification of grammatic elements of each string - e.g., nouns, verbs), named entity recognition (i.e., identification of text entities - e.g., names, dates, events), and relation extraction (e.g., coreference resolution). On the other hand, semantic analysis is designed to analyze the logic structure of a sentence. Through a specific set of rules, our methods can identify whether a sentence contains health information of a component (e.g., degraded performance, anomaly behavior) or the causal relationship between two events (i.e., a cause-effect pair). An innovative element of our approach is that semantic analysis relies on MBSE models to identify links between textual elements. MBSE are diagrams designed to represent system and component dependencies (from both a form and functional point of view). In our approach, MBSE models emulate system engineer knowledge about component/system architecture. This paper presents in detail how the integration of NLP methods and MBSE models is performed. Few analysis examples focusing on centrifugal pumps are presented.

97 - MATHEMATICS AND COMPUTING↗