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At least 415 records · Page 23

Bootstrapping smooth conformal defects in Chern-Simons-matter theories

Abstract The expectation value of a smooth conformal line defect in a CFT is a conformal invariant functional of its path in space-time. For example, in largeNholographic theories, these fundamental observables are dual to the open-string partition function in AdS. In this paper, we develop a bootstrap method for studying them and apply it to conformal line defects in Chern-Simons matter theories. In these cases, the line bootstrap is based on three minimal assumptions — conformal invariance of the line defect, largeNfactorization, and the spectrum of the two lowest-lying operators at the end of the line. On the basis of these assumptions, we solve the one-dimensional CFT on the line and systematically compute the defect expectation value in an expansion around the straight line. We find that the conformal symmetry of a straight defect is insufficient to fix the answer. Instead, imposing the conformal symmetry of the defect along an arbitrary curved line leads to a functional bootstrap constraint. The solution to this constraint is found to be unique.

Physics↗

Visualization of R410A Flow Boiling Inside Horizontal Smooth Tubes under Diabatic Conditions

This article presents a novel approach to visualize the flow boiling in round tubes under “diabatic conditions”. In the visualization test section, a 3D printed round tube is placed inside a glass tube with secondary fluid at a higher temperature flowing in the annulus between the two tubes thus providing diabatic conditions. Experimental work was conducted for evaporating R410A flow in a horizontal smooth round tube with the inner diameter of 6.3 mm. Compared to the traditional adiabatic visualization technique, the more realistic evaporative condition is simulated and the developing evaporation process is captured. New insights for the flow behavior at low vapor quality are brought by this diabatic method. The vapor plug occurs at very low vapor quality, and this is attributed to the coalescence of bubbles generated on the heated tube wall. For the intermittent flow, liquid slug triggered by Kelvin–Helmholtz instability affects the nucleation on the tube wall. It brings the fresh liquid to rewet the dry surface and activate the nucleation sites. Finally, heat flux condition affects the heat transfer mechanisms during the flow boiling, and the heat transfer through the nucleate boiling mechanism increases as the heat flux increases.

3D printed↗

Understanding Improvements in Coalesced Epilayers Grown over Nanopatterned Substrates

Nanopatterned substrates provide opportunities for reducing costs of high-efficiency III-V devices through methods such as substrate reuse and growth on cheaper substrates. In this work, we aim to better understand some of the fundamental challenges of growing high quality III-V material on nanopatterned substrates. Through specific pattern orientations and control of overgrowth morphology, we report that smooth and defect-free coalesced III-V epilayers are attainable over nanopatterned GaAs substrates.

coalescense↗

Pedestrian-Involved Traffic Signal Optimization Using Decentralized Graph-based Multi-Agent Reinforcement Learning

Incorporating pedestrian movements in traffic signal timing optimization is essential for ensuring smooth and safe urban transportation systems. To develop an effective signal timing plan, it is crucial to comprehend how various pedestrian accommodation strategies impact both vehicle and pedestrian flow. This study explores the application of the Decentralized Graph-based Multi-Agent Reinforcement Learning (DGMARL) method for signal timing optimization. It considers both pedestrian and vehicle traffic state and assesses the effects of fixed and adaptive pedestrian request response on traffic and signal timing. The evaluation of DGMARL encompasses vehicles Eco_PI which is fuel consumption impact related to vehicle stops and stop delay, and pedestrian waiting time to ensure overall system efficiency. The proposed approach was evaluated using a Digital Twin microscopic traffic simulation model of MLK Smart Corridor in Chattanooga, Tennessee. The evaluation outcomes of vehicles Eco_PI, pedestrian waiting time and serving time are compared with the actuated and DGMARL signal timing with fixed pedestrian recall and minimum recall to determine the most suitable approaches for various traffic conditions. The results indicated that, on average, the strategy of Signal timing optimization with adaptive pedestrian request response improved the Eco_PI by 32.43%, and Signal timing optimization with both automated pedestrian traffic demand and adaptive pedestrian request response improved the Eco_PI by 31.62% compared to the actuated and DGMARL signal timing with fixed pedestrian recall and minimum recall.

K Kumarasamy, Vijayalakshmi↗

Development and transferability of neural-network models for plasma-surface interactions

Plasma-surface interactions are increasingly critical to modern technologies; yet, accurate molecular dynamics simulations remain limited by the capabilities of interatomic potentials. Deep Potentials (DPs) promise to revolutionize the field by providing a systematic method for producing accurate interatomic potentials. The primary challenge of DP development is selecting a dataset, which efficiently spans the set of atomic environments one expects to encounter in the subsequent molecular dynamics simulations. The computational cost of density functional theory calculations, which are the typical basis for DP development, makes it impossible to directly verify the quality of a given DP. To address this challenge, we explore the development of a deep-learned interatomic potential, “DeepREBO,” trained to reproduce the behavior of the REBO2 empirical potential, enabling direct validation of training methodology and transferability. Using an active learning framework, we begin with a minimal dataset and iteratively expand it to train a Deep Potential-Smooth Edition model that faithfully reproduces REBO2 results for 25 eV hydrogen bombardment of diamond (001), a particularly challenging case. We show that small, carefully curated datasets can outperform large, unguided ones, with effective models requiring fewer than 15 000 snapshots. Subsequent transferability tests demonstrate that while DeepREBO generalizes well to diamond (111) surfaces, performance degrades for amorphous carbon or higher-energy impacts, highlighting the need for use-case-specific training data. We also evaluate methods to improve short-range repulsion. This study outlines best practices for training robust deep potentials and underscores the importance of dataset design for predictive plasma simulations.

Ab-initio molecular dynamics↗

Classification Analytics of Pu-239 and U-235 Source Signatures Using Gamma Spectral Regions

Machine learning detection methods using gamma signatures from spectral measurements of low-intensity Pu-239 and U-235 sources are studied. NaI detectors located at different distances fromthe source have been used to collect the training and independent testing data sets. The source is introduced via a shielded conduit into the facility where it is surrounded by 21 NaI detectors deployed over 6 x 6 meters area in the formation of two concentric circles and a spiral. The counts in gamma spectral regions associated with these two sources are estimated at 1 second intervals for each NaI detector, and are used as classifier features for detecting the source presence. Eight different classifiers with five basic properties — namely, smooth, non-smooth, statistical, structural, and hyper-parameter tuning — are trained and tested using the background and source measurements collected over multiple experimental runs. While the overall classifier performance improved as detectors closer to the source are used, some identically produced detectors under-performed but differently between two sources. Some classifiers achieved lower training error but their testing error based on independent measurements is higher for both sources. Overall, these results indicate significant over-fitting by these methods, and illustrate the complexity of training and selecting the machine learning methods to solve these detection problems.

Rao, Nageswara↗

BeyondPlanck: V. Minimal ADC Corrections for Planck LFI

We describe the correction procedure for Analog-to-Digital Converter (ADC) differential non-linearities (DNL) adopted in the Bayesian end-to-end BEYONDPLANCK analysis framework. This method is nearly identical to that developed for the official Planck Low Frequency Instrument (LFI) Data Processing Center (DPC) analysis, and relies on the binned rms noise profile of each detector data stream. However, rather than building the correction profile directly from the raw rms profile, we first fit a Gaussian to each significant ADC-induced rms decrement, and then derive the corresponding correction model from this smooth model. The main advantage of this approach is that only samples which are significantly affected by ADC DNLs are corrected, as opposed to the DPC approach in which the correction is applied to all samples, filtering out signals not associated with ADC DNLs. The new corrections are only applied to data for which there is a clear detection of the non-linearities, and for which they perform at least comparably with the DPC corrections. Out of a total of 88 LFI data streams (sky and reference load for each of the 44 detectors) we apply the new minimal ADC corrections in 25 cases, and maintain the DPC corrections in 8 cases. All these corrections are applied to 44 or 70 GHz channels, while, as in previous analyses, none of the 30 GHz ADCs show significant evidence of non-linearity. By comparing the BEYONDPLANCK and DPC ADC correction methods, we estimate that the residual ADC uncertainty is about two orders of magnitude below the total noise of both the 44 and 70 GHz channels, and their impact on current cosmological parameter estimation is small. However, we also show that non-idealities in the ADC corrections can generate sharp stripes in the final frequency maps, and these could be important for future joint analyses with the Planck High Frequency Instrument (HFI), Wilkinson Microwave Anisotropy Probe (WMAP), or other datasets. We therefore conclude that, although the existing corrections are adequate for LFI-based cosmological parameter analysis, further work on LFI ADC corrections is still warranted.

79 ASTRONOMY AND ASTROPHYSICS↗

In Tube Condensation Heat Transfer and Pressure Drop for R454B and R32—Potential Replacements for R410A

The heating, ventilation and air conditioning (HVAC) industry in the United States seeks near-term alternative refrigerants to replace R-410A in unitary equipment. Two potential replacement refrigerants are R-454B and R-32. It is of interest to investigate the capability and accuracy of existing heat exchanger design methods when applied to these replacement refrigerants. To that end, this work presents empirical condensation quasi-local heat transfer coefficient and pressure drop data for R-454B and R-32. These data were obtained in a $\frac{3}{8}$ in. (9.52 mm) outside diameter (OD) smooth copper tube with a wall thickness of 0.032 in. (0.81 mm). The experimental variables and their ranges included refrigerant absolute pressure ( 1960 ≤ P a b s ≤ 3196 kPa), condensation temperature ( 35 ≤ T c o n d ≤ 50 °C), mass flux ( 100 ≤ G ≤ 200 kg m -2 s -1 ), vapor quality ( 0 ≤ x ≤ 1 ), and heat flux ( 32.9 ≤ q ″ ≤ 62.97 kW m -2 ). It was found that the heat transfer correlation developed by Cavallini et al. Cavallini et al. (2006) predicted the experimental condensation heat transfer data, for both R-454B and R-32, with the greatest accuracy. Using the Cavallini et al. correlation, it was found that the mean absolute percentage error (MAPE) was 10.5% and 15.1% for R-454B and R-32, respectively. Additionally, the pressure drop correlation developed by Friedel Friedel (1979) predicted the experimentally determined pressure gradient with a MAPE of 7.7% and 5.5% for R-454B and R-32, respectively. These results will assist the practicing thermal engineer to choose the most appropriate design correlation for these near-term replacement refrigerants.

42 ENGINEERING↗

Modulating effect of evanescent waves on thin film growth

Atomic-scale smooth thin films are keys to successful integration and proper function of many multilayer-structured devices. However, the intrinsic islandlike growth mode prevents human beings from realizing such ultrasmooth films of many important functional materials. To solve this problem, we propose a negative entropy-infusing method that employs evanescent waves to enhance the downward interlayer diffusion of adatoms and thus transform the islandlike growth mode to the layer-by-layer growth mode. In this work, the formulas of the optical force and the lowered diffusion barrier were derived, and the application of this theory on a simplified example demonstrates significantly improved surface morphologies through numerical simulations.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

MFANS 2024 - Formally Proving Characteristics of Cyber-Physical Systems

Cyber-physical systems (CPS) are engineered systems that rely on the smooth integration of computational algorithms and physical elements. This integration presents new challenges for verifying that systems will behave as expected. The goal of this presentation is to present current challenges and potential solutions for the formal verification of cyber-physical systems. For cyber systems, formal methods refer to systematically rigorous mathematical techniques employed in the specification, development, analysis, and verification of both software and hardware systems. Recent advancements in computer science have yielded sophisticated tools specifically designed to address challenges associated with formal methods in complex systems. These tools leverage various foundational concepts such as logic, formal languages, program semantics, type systems, type theory, and automata theory. A notable achievement in the application of formal methods is the seL4 microkernel, claimed to be the first general-purpose operating-system kernel to be verified. Its proof implies the absence of bugs and guarantees that the kernel meets specifications. For physical systems, dynamic and control theory has a history of using rigorous analytic techniques to prove functional correctness. Lyapunov, optimal, classical, modern, and robust control theories all provide rigorous mathematical methods both to analyze system performance and to design controller that can be guaranteed to meet certain objectives. Recent computational techniques like level set theory and reachability analysis provide assertions that a system's state will avoid unsafe regions. Even though success has been independently achieved for cyber systems and physical systems, the integration of such systems creates new challenges. In particular, there is an obvious discrepancy between finite-state machines and infinite-state systems, resulting in different approaches for modeling and analyzing these system. While it is possible to simulate hybrid systems, this provides only a demonstration of a performance and not proof. For hybrid systems, current formal methods and system analysis approaches typically require a workarounds to work on hybrid systems like CPS. This paper will outline the state of the art and limits of current practice for formally verifying CPS and will identify possible research directions that require attention.

97 MATHEMATICS AND COMPUTING↗

A group finder algorithm optimised for the study of local galaxy environments

Context. The majority of galaxy group catalogues available in the literature use the popular friends-of-friends algorithm which links galaxies using a linking length. One potential drawback to this approach is that clusters of points can be linked with thin bridges which may not be desirable. In order to study galaxy groups, it is important to obtain realistic group structures. Aim. Here, in this study, we present a new simple group finder algorithm, TD-ENCLOSER, that finds the group that encloses a target galaxy of interest. Methods. TD-ENCLOSER is based on the kernel density estimation method which treats each galaxy, represented by a zero-dimensional particle, as a two-dimensional circular Gaussian. The algorithm assigns galaxies to peaks in the density field in order of density in descending order (‘top down’) so that galaxy groups ‘grow’ around the density peaks. Outliers in under-dense regions are prevented from joining groups by a specified hard threshold, while outliers at the group edges are clipped below a soft (blurred) interior density level. Results. The group assignments are largely insensitive to all free parameter variations apart from the hard density threshold and the kernel standard deviation, although this is a known feature of density-based group finder algorithms and it operates with a computing speed that increases linearly with the size of the input sample. In preparation for a companion paper, we also present a simple algorithm to select unique representative groups when duplicates occur. Conclusions. TD-ENCLOSER is tested on a mock galaxy catalogue using a smoothing scale of 0.3 Mpc and is found to be able to recover the input group distribution with sufficient accuracy to be applied to observed galaxy distributions.

79 ASTRONOMY AND ASTROPHYSICS↗

Computation of Direct Sensitivities of Spatial Multibody Systems With Joint Friction

Abstract Friction exists in most mechanical systems and may have a major influence on the dynamic performance of the system. The incorporation of friction in dynamic systems has been a subject of active research for several years owing to its high nonlinearity and its dependence on several parameters. Consequently, optimization of dynamic systems with friction becomes a challenging task. Gradient-based optimization of dynamical systems is a prominent technique for optimal design and requires the computation of model sensitivities with respect to the design parameters. The novel contribution of this paper is the derivation of the analytical methodology for the computation of direct sensitivities for smooth multibody systems with joint friction using the Lagrangian index-1 formulation. System dynamics have been computed using two different friction models; the Brown and McPhee, and the Gonthier et al. model. The methodology proposed to obtain model sensitivities has also been validated using the complex finite difference method. A case study has been conducted on a spatial multibody system to observe the effect of friction on the dynamics and model sensitivities, compare sensitivities with respect to different parameters and demonstrate the numerical and validation aspects. Since design parameters can have very different magnitudes and units, the sensitivities have been scaled with the parameters for comparison. Finally, a discussion has been presented on the interpretation of the case study results. Due to the incorporation of joint friction, ‘jumps’ or discontinuities are observed in the model sensitivities akin to those observed for hybrid dynamical systems.

Engineering↗

Adaptive immersed isogeometric level-set topology optimization

Here, this paper presents for the first time an adaptive immersed approach for level-set topology optimization using higher-order truncated hierarchical B-spline discretizations for design and state variable fields. Boundaries and interfaces are represented implicitly by the iso-contour of one or multiple level-set functions. An immersed finite element method, the eXtended IsoGeometric Analysis, is used to predict the physical response. The proposed optimization framework affords different adaptively refined higher-order B-spline discretizations for individual design and state variable fields. The increased continuity of higher-order B-spline discretizations together with local refinement enables direct control over the accuracy of the representation of each field while simultaneously reducing computational cost compared to uniformly refined discretizations. A flexible mesh adaptation strategy enables local refinement based on geometric measures or physics-based error indicators. These adaptive discretization and analysis approaches are integrated into gradient-based optimization schemes, evaluating the design sensitivities using the adjoint method. Numerical studies illustrate the features of the proposed framework with static, linear elastic, multi-material, two- and three-dimensional problems. The examples provide insight into the effect of refining the design variable field on the optimization result and the convergence rate of the optimization process. Using coarse higher-order B-spline discretizations for level-set fields promotes the development of smooth designs and suppresses the emergence of small features. Moreover, adaptive mesh refinement for state variable fields results in a reduction of overall computational cost. Higher-order B-spline discretizations are especially interesting when evaluating gradients of state variable fields due to their higher inter-element continuity.

36 MATERIALS SCIENCE↗

A Lizard-inspired Tube Inspector (LTI) Robot

This final report summarizes the research findings of the current project. This project is a collaboration between New Mexico State University (NMSU) as a lead (Recipient) and Arizona State University (ASU) as a Co-Recipient. Tubular structures are common components of boilers and heat exchangers in power plants. Over time, these components may suffer corrosion, cracks, and stress-corrosion cracks in either the body or the welded connections. A single tube leakage can cause an outage of several weeks. Regular inspection is a key safety factor when ensuring that power plants are maintained in reliable, operational condition. This inspection, however, is challenging, time-consuming, and in many cases impossible due to accessibility issues and safety concerns. Recent developments in robotic-based inspection can offer a great solution. Hard-to-reach places can be inspected without overhauling the unit, saving time and cost. Although several robots have been designed and implemented successfully for inspecting power plant components, in particular tubular structures, their mobility and flexibility are limited. Most of these robots use wheels for mobility which reduces their maneuverability of these robots. Moreover, they usually use magnets to attach to tubes which will not work on tubes with non-ferromagnetic materials. These robots usually carry measurement tools for a particular non-destructive testing (NDT) method such as ultrasound testing (UT) that requires a couplant to perform a point-by-point (scanning) inspection of the tubular structure. In this project, we developed a versatile lizard-inspired tube inspector (LTI) robot with embedded inspection sensing components for tube inspection which removes the need for point-by-point scanning of tube surface for crack and corrosion detection. Inspired by a “lizard”, the novelty of the current project is the integration of couplant-free ultrasound sensing and transmission, advanced data-driven defect detection and imaging, and friction-based mechanical mobility components in a single robot to eliminate a need for smooth surfaces and simple geometry for mobility and scanning. The LTI robot could replace the wheel-based approach with friction-based mobility to significantly increase the flexibility and maneuverability of the robot. The LTI robot can get into a power plant unit, such as a boiler, from a small area allowing it to access a component of interest for inspection (e.g., move on OD, curved and flat surfaces, non-ferromagnetic or ferromagnetic materials, and tubes with rough surfaces and complex geometries). Additionally, an advanced data-driven method using ultrasound data was pioneered to allow the robot to detect defects in the entire area between the robot’s multi-functional mobility system (grippers). Integrating a couplant-free ultrasound sensing in the robot’s grippers as well as using advanced data-driven methods allowed the LTI to detect defects in the entire cross-section of a tube using its grippers when stationary and when mobile.

20 FOSSIL-FUELED POWER PLANTS↗

Carbene Functionalization of Monolayer Tungsten Disulfide for Enhanced Quantum Emission

Semiconducting two-dimensional (2D) transition metal dichalcogenides (TMDs) are promising materials for an array of applications, ranging from conventional field-effect transistors, photodetectors, and light-emitting diodes to their more recent use in quantum photonic technologies. Chemical functionalization of 2D TMDs with organic ligands and adlayers provides an additional means for customizing their electronic and optical properties. While many pathways have been reported for the chemical functionalization of 2D TMDs, their frequent reliance on solution-based methods results in limited control over adlayer thickness and coverage, thus hindering utility in high-performance applications. Here, in this study, we describe the vapor-phase functionalization of a 2D TMD with carbene ligands, specifically tungsten disulfide (WS 2 ) with N-heterocyclic carbenes (NHCs), resulting in molecularly smooth, thin, and uniform adlayers. Reacting NHCs with monolayer WS 2 reduces the broad photoluminescence background observed at cryogenic temperatures by 58%, which facilitates the detection of single-photon emitters from strained monolayer WS 2 , as indicated by second order correlation values ( g (2) ) as low as 0.17 ± 0.07. Chemical characterization coupled with density functional theory calculations suggests that the NHC adlayer has a dual defect-passivation and doping effect on monolayer WS 2 that results in enhanced single-photon emission. Overall, this study establishes vapor-phase carbene functionalization as a homogeneous surface modification scheme for tailoring the quantum emission properties of semiconducting 2D TMDs.

N-heterocyclic carbenes↗

Code for paper "Reconstructing an Implosion with Space-Time Smoothing of Velocimetry Traces"

New diagnostics to obtain high-temporal resolution observation of surface velocity provide a rich collection of data from high-explosive (HE) experiments. Using this data to estimate the temporal evolution of an imploding, HE-driven surface is of great interest for validating simulation of the physical system and for design of future experiments. This is the code for a paper in which we propose a method for using a Gaussian process to estimate the surface position over time and provide uncertainty estimates on that reconstruction accounting for measurement error, uncertainty to sparse spatial sampling velocity data, and robustness to outlying observations. In the paper, the code is applied on data from a hemispherical HE implosion experiment. This code is for release with the paper for peer-review, replicating the results and making the figures from the paper.

Grosskopf, Michael↗

Discrete element simulation of Pebble Bed Reactors on graphics processing units

Prediction of pebble positions in a Pebble Bed Reactor (PBR) is necessary for both reactor physics and thermal hydraulics simulations as the arrangement of pebbles has a significant impact on the resulting core power, coolant flow, and fuel temperature. Knowledge of pebble movement as the fuel is cycled through the core is also critical for predicting the fuel residence time and subsequently, the fuel burnup. Simulation with the Discrete Element Method (DEM) can provide knowledge of both the fuel packing and the fuel movement during cycling. Previous works that have performed 3D full-core DEM simulation of PBRs have used simplified models that neglect reflector wall features. This work employs a graphics processing unit (GPU)-enabled DEM code, Project Chrono, to analyze the differences in pebble packing and pebble velocities between a simplified smooth PBR reflector and a more realistic reflector that includes circular wall features. Additionally, a sensitivity study is performed on the depth of the wall features to ensure that crystallization is prevented. Project Chrono is also validated for PBR cycling applications using experimental data. It is found that wall features with a depth of at least 0.5 pebble diameters significantly reduce crystallization in the near-wall region, leading to discrepancies in both packing fraction and pebble velocity in this region compared to the simplified reflector models. These discrepancies are found to lead to roughly a 5–10% difference in the prediction of the near-wall porosity and a 10% difference in the prediction of the velocity of pebbles near the wall. As a result of these discrepancies, it is suggested that future DEM simulations of PBRs include wall features to reduce modeling errors.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

The interplay of excitonic delocalization and vibrational localization in optical lineshapes: A variational polaron approach

The dynamics of molecular excitonic systems are complicated by a competition between electronic coupling (which drives delocalization) and vibrational-electronic (vibronic) interactions (which tend to encourage electronic localization). A particular challenge of molecular systems is that they typically possess a large number of independent vibrations, with frequencies often spanning the entire spectrum of relevant electronic energy gaps. Recent spectroscopic observations and numerical simulations on a water-soluble chlorophyll-binding protein (WSCP) reveal a transition between two regimes of vibronic behavior, a Redfield-like regime in which low-frequency vibrations respond to a delocalized excitonic state, and a Förster-like regime where high-frequency vibrations act as incoherent excitations on individual pigments. Although numerical simulations can reproduce these effects, there is a need for a simple, systematic theory that accurately describes the smooth transition between these two regimes in experimental spectra. Here we address this challenge by generalizing the variational polaron transform approach of [Bloemsma et al., Chem. Phys. 481, 250 (2016)] to include arbitrary bath densities for systems with or without symmetry. We benchmark this theory against both numerical matrix-diagonalization methods and experimental 77 K fluorescence spectra for two WSCP variants, obtaining quite satisfactory agreement in both cases. Here, we apply this theory to offer an explanation for the large loss in apparent electronic coupling in the WSCP Q57K mutant and to examine the likely impact of the interplay between excitonic delocalization and vibrational localization on vibrational sideband shapes and apparent coupling strengths in high-resolution optical spectra for chlorophyll-protein complexes such as WSCP.

14 SOLAR ENERGY↗