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At least 1,297 records · Page 72

Lepton flavor asymmetries: from the early Universe to BBN

Large primordial lepton flavor asymmetries with almost vanishing total baryon-minus-lepton number can evade the usual BBN and CMB constraints if neutrino oscillations lead to perfect flavor equilibration. Solving the momentum averaged quantum kinetic equations (QKEs) describing neutrino oscillations and interactions, we perform the first systematic investigation of this scenario, uncovering a rich flavor structure in stark contradiction to the assumption of simple flavor equilibration. We find (i) a particular direction in flavor space, ∆ne ≃ – 2/3 (– 1)∆n μ for normal (inverted) neutrino mass hierarchy, in which the flavor equilibration is efficient and primordial asymmetries are essentially unconstrained, (ii) a minimal washout factor, ∆$n_{e}^{2}$| BBN ≤ 0.03 (0.016) ∑ α ∆$n_{α}^{2}$| ini yielding a conservative estimate for the allowed primordial asymmetries in a generic flavor direction, and (iii) particularly strong or weak washout if one of the initial flavor asymmetries vanishes due to non-adiabatic muon- or electron-driven MSW transitions. These results open up the possibility of a first-order QCD phase transition facilitated by large lepton asymmetries as well as baryogenesis from large and compensated ∆n e = ∆n μ asymmetries. Our systematic approach of deriving momentum averaged QKEs includes collision terms beyond the damping approximation, energy transfer between the neutrino and electron-photon plasma, and provides a fast and reliable way to investigate the impact of primordial lepton asymmetries at the time of BBN. We publicly release the Mathematica code COFLASY-M on https://github.com/mariofnavarro/COFLASY which solves the QKEs numerically.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Probing neutrino quantum decoherence at reactor experiments

We explore how well reactor antineutrino experiments can constrain or measure the loss of quantum coherence in neutrino oscillations. We assume that decoherence effects are encoded in the size of the neutrino wave-packet, σ . We find that the current experiments Daya Bay and the Reactor Experiment for Neutrino Oscillation (RENO) already constrain σ > 1 . 0 × 10 - 4 nm and estimate that future data from the Jiangmen Underground Neutrino Observatory (JUNO) would be sensitive to σ < 2 . 1 × 10 - 3 nm. If the effects of loss of coherence are within the sensitivity of JUNO, we expect σ to be measured with good precision. The discovery of nontrivial decoherence effects in JUNO would indicate that our understanding of the coherence of neutrino sources is, at least, incomplete.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

The Ghent Hybrid model in NuWro: a new neutrino single-pion production model in the GeV regime

Neutrino-induced single-pion production constitutes an essential interaction channel in modern neutrino oscillation experiments, with its products building up a significant fraction of the observable hadronic final states. Frameworks of oscillation analyses strongly rely on Monte Carlo neutrino event generators, which provide theoretical predictions of neutrino interactions on nuclear targets. Thus, it is crucial to integrate state-of-the-art single-pion production models with Monte Carlo simulations to prepare for the upcoming systematics-dominated landscape of neutrino measurements. In this work, we present the implementation of the Ghent Hybrid model for neutrino-induced single-pion production in the NuWro Monte Carlo event generator. The interaction dynamics includes coherently-added contributions from nucleon resonances and a non-resonant background, merged into the pythia branching predictions in the deep-inelastic regime, as instrumented by NuWro. This neutrino-nucleon interaction model is fully incorporated into the nuclear framework of the generator, allowing it to account for the influence of both initial- and final-state nuclear medium effects. We compare the predictions of this integrated implementation with recent pion production data from accelerator-based neutrino experiments. The results of the novel model show improved agreement of the generator predictions with the data and point to the significance of the refined treatment of the description of pion-production processes beyond the ∆ region.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Predicting chatter using machine learning and acoustic signals from low-cost microphones

Machining chatter is a phenomenon resulting from self-oscillation between a machining tool and workpiece. This self-oscillation results in variation on the machined product that reduces the ability to meet desired specifications. Chatter is a widely studied topic as it directly relates to the quality of machined products. Here, this study details the application of a Random Forest (RF) classifier with Recursive Feature Elimination (RFE) to machining audio collected by a single microphone during down-milling operations. This approach allows straightforward feature elimination that results in an easily understood set of analyzed dimensions. Stability is predicted solely based on the classification output of the RF classifier. Our approach proves highly predictive with consistent machining setup and a small sample set. We also review transferability between machining setups and present key findings. Our RF approach demonstrates the ability to analyze and classify chatter through a low-cost approach with limited training data required. The motivation for using a single microphone is to enable detection on machines without other sensors, such as accelerometers, present in the machining setup. The value of the in-process sensor and chatter classifier is highlighted because the machining setup included asymmetric dynamics that reduced the accuracy of the traditional analytical stability solution. We see a natural progression to deploying this audio-only methodology with real-time processing and classification using either a laptop or smartphone. This progression will allow visual indicators during the machining process that can alert machinists of progression into unstable machining processes.

42 ENGINEERING↗

Global teleconnections influencing large-scale drought in the United States using SVDI

Understanding recent large-scale drought patterns and the mechanisms producing extreme drought events is vital for future drought forecasts and understanding future drought risks. Increasingly, vapor pressure deficit (VPD) has been used as an important measure of evaporative demand and proxy for drought detection. In this study, VPD is used to calculate the new Standardized VPD Drought Index (SVDI) with NASA North American Land Data Assimilation System (NLDAS) data. Previous studies have shown that SVDI accurately identifies the timing and magnitude short-term droughts in the United States (U.S). In the present study, SVDI is now used to identify large-scale drought patterns between 1980 and 2021 and drought variability driven by selected global teleconnections originating in the Pacific and Atlantic Oceans. Spatial drought characteristics were extracted from SVDI using empirical orthogonal function (EOF) analysis. Then a k-means clustering algorithm was applied to both EOF principal components and primary teleconnections, including the El Nino-Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO) to identify drought events driven by the Pacific Ocean. Results show that the SVDI is useful in evaluating large-scale drought variability in the U.S. related to global teleconnections, and that mechanisms influencing summer drought patterns in the Western and Southwestern U.S. are driven by a tropical-extratropical interactions originating in the equatorial Pacific Ocean related to ENSO dynamics with interdecadal variability modulated by PDO. The large-scale droughts in the Central and Southern U.S., like those in 2011 and 2012, on the other hand, are driven by the North Pacific Ocean warm pool during a strong negative PDO, which subsequently influenced variability in the Bermuda-Azores High in the Atlantic Ocean. In summer 2011, the Bermuda-Azores High weakened, reducing the onshore winds and moisture transport along the eastern Gulf of Mexico and contributing to ongoing drought in the region. The Northern Pacific and Atlantic Ocean sea surface temperatures (SSTs) have increased between 1980 and 2021. In conclusion, as SSTs continue to rise in the Northern Pacific Ocean, one consequence of the coupled North Pacific warm pool and atmospheric dynamics, is to increase summer drought variability over a large region in the southern and midwestern U.S. under global warming.

54 ENVIRONMENTAL SCIENCES↗

Experimentally simulated sea level rise destabilizes carbon-mineral associations in temperate tidal marsh soil

How sea level rise (SLR) alters carbon (C) dynamics in tidal salt marsh soils is unresolved. Changes in hydrodynamics could influence organo-mineral associations, influencing dissolved organic carbon (DOC) fluxes. As SLR increases the duration of inundation, we hypothesize that lateral DOC export will increase due to reductive dissolution of C-bearing iron (Fe) oxides, destabilizing soil C stocks and influencing greenhouse gas emissions. To test this, soil cores (0–8 cm depth) were collected from the high marsh of a temperate salt marsh that currently experiences changes in water level and soil redox oscillation due to spring-neap tides. Mesocosms experimentally simulated SLR by continuously inundating high marsh soils and were compared to mesocosms with Control conditions, where the water level oscillated on a spring-neap cycle. Porewater DOC, lateral DOC, and porewater reduced Fe (Fe 2+ ) concentrations were significantly higher in SLR treatments (1.7 ± 0.5 mM, 0.63 ± 0.14 mM, and 0.15 ± 0.11 mM, respectively) than Control treatments (1.2 ± 0.35 mM, 0.56 ± 0.15 mM, and 0.08 ± 01 mM, respectively Solid phase analysis with Fe extended X-ray absorption fine-structure spectroscopy further revealed that SLR led to > 3 times less Fe oxide-C coprecipitates than Control conditions In addition, the overall global warming potential (GWP) decreased under SLR due to suppressed CO 2 emissions. Our data suggest that SLR may increase lateral C export of current C stocks by dissolving C-bearing Fe oxides but decrease the overall GWP from emissions of soil trace gases. Finally, these findings have implications for understanding the fate of SOC dynamics under future SLR scenarios.

dissolved organic carbon↗

In-situ quantification of the surface roughness for facile fabrications of atomically smooth thin films

Here in this work we present an in-situ technique to quantify the layer-by-layer roughness of thin films and heterostructures by measuring the spectral profile of the reflection high-energy electron diffraction (RHEED). The characteristic features of the diffraction spot, including the vertical to lateral size ratio c/b and the asymmetrical ratio c 1 /c 2 along the vertical direction, are found to be quantitatively dependent on the surface roughness. The quantitative relationships between them are established and discussed for different incident angles of high-energy electrons. As an example, the surface roughnesses of LaCoO 3 films grown at different temperatures are obtained using such an in-situ technique, which are confirmed by the ex-situ atomic force microscopy. Moreover, the in-situ measured layer-by-layer roughness oscillations of two LaCoO 3 films are demonstrated, revealing drastically different information from the intensity oscillations. The experiments assisted with the in-situ technique demonstrate an outstanding high resolution down to similar to ~0.1 Å. Therefore, the new quantitative RHEED technique with real-time feedbacks significantly escalates the thin film synthesis efficiency, especially for achieving atomically smooth surfaces and interfaces. It opens up new prospects for future generations of thin film growth, such as the artificial intelligence-assisted thin film growth.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Quasilinear theory: the lost ponderomotive effects and why they matter

Quasilinear theory (QLT) has been used for modeling wave–plasma interactions for decades but remains largely heuristic. Plasma inhomogeneity, ponderomotive effects, microscopic fluctuations, and collisions are not easily accommodated from first principles in QLT, and typically are ignored entirely, due to the limitations of the standard Fourier–Laplace global-mode approach. This results in inconsistencies, for example, violation of the action conservation for nonresonant waves. However, these issues can be avoided, and the theory can be substantially generalized and corrected, if QLT is formulated using more suitable analytical tools, particularly, the Weyl symbol calculus. Here, an attempt is made to deliver an accessible review of this modern formulation, provide intuitive calculations for special cases, and elaborate on the connection with the ‘oscillation-center QLT’ originally proposed by Dewar (Phys Fluids 16:1102, 1973). A Fokker–Planck equation for a ‘dressed’ distribution is derived from the Klimontovich equation and captures quasilinear diffusion, ponderomotive forces, and interactions with background fields for a generic Hamiltonian, so many known formulations of QLT for specific plasma models become corollaries of a single unifying theory. Also, waves are allowed to be off-shell (not constrained by a dispersion relation), which allows them to accommodate microscopic fluctuations. This leads to a collision integral of the Balescu–Lenard type that has all the usual properties but is not restricted to any specific plasma model. For on-shell waves, a generalized version of the classic oscillation-center QLT is obtained. Finally, combined with the wave-kinetic equation, this formulation not only conserves particles, momentum, and energy, like the classic QLT but also reinstates the action conservation for nonresonant waves.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Assessing entropy for catalytic processes at complex reactive interfaces

When chemical reactions are accelerated by a catalyst, entropy differences between reactants and their transient intermediates can be the driving force behind the promotion or inhibition of desired and parasitic chemical pathways. Understanding and controlling catalytic processes therefore requires both a fundamental and practicable understanding of entropy in addition to enthalpy. In unstructured media such as the vapor phase equilibrated with sparsely covered surfaces, entropy can be adequately accounted for by well-established approaches based on translational, rotational, and harmonic vibrational partition functions. However, these approximations become inadequate in more complex condensed phase environments, e.g., solid liquid interfaces of confined reaction spaces. In this chapter, we provide an overview of the state-of-art in the computational quantification of entropy and its known ramifications on catalysis. The fundamental roles of thermodynamics and kinetics in catalysis are covered in enough detail to appreciate and contextualize the computational methods employed to compute chemically accurate estimates of entropy. These methods are discussed in appropriate detail and range from the ubiquitous harmonic oscillator approximation where entropy unrelated to high frequency oscillations is typically underestimated, to enhanced free energy sampling with molecular dynamics where the desired accuracy must be weighed against the associated computational cost of obtaining it. The rising importance of machine learning and artificial intelligence in accelerating methodological progress in this field is touched upon, as well. Finally, applications, successes, and pitfalls of using these methods are provided to showcase past and present accomplishments while clarifying where improvements in both understanding and methodology are still needed.

Kollias, Loukas↗

Derivative-based SINDy (DSINDy): Addressing the challenge of discovering governing equations from noisy data

Recent advances in the field of data-driven dynamics allow for the discovery of ODE systems using state measurements. One approach, known as Sparse Identification of Nonlinear Dynamics (SINDy), assumes the dynamics are sparse within a predetermined basis in the states and finds the expansion coefficients through linear regression with sparsity constraints. This approach requires an accurate estimation of the state time derivatives, which is not necessarily possible in the high-noise regime without additional constraints. We present an approach called Derivative-based SINDy (DSINDy) that combines two novel methods to improve ODE recovery at high-noise levels. First, we denoise the state variables by applying a projection operator that leverages the assumed basis for the system dynamics. Second, we use a second order cone program (SOCP) to find the derivative and governing equations simultaneously. We derive theoretical results for the projection-based denoising step, which allow us to estimate the values of hyperparameters used in the SOCP formulation. This underlying theory helps limit the number of required user-specified parameters. Finally, we present results demonstrating that our approach leads to improved system recovery for the Van der Pol oscillator, the Duffing oscillator, the Rössler attractor, and the Lorenz 96 model.

97 MATHEMATICS AND COMPUTING↗

Pressure-stabilized fixed-stress iterative solutions of compositional poromechanics

We consider the numerical behavior of the fixed-stress splitting method for coupled poromechanics as undrained regimes are approached. We explain that pressure stability is related to the splitting error of the scheme, not the fact that the discrete saddle point matrix never appears in the fixed-stress approach. This observation reconciles previous results regarding the pressure stability of the splitting method. Using examples of compositional poromechanics with application to geological CO sequestration, we see that solutions obtained using the fixed-stress scheme with a low order finite element-finite volume discretization which is not inherently inf-sup stable can exhibit the same pressure oscillations obtained with the corresponding fully implicit scheme. Moreover, pressure jump stabilization can effectively remove these spurious oscillations in the fixed-stress setting, while also improving the efficiency of the scheme in terms of the number of iterations required at every time step to reach convergence.

42 ENGINEERING↗

Nonlinear dynamics of combustor azimuthal modes: Experiments and modeling

This paper provides an experimental and theoretical investigation of azimuthal instabilities in a lean, premixed combustor. It presents data from a high Reynolds number, industrial-scale facility with multiple fuel stages that enable variation of radial and azimuthal symmetries. The combustor exhibits a variety of behaviors – including standing, spinning, mixed waves, and intermittent behaviors, as well as periodic limit cycles and quasi-periodic oscillations – depending upon varying power and azimuthal symmetry. A second key objective of this paper is to present a weakly nonlinear framework that is used to understand and interpret these results, showing the influence of eigenmode degeneracy, background noise, and azimuthal non-uniformities in mean quantities such as temperature and flame-acoustic coupling. In particular, this analysis shows the importance of the linear instability growth/damping rate and azimuthal non-uniformities in controlling the relative prominence of standing, spinning, or mixed waves at the limit cycle, as well as the preference in the spinning direction. It also shows the conditions under which single frequency or quasi-periodic oscillations are dominant, and how these are more fundamentally influenced by azimuthal non-uniformities and background noise.

42 ENGINEERING↗

Thermal and electric multidomain dynamic model for integration of power grid distribution with behind-the-meter devices

As renewable energy sources like solar and wind power become more integrated into the grid, coordinated control of behind-the-meter devices is crucial for enhancing grid flexibility and reliability and for meeting cost targets, with standardized models being developed to support this transition. The increasing flexibility and uncertainty of integrated renewable energy grids, along with interactions between various subsystems, make traditional steady-state modeling insufficient to capture transient and dynamic behaviors. Current models (e.g., composite load and battery equivalent models) focus on thermodynamic or electrical characteristics but overlook critical electromechanical interactions. This limits the ability to share performance information for grid services and hampers fast dynamic simulations. In addition, motor stalling is usually triggered by a fault event and attributed to the characteristics of the mechanical torque of the motor, resulting in absorption of a large amount of reactive power during the stalling period. Further, this significant withdrawal of reactive power will deteriorate the dynamic voltage stability of power grids and cause delayed voltage recovery. Therefore, an in-depth modeling of the thermodynamics or mechanical torque is essential to study the impacts of the realistic torque characteristics of those behind-the-meter devices on power system voltage stability. This study developed a dynamic multidomain model for building HVAC systems, such as air-source heat pumps, to simulate their thermal and electrical responses to grid transients. The model can accurately predict power metrics with a mean absolute percentage error of 10%, by validating against with power system computer-aided design performance data. Case studies demonstrate the model capability of capturing the transient response to sudden voltage changes, rapid load fluctuations, and system shutdowns respectively. During a sudden voltage drop (30% for 0.1s), a fully loaded heat pump’s motor speed dropped, continued declining, and shut down after 3.6s, with severe power oscillations and a torque spike. A partially loaded unit experienced temporary oscillations but stabilized. Under higher building loads, compressor speed increased from 64% to 100%, with power and torque rising before stabilizing. In safety-triggered shutdowns, power decreased after minor fluctuations, and torque briefly spiked before dropping to zero.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Effects of knock intensity measurement technique and fuel chemical composition on the research octane number (RON) of FACE gasolines: Part 2 – Effects of spark timing

The Research and Motor Octane Number (RON, MON) characterize a fuel’s knock resistance by rating the knock intensity of a sample fuel relative to that of Primary Reference Fuels (PRF) in a Cooperative Fuel Research (CFR) Engine. A fuel’s octane number is regulated to prevent damage from autoignition leading to knocking combustion in spark-ignition engines. The operational differences between the standard RON rating and modern engine operation are explored in a three-part publication series. The previous study focused on the effects of lambda and knock characterization. This second study primarily focuses on the effects of spark timing on RON determination. Following the findings from the first publication, the knock intensity was captured by the knockmeter and by the maximum amplitude of pressure oscillations (MAPO) at the lambda of peak knock intensity and stoichiometry. Knock-limited spark advance tests were conducted for a set of seven Fuels for Advanced Combustion Engines (FACE) from the Coordinating Research Council (CRC) with varying chemical composition, PRFs, and Toluene Standardization Fuels (TSFs). For retarded spark timings, pre-spark low-temperature heat release was found for low RON PRFs. Low RON PRFs also showed knocking characteristics before reaching the center of combustion suggesting that the use of knock-limited spark advance (KLSA) was preferred over the knock-limited combustion phasing. Primarily paraffinic fuels tended towards increased pressure oscillations while dominantly aromatic fuels experienced higher pressure rise rates. A MAPO-based KLSA correlated best to Octane Index at a negative K-factor suggesting beyond RON operation despite being at otherwise RON conditions. At stoichiometry, the MAPO-based KLSA did neither correlate to RON nor Octane Index. Finally, good agreement was found between KLSA-based effective RON from this study to the MAPO-based effective RON from the first study.

10 SYNTHETIC FUELS↗

Revealing melt flow instabilities in laser powder bed fusion additive manufacturing of aluminum alloy via in-situ high-speed X-ray imaging

Laser metal additive manufacturing technologies enable the fabrication of geometrically and compositionally complex parts unachievable by conventional manufacturing methods. However, the certification and qualification of additively manufactured parts are greatly hindered by the stochastic melt flow instabilities intrinsic to the process, which has not been explicitly revealed by direct observation. Here, we report the mechanisms of the melt flow instabilities in laser powder bed fusion additive manufacturing process revealed by in-situ high-speed high-resolution synchrotron X-ray imaging. Here we identified powder/droplet impact, significant keyhole oscillation, and melting-mode switching as three major mechanisms for causing melt flow instabilities. We demonstrated the detrimental consequences of these instabilities brought to the process, and presented new understanding on the melt flow evolution and keyhole oscillation. This work provides critical insights into process instabilities during laser metal additive manufacturing, which may guide the development of instability mitigation approaches. The results reported here are also important for the development and validation of high-fidelity computational models.

36 MATERIALS SCIENCE↗

A quadratic programming flux correction method for high-order DG discretizations of S transport

In this work, we present a new flux-fixup approach for arbitrarily high-order discontinuous Galerkin (DG) discretizations of the S N transport equation, and we demonstrate the compatibility of this approach with the Variable Eddington Factor (VEF) method. The new fixup approach is sweep-compatible: during a transport sweep (block Gauss-Seidel iteration in which the scattering source is lagged), a local quadratic programming (QP) problem is solved in each spatial element to ensure that the solution satisfies certain physical constraints, including local particle balance. In this paper, we describe two choices of physical constraints, resulting in two variants of the method: QP Zero (QPZ) and QP Maximum Principle (QPMP). In QPZ, the finite element coefficients of the solution are constrained to be nonnegative. In QPMP, they are constrained to adhere to an approximate discrete maximum principle. There are two primary takeaways in this paper. First, when the positive Bernstein basis is used for DG discretization, the QPMP method eliminates negativities, preserves high-order accuracy for smooth problems, and significantly dampens unphysical oscillations in the solution. The latter feature – the dampening of unphysical oscillations – is an improvement upon standard, simpler fixup approaches such as the approach described in (denoted as the “zero and rescale” (ZR) method in this paper). This improvement comes at a moderate computational cost, but it is not prohibitive. Our results show that, even in an unrealistic worst-case scenario where 83% of the spatial elements require a fixup, the computational cost of performing a transport sweep with fixup is only ~31% greater than performing one without fixup. The second takeaway is that the VEF method can be used to accelerate the convergence of transport sweeps even when a fixup is applied. When optically thick regions are present, transport sweeps converge slowly, regardless of whether a fixup is applied, and acceleration is needed. However, attempting to apply standard diffusion synthetic acceleration (DSA) to fixed-up transport sweeps results in divergence for optically thick problems. Our results show that the same is not true for VEF. When VEF is combined with fixed-up transport sweeps, the result is a scheme that produces a nonnegative solution, converges independently of the mean free path, and, in the case of the QPMP fixup, adheres to an approximate discrete maximum principle.

97 MATHEMATICS AND COMPUTING↗

X-ray observation of individual Ti-6Al-4V spherical powder particle impact in an in-situ operando laser directed energy deposition system

Understanding the particle capture mechanism in the laser directed energy deposition additive manufacturing process provides a foundation for improving productivity and reducing material loss. Capturing this phenomenon is challenging due to its highly transient time interval. To analyze the impact behavior of spherical Ti-6Al-4V powder, a custom laser directed energy deposition system was designed to control the deposition of individual particles. Synchrotron X-ray imaging at 24 kHz monitored the impact dynamics of individual powder particles. A multi-physics model based on the Smoothed-Particle Hydrodynamics scheme supported the analysis by providing the temperature and velocity fields of the molten pool. Results revealed that in laser directed energy deposition, surface tension forces dominated the powder–molten pool interaction. Hydrophobic Ti-6Al-4V powder particles had an equilibrium contact angle of 121 degrees with their molten state. Furthermore, Ti-6Al-4V powder particles required a high impact velocity (6 to 12 m/s) to transition from oscillation to submergence behavior. Lastly, oscillating powder particles that impacted near the location of the laser beam exhibited faster melting, highlighting the contribution of the laser beam to the melting mechanism. This work lays the foundation for investigations of powder particle impact in laser directed deposition and supports the validation of numerical models of powder–molten pool interactions.

36 MATERIALS SCIENCE↗