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At least 1,171 records · Page 65

Wealth inequality in the prehispanic northern US Southwest: from Malthus to Tyche

Persistent differences in wealth and power among prehispanic Pueblo societies are visible from the late AD 800s through the late 1200s, after which large portions of the northern US Southwest were depopulated. In this paper we measure these differences in wealth using Gini coefficients based on house size, and show that high Ginis (large wealth differences) are positively related to persistence in settlements and inversely related to an annual measure of the size of the unoccupied dry-farming niche. We argue that wealth inequality in this record is due first to processes inherent in village life which have internally different distributions of the most productive maize fields, exacerbated by the dynamics of systems of balanced reciprocity; and second to decreasing ability to escape village life owing to shrinking availability of unoccupied places within the maize dry-farming niche as villages get enmeshed in regional systems of tribute or taxation. We embed this analytical reconstruction in the model of an ‘Abrupt imposition of Malthusian equilibrium in a natural-fertility, agrarian society’ proposed by Puleston et al. (Puleston C, Tuljapurkar S, Winterhalder B. 2014 PLoS ONE 9, e87541 (doi:10.1371/journal.pone.0087541)), but show that the transition to Malthusian dynamics in this area is not abrupt but extends over centuries. This article is part of the theme issue ‘Evolutionary ecology of inequality’.

99 GENERAL AND MISCELLANEOUS↗

Dynamic Interaction of Grid-Forming and Grid-Following Inverters with Synchronous Generators in Hybrid Power Plants

As the integration of renewable energy resources such as wind and solar generation continues to grow, the use of hybrid power plants with both synchronous machines and power electronic inverters operating in parallel becomes more common. This paper studies the impact on small-signal stability for these pairs of devices, first as an isolated two-device system and then as part of a 9-bus test system. Each operational scenario was studied with both a grid-following inverter and a grid-forming inverter. In each scenario, the state variables associated with the synchronous generator's excitation system were found to be responsible for the inception of instability. These results underscore the importance of accurate modeling of excitation systems when modeling power systems with hybrid power plants.

hybrid power plant↗

Violation of detailed balance in non-equilibrium magnons observed by inelastic neutron scattering

Traditional inelastic neutron scattering (INS) characterizes excitations—such as phonons and magnons—in condensed matter systems at thermodynamic equilibrium. However, the most intriguing and puzzling many-body effects in open quantum systems often emerge from dissipative dynamics that are inherently out of equilibrium. Here, we use a combination of laser pumping and INS to experimentally observe long-lived nonequilibrium magnons in a two-dimensional (2D) square-lattice Heisenberg antiferromagnet. These nonequilibrium magnons manifest themselves as a violation of detailed balance in the dynamic structure factor and reach steady states under periodic driving, analogous to nonequilibrium steady states in driven dissipative systems. Furthermore, we show that the violation of detailed balance reflects the quantum-mechanical nature of the underlying dynamical system, where out-of-time-ordered correlations of creation and annihilation operators do not satisfy commutation relations. The in operando INS technique developed here provides a new approach to studying nonequilibrium magnons in prototypical 2D quantum magnets and can be extended to other systems, including one-dimensional spin chains and topological many-body spin systems, where nonequilibrium effects are widespread and rich in discovery potential.

Hua, Chengyun [Oak Ridge National Laboratory (ORNL↗

On-the-fly active learning of interpretable Bayesian force fields for atomistic rare events

Abstract Machine learned force fields typically require manual construction of training sets consisting of thousands of first principles calculations, which can result in low training efficiency and unpredictable errors when applied to structures not represented in the training set of the model. This severely limits the practical application of these models in systems with dynamics governed by important rare events, such as chemical reactions and diffusion. We present an adaptive Bayesian inference method for automating the training of interpretable, low-dimensional, and multi-element interatomic force fields using structures drawn on the fly from molecular dynamics simulations. Within an active learning framework, the internal uncertainty of a Gaussian process regression model is used to decide whether to accept the model prediction or to perform a first principles calculation to augment the training set of the model. The method is applied to a range of single- and multi-element systems and shown to achieve a favorable balance of accuracy and computational efficiency, while requiring a minimal amount of ab initio training data. We provide a fully open-source implementation of our method, as well as a procedure to map trained models to computationally efficient tabulated force fields.

36 MATERIALS SCIENCE↗

Large-scale molecular dynamics simulations of bubble collapse in water: Effects of system size, water model, and nitrogen

Molecular dynamics simulations in the microcanonical ensemble are performed to study the collapse of a bubble in liquid water using the single-site mW and the four-site TIP4P/2005 water models. To study system size effects, simulations for pure water systems are performed using periodically replicated simulation boxes with linear dimensions, L, ranging from 32 to 512 nm with the largest systems containing 8.7 × 10 6 and 4.5 × 10 9 molecules for the TIP4P/2005 and mW water models, respectively. The computationally more efficient mW water model allows us to reach converging behavior when the bubble dynamics results are plotted in reduced units, and the limiting behavior can be obtained through linear extrapolation in L –1 . Qualitative differences are observed between simulations with the mW and TIP4P/2005 water models, but they can be explained by the models’ differences in predicted viscosity and surface tension. Although bubble collapse occurs on time scales of only hundreds of picoseconds, the system sizes used here are sufficiently large to obtain bubble dynamics consistent with the Rayleigh–Plesset equation when using the models’ thermophysical properties as input. For the conditions explored here, extreme heating of the interfacial water molecules near the time of collapse is observed for the larger mW water systems (but the model underpredicts the viscosity), whereas heating is less pronounced for the TIP4P/2005 water systems because its larger viscosity contribution slows the collapse dynamics. The presence of nitrogen within the bubble only starts to affect bubble dynamics near the very end of the initial collapse, leading to an incomplete collapse and strong rebound for the mW water model. Although nitrogen is non-condensable at 300 K, it becomes highly compressed and reaches a liquid-like density near the collapse point. We find that the dissolution of nitrogen is much slower than the movement of the collapsing water front, and the re-expansion of the dense nitrogen droplet gives rise to bubble rebound. The incompatibility of the collapse and dissolution time scales should be considered for continuum-scale modeling of bubble dynamics. Finally, we also confirm that the diffusion coefficient for dissolved nitrogen is insensitive to pressure as the liquid transitions from a compressed to a stretched state.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

PDB-IHM: A System for Deposition, Curation, Validation, and Dissemination of Integrative Structures

Structures of many large biomolecular assemblies are now being determined using integrative approaches. In these approaches, information derived from multiple experimental and computational methods is combined to compute three-dimensional structures of multi-protein complexes and other macromolecular machines. A standalone prototype data resource for integrative structures called PDB-Dev was built, based on recommendations of the Integrative and Hybrid Methods (IHM) Task Force of the Worldwide Protein Data Bank (wwPDB). This effort included developing data standards and software tools for collecting, curating, validating, visualizing, archiving, and disseminating integrative structures that span diverse spatiotemporal scales and conformational states. Mechanisms have been created to validate integrative structures based on the experimental data underpinning them. Building upon this foundational framework, PDB-Dev has been further expanded to handle large dynamic macromolecular systems and integrative structures that combine, for example, experimental restraints with atomic coordinates computed by machine learning algorithms. Data standards and supporting tools have also been extended to capture information about biomolecular dynamics, such as conformational transitions and related kinetic data derived from biophysical methods. Recently, PDB-Dev was unified with the PDB archive and rebranded as PDB-IHM (pdb-ihm.org), further promoting FAIR (Findable, Accessible, Interoperable, and Reusable) principles of data stewardship for integrative structural biology.

IHMCIF↗

Applying the core-satellite species concept: Characteristics of rare and common riverine dissolved organic matter

Introduction: Dissolved organic matter (DOM) composition varies over space and time, with a multitude of factors driving the presence or absence of each compound found in the complex DOM mixture. Compounds ubiquitously present across a wide range of river systems (hereafter termed core compounds) may differ in chemical composition and reactivity from compounds present in only a few settings (hereafter termed satellite compounds). Here, we investigated the spatial patterns in DOM molecular formulae presence (occupancy) in surface water and sediments across 97 river corridors at a continental scale using the “Worldwide Hydrobiogeochemical Observation Network for Dynamic River Systems—WHONDRS” research consortium. Methods: We used a novel data-driven approach to identify core and satellite compounds and compared their molecular properties identified with Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR MS). Results: In this work, we found that core compounds clustered around intermediate hydrogen/carbon and oxygen/carbon ratios across both sediment and surface water samples, whereas the satellite compounds varied widely in their elemental composition. Within surface water samples, core compounds were dominated by lignin-like formulae, whereas protein-like formulae dominated the core pool in sediment samples. In contrast, satellite molecular formulae were more evenly distributed between compound classes in both sediment and water molecules. Core compounds found in both sediment and water exhibited lower molecular mass, lower oxidation state, and a higher degree of aromaticity, and were inferred to be more persistent than global satellite compounds. Higher putative biochemical transformations were found in core than satellite compounds, suggesting that the core pool was more processed. Discussion: The observed differences in chemical properties of core and satellite compounds point to potential differences in their sources and contribution to DOM processing in river corridors. Overall, our work points to the potential of data-driven approaches separating rare and common compounds to reduce some of the complexity inherent in studying riverine DOM.

54 ENVIRONMENTAL SCIENCES↗

Dynamic Performance Enhancement for Nonlinear Stochastic Systems Using RBF Driven Nonlinear Compensation with Extended Kalman Filter

In this paper, a novel hybrid control method is proposed to enhance the control performance of the PI based control system for a class of nonlinear and non-Gaussian stochastic dynamic processes with unmeasurable states. Firstly, to enhance the tracking performance of the PI controller where the PI parameters are fixed in many actual control systems, the compensative signal is formed using the extended Kalman filter(EKF) based state estimator and driven by the radial basis function (RBF) neural network based compensator. In addition, the weights of RBF is trained to minimize the entropy criterion of tracking error as the process is subjected to non-Gaussian disturbances. Meanwhile, since the precise statistical property of noises is hard to obtain for many industrial processes, the kernel density estimation (KDE) technique is employed in this paper to estimate the entropy. The convergence of RBF network is discussed and the stability of the resulted closed-loop hybrid control system is analyzed in mean square sense. Finally, a numerical example and a practical system testing are given to illustrate the effectiveness of the proposed control method.

stochastic systems, PI Controller, Entropy, Extend↗

Modeling Exhaust-Generated Aerodynamic Pressure Loads on Airfield Matting Repair Systems

Airfield matting systems are commonly used for rapid repair of damaged runways to facilitate continuity of critical operations. Under normal service conditions, matting repair systems are subject not only to wheel loads exerted by airfield traffic but also to aerodynamic pressure loads resulting from high-speed, turbulent exhaust plumes produced by jets during taxi and take-off. Matting systems employed by the U.S. Air Force have been tested with respect to wheel loads, but probabilities of failure because of pressure loads produced by jet exhaust have not yet been established. This study presents a numerical approach for preliminary estimation of worst-case matting anchor forces resulting from exhaust-generated pressure loads. Using a two-dimensional computational fluid dynamics model, system behavior is evaluated by means of a parametric study of six system variables, of which the most significant are: (1) distance between engine and matting, (2) depth of cavity openings at matting edges, and (3) engine exhaust velocity. The results demonstrate that matting systems are likely to experience net uplift in typical service scenarios, driven by the combined effects of flow separation and cavity pressurization. Worst-case anchor pull-out forces, computed according to a tributary-area approach, are estimated to fall in the range of 130 lb (581 N) to 979 lb (4,350 N), depending on assumed load-sharing behavior among anchors and the size of the repair site. Field testing of instrumented matting systems during jet taxi and take-off sequences is recommended as the best next step toward understanding system behavior.

Engineering↗

Charging-driven coarsening and melting of a colloidal nanoparticle monolayer at an ionic liquid–vacuum interface

In this work, we induce and investigate the coarsening and melting dynamics of an initially static nanoparticle colloidal monolayer at an ionic liquid–vacuum interface, driven by a focused, scanning electron beam. Coarsening occurs through grain interface migration and larger-scale motions such as grain rotations, often facilitated by sliding dislocations. The progressive decrease in area fraction that drives melting of the monolayer is explained using an electrowetting model whereby particles at the interface are solvated once their accumulating charge recruits sufficient counterions to subsume the particle. Subject to stochastic particle removal from the monolayer, melting is recapitulated in simulations with a Lennard-Jones potential. This new driving mechanism for colloidal systems, whose dynamical timescales we show can be controlled with the accelerating voltage, opens the possibility to manipulate particle interactions dynamically without need to vary particle intrinsic properties or surface treatments. Furthermore, the decrease in particle size availed by electron imaging presents opportunities to observe force and time scales in a lesser-explored regime intermediate between typical colloidal and molecular systems.

36 MATERIALS SCIENCE↗

Hy-DAT: A Tool to Address Hydropower Modeling Gaps Using Interdependency, Efficiency Curves, and Unit Dispatch Models

As the power system continues to be flooded with intermittent resources, it becomes more important to accurately assess the role of hydro and its impact on the power grid. While hydropower generation has been studied for decades, dependency of power generation on water availability and constraints in hydro operation are not well represented in power system models used in the planning and operation of large-scale interconnection studies. There are still multiple modeling gaps that need to be addressed; if not, they can lead to inaccurate operation and planning reliability studies, and consequently to unintentional load shedding or even blackouts. As a result, it is very important thathydropower is represented correctly in both steady-state and dynamic power system studies. In this paper, we discuss the development and use of the Hydrological Dispatch and Analysis Tool (Hy-DAT) as an interactive graphical user interface (GUI), that uses a novel methodology to address the hydropower modeling gaps like water availability and inter-dependency using a database, and algorithms, to generate accurate representative models for power system simulation.

Wang, Dewei↗

Experimental realization of linearly polarized x-ray detected ferromagnetic resonance

We present the first theoretical and experimental evidence of time-resolved dynamic x-ray magnetic linear dichroism (XMLD) measurements of GHz magnetic precessions driven by ferromagnetic resonance in both metallic and insulating thin films. Our findings show a dynamic XMLD in both ferromagnetic Ni 80 Fe 20 and ferrimagnetic Ni 0.65 Zn 0.35 Al 0.8 Fe 1.2 O 4 for different measurement geometries and linear polarizations. A detailed analysis of the observed signals reveals the importance of separating different harmonic components in the dynamic signal in order to identify the XMLD response without the influence of competing contributions. In particular, RF magnetic resonance elicits a large dynamic XMLD response at the fundamental frequency under experimental geometries with oblique x-ray polarization. The geometric range and experimental sensitivity can be improved by isolating the 2ω Fourier component of the dynamic response. These results illustrate the potential of dynamic XMLD and represent a milestone accomplishment toward the study of GHz spin dynamics in systems beyond ferromagnetic order.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Quantum optimal control for pure-state preparation using one initial state

This paper presents a framework for solving the pure-state preparation problem using numerical optimal control. As an example, we consider the case where a number of qubits are dispersively coupled to a readout cavity. Herein, we model open system quantum dynamics using the Markovian Lindblad master equation driven by external control pulses. The main result of this paper develops a basis of density matrices (a parameterization) where each basis element is a density matrix by itself. Utilizing a specific objective function, we show how an ensemble of the basis elements can be used as a single initial state throughout the optimization process—independent of the system dimension. We apply the general framework to the specific application of ground-state reset of one and two qubits coupled to a readout cavity.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Digital Twin Industry Standards and Opportunities from the Particle Accelerator Community

Digital twins (DTs) are predictive models of a physical system that dynamically update to reflect any changes. This concept was first conceived as early as 1993 by David Gelernter in his speculative non-fiction Mirror Worlds. DTs were coined in 2002 by Michael Grieves and applied to Product Lifecycle Management for manufacturing. Since then, industry has been developing tools to simplify the creation, deployment, and use of digital twins for manufacturing, fleet management, and biological systems. We will recommend industry standard technology and interfaces that we should adopt in the accelerator community. We further identify gaps in this technology to which we can add new capabilities and solutions, which can be expanded for our use cases.

Miceli, Tia [Fermilab] (ORCID:0000000265577789)↗

GEFSv12 High- and Low-Skill Day-10 Tornado Forecasts

Abstract On average, modern numerical weather prediction forecasts for daily tornado frequency exhibit no skill beyond day 10. However, in this extended-range lead window, there are particular model cycles that have exceptionally high forecast skill for tornadoes because of their ability to correctly simulate the future synoptic pattern. Here, model initial conditions that produced a more skillful forecast for tornadoes over the United States were exploited while also highlighting potential causes for low-skill cycles within the Global Ensemble Forecasting System, version 12 (GEFSv12). There were 88 high-skill and 91 low-skill forecasts in which the verifying day-10 synoptic pattern for tornado conditions revealed a western U.S. thermal trough and an eastern U.S. thermal ridge, a favorable configuration for tornadic storm occurrence. Initial conditions for high skill forecasts tended to exhibit warmer sea surface temperatures throughout the tropical Pacific Ocean and Gulf of Mexico, an active Madden–Julian oscillation, and significant modulation of Earth-relative atmospheric angular momentum. Low-skill forecasts were often initialized during La Niña and negative Pacific decadal oscillation conditions. Significant atmospheric blocking over eastern Russia—in which the GEFSv12 overforecast the duration and characteristics of the downstream flow—was a common physical process associated with low-skill forecasts. This work helps to increase our understanding of the common causes of high- or low-skill extended-range tornado forecasts and could serve as a helpful tool for operational forecasters. Significance Statement This research provides a framework for the anticipation of a more (or less) skillful 10-day tornado forecast in an operational numerical weather prediction system. High-skill forecasts were associated with substantial tropical convection and warm sea surface temperature throughout the Pacific Ocean and Gulf of Mexico, whereas the underlying cause of low-skill forecasts were typically associated with a blocking anticyclone over eastern Russia. These findings are important because they permit increased or decreased confidence in a long-range forecast of tornado occurrence based on a dynamical prediction system.

Meteorology & Atmospheric Sciences↗

“Frequency” and the PMU standard

The Phasor Measurement Unit (PMU) has revolutionized power system management by providing high-resolution, time-stamped, spatial, and temporal measure¬ments of the state of power systems. However, the standards defining the measured quantities have ambiguities that cause uncertainty, irreproducibility, and loss of interoperability during periods of change where the measurements should have the greatest value. This paper examines PMU frequency measurement to highlight the problems. It develops some suggestions for the scope and the next evolutionary improvements to the documentary standards. The aim is to improve the meaningfulness and trustworthiness of dynamic power system measurements.

Frequency, rate of change of frequency, definition↗

Shared automated vehicle fleet operations for first-mile last-mile transit connections with dynamic pooling

Shared automated vehicles (SAVs) have the potential to promote transit ridership by providing efficient first-mile last-mile (FMLM) connections through reduced operational costs to fleet providers and lower out-of-pocket costs to riders. To help plan for a future of integrated mobility, this paper investigates the impacts of SAVs serving FMLM connections, as a mode that provides flexibility in access/egress decisions and is well coordinated with train station schedules. To achieve this objective, a novel dynamic pooling algorithm was introduced to match SAVs with riders while coordinating the riders' arrival times at the light-rail station to a known train schedule. Microsimulations of SAVs and travelers throughout two central Austin neighborhoods show how larger service areas, higher levels of SAV demand, and longer arrival times between successive trains require larger SAV fleet sizes and higher SAV utilization rates to deliver close traveler wait times. Four-person SAVs appear to perform similar to 6-seat SAVs but will cost less to provide. Using a dynamic pooling algorithm tightly coordinated with train arrivals (every 15 min) delivers 87% of travelers to their stations in time to catch the next train, whereas uncoordinated assignments deliver just 58% of travelers in time.

33 ADVANCED PROPULSION SYSTEMS↗

Catalytic Resonance Theory: The Catalytic Mechanics of Programmable Ratchets

Catalytic reaction networks of multiple elementary steps operating under dynamic conditions via a programmed input oscillation are difficult to interpret and optimize due to reaction system complexity. To understand these dynamic systems, individual elementary catalytic reactions oscillating between catalyst states were evaluated to identify their three fundamental characteristics that define their ability to promote reactions away from equilibrium. First, elementary catalytic reactions exhibit directionality to promote reactions forward or backward from equilibrium as determined by a ratchet directionality metric comprised of the input oscillation duty cycle and the reaction rate constants. Second, catalytic ratchets are defined by the catalyst state of strong or weak binding that permit reactants to proceed through the transition state. Third, elementary catalytic ratchets exhibit a cutoff frequency which defines the transition in applied frequency for which the catalytic ratchet functions to promote chemistry away from equilibrium. All three ratchet characteristics are calculated from chemical reaction parameters including rate constants derived from linear scaling parameters, reaction conditions, and catalyst state. The characteristics of the reaction network’s constituent elementary catalytic reactions provided an interpretation of complex reaction networks and a method of predicting the behavior of dynamic surface chemistry on oscillating catalysts.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗