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At least 631 records · Page 35

Integrable symplectic maps with a polygon tessellation

Identifying integrable dynamics remains a formidable challenge, and despite centuries of research, only a handful of examples are known to date. In this article, we explore a distinct form of area-preserving (symplectic) mappings derived from the stroboscopic Poincaré cross section of a kicked rotator—an oscillator subjected to an external force periodically switched on in short pulses. The significance of this class of problems extends to various applications in physics and mathematics, including particle accelerators, crystallography, and studies of chaos. Notably, Suris's theorem constrains the integrability within this category of mappings, outlining potential scenarios with analytic invariants of motion. In this paper, we challenge the assumption of the analyticity of the invariant by exploring piecewise linear transformations on a torus ( T 2 ) and associated systems on the plane ( R 2 ), incorporating arithmetic quasiperiodicity and discontinuities. Introducing a new automated technique, we discovered previously unknown scenarios featuring polygonal invariants that form perfect tessellations and, moreover, fibrations of the plane or torus. This work reveals a novel category of planar tilings characterized by discrete symmetries that emerge from the invertibility of transformations and are intrinsically linked to the presence of integrability. Our algorithm relies on the analysis of the Poincaré rotation number and its piecewise monotonic nature for integrable cases, contrasting with the noisy behavior in the case of chaos, thereby allowing for clear separation. Some of the newly discovered systems exhibit the peculiar behavior of “integrable diffusion,” characterized by infinite and quasirandom hopping between tiles while being confined to a set of invariant segments. Finally, through the implementation of a smoothening procedure, all mappings can be generalized to quasi-integrable scenarios with suppressed volume occupied by chaotic trajectories, thereby opening doors to potential practical applications. Published by the American Physical Society 2024

43 PARTICLE ACCELERATORS↗

Systems and methods for approximating musculoskeletal dynamics

An approximation method and system are provided for more quickly controlling a prosthetic or other device by reducing computational processing time in a muscle model that can be used to control the prosthetic. For a given muscle, the approximation method can quickly compute polynomial structures for a muscle length and for each associated moment arms, which may be used to generate a torque for a joint position of a physics model. The physics model, in turn, produces a next joint position and velocity data for driving a prosthetic. The approximation method expands the polynomial structures as long as expansion is possible and sufficiently beneficial. The computations can be performed quickly by expanding the polynomial structures in a way that constrains the muscle length polynomial to the moment arm polynomial structures, and vice versa.

Sobinov, Anton↗

Using system identification in modeling the yaw response of tail fins for small wind turbines with bearing friction

Here, we describe three main developments of our previous study of the nonlinear yaw dynamics of the tail fins for small wind turbines [Khedr et al., J. Renewable Sustainable Energy 16, 053305 (2024)]. First, the model constants derived from archived computational and experimental studies are adjusted by employing system identification (SI) to maximize the model's agreement with wind tunnel tests. This adjustment was done for high wind speeds, where yaw bearing friction can be ignored. When starting a turbine at low wind speed, however, friction can become important. Our second development is to implement a model for the frictional resistive torque and use SI to maximize its accuracy. These developments used wind tunnel experiments on generic delta, elliptical, and rectangular planforms that were described by Khedr et al. [J. Renewable Sustainable Energy 16, 053305 (2024)]. Since the aerodynamic and friction models employ a large number of constants, we describe ways to constrain the values using linearized solutions of the response equations for small and large yaw angles. Third, we test the generality of the aerodynamic and friction modeling using the complex planform from a commercial small turbine, for which limited theoretical and computational guidance is available in selecting the model constants. The model implemented with SI is shown to provide an accurate description of the yaw response of the complex planform. Guidelines are given for the use of wind tunnel tests to determine the model constants for tail fins of any planform.

17 WIND ENERGY↗

Arctic Deployment of a Fully Integrated Self-Powered Drifting Buoy Harvesting Wave Energy via a Triboelectric Nanogenerator

The Arctic Ocean remains one of the most poorly sampled regions on Earth, where improved in situ environmental monitoring is vital for advancing oceanographic and atmospheric studies. However, data collection efforts are constrained by the short operational lifespans and high costs of conventional systems. Drifting buoys powered by pendulum-driven wave energy harvesters offer a cost-effective alternative, yet earlier designs have neither been optimized for real-world wave conditions nor validated in the Arctic. In this study, we develop a self-powered drifting buoy that integrates a pendulum-driven triboelectric nanogenerator (TENG) system with a mechanical motion rectifier, a high-gear-ratio transmission, and power management circuits. Through coupled buoy–pendulum dynamic simulations and laboratory testing using a motion simulator, we identify an optimal pendulum mass of 1.6 kg (12.7% of total buoy weight) that maximizes energy output while maintaining buoy stability. Laboratory experiments achieved average power outputs of 12.7 mW under Arctic-like wave and temperature conditions. The system was successfully deployed in the Bering Sea, where it generated 11 J of energy in 3.1 m waves, marking the first Arctic deployment of a TENG-based drifting buoy for sea surface temperature monitoring. This work establishes a cost-effective framework for designing self-powered Arctic monitoring platforms and advances the feasibility of long-term environmental observations in real Arctic waters.

marine enerby↗

Viscosity in water from first-principles and deep-neural-network simulations

Abstract We report on an extensive study of the viscosity of liquid water at near-ambient conditions, performed within the Green-Kubo theory of linear response and equilibrium ab initio molecular dynamics (AIMD), based on density-functional theory (DFT). In order to cope with the long simulation times necessary to achieve an acceptable statistical accuracy, our ab initio approach is enhanced with deep-neural-network potentials (NNP). This approach is first validated against AIMD results, obtained by using the Perdew–Burke–Ernzerhof (PBE) exchange-correlation functional and paying careful attention to crucial, yet often overlooked, aspects of the statistical data analysis. Then, we train a second NNP to a dataset generated from the Strongly Constrained and Appropriately Normed (SCAN) functional. Once the error resulting from the imperfect prediction of the melting line is offset by referring the simulated temperature to the theoretical melting one, our SCAN predictions of the shear viscosity of water are in very good agreement with experiments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Thermal acclimation of plant photosynthesis and autotrophic respiration in a northern peatland

Peatlands contain one-third of global soil carbon (C), but the responses of peatland ecosystems to long-term warming are not well understood. Here, we pursue an emergent understanding of warming effects on ecosystem C fluxes at peatlands by constraining a process-oriented model, the terrestrial ECOsystem model, with observational data from a long-term warming experiment at the Spruce and Peatland Responses Under Changing Environments site. Model-based assessments show that ecosystem-level photosynthesis and autotrophic respiration exhibited significant thermal acclimation, with temperature sensitivities being linearly decreased with warming. Using the thermal-acclimated parameter values, simulated gross primary production, net primary production, and plant autotrophic respiration (R a ), were all lower than those simulated with non-thermal acclimated parameter values. In contrast, ecosystem respiration simulated with thermal acclimated parameter values was higher than that simulated with non-thermal acclimated parameter values. Net ecosystem CO 2 exchange was much higher after constraining model parameters with observational data from the warming treatments, releasing C at a rate of 28.3 g C m -2 yr -1 °C -1 . Our data-model integration study suggests that peatlands are likely to release more C than previously estimated. Earth system models may overestimate C uptake by peatlands under warming if physiological thermal acclimation of plants is not incorporated. Thus, it is critical to consider the long-term physiological thermal acclimation of plants in the models to better predict global C dynamics under future climate and their feedback to climate change.

54 ENVIRONMENTAL SCIENCES↗

Global constraint on the jet transport coefficient from single-hadron, dihadron, and γ -hadron spectra in high-energy heavy-ion collisions

Modifications of large transverse momentum single-hadron, dihadron, and γ -hadron spectra in relativistic heavy-ion collisions are direct consequences of parton-medium interactions in the quark-gluon plasma (QGP). The interaction strength and underlying dynamics can be quantified by the jet transport coefficient q ̂ . We carry out the first global constraint on q ̂ using a next-to-leading order pQCD parton model with higher-twist parton energy loss and combining world experimental data on single-hadron, dihadron, and γ -hadron suppression at both RHIC and LHC energies with a wide range of centralities. The global Bayesian analysis using the information field (IF) priors provides the most stringent constraint on q ̂ ( T ) . We demonstrate in particular the progressive constraining power of the IF Bayesian analysis on the strong temperature dependence of q ̂ using data from different centralities and colliding energies. We also discuss the advantage of using both inclusive and correlation observables with different geometric biases. As a verification, the obtained q ̂ ( T ) is shown to describe data on single-hadron anisotropy at high transverse momentum well. Predictions for future jet quenching measurements in oxygen-oxygen collisions are also provided. Published by the American Physical Society 2024

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Budget-Constrained Sizing of Renewable and Energy Storage Systems for Farm-Scale Ammonia Production Within the Food-Energy-Water Nexus

In the transition toward sustainable agriculture, farms have emerged as eco-friendly pioneers, harnessing clean hybrid wind and solar systems to improve farm performance. A concern in this paradigm is the effective sizing of renewable energy systems to ensure optimal energy use within budget considerations. This research focuses on optimizing renewable energy sizing in small-scale ammonia production to meet specific farm demands and enhance local resilience, emphasizing the interplay between environmental and economic factors. These findings promise increased energy efficiency and sustainability in this innovative agricultural sector. Additionally, our approach considers small-scale ammonia plant needs and the dynamic relationships between ammonia, water, and farm demands. Simulations demonstrate substantial cost savings in farm electricity consumption. Specifically, scenarios with renewable energy integration in the farm can reduce at least 13% electricity cost compared to a grid-dependent system in the 15-year simulation.

ammonia↗

Frequency Nadir Constrained Unit Commitment for High Renewable Penetration Island Power Systems

The process of energy decarbonization in island power systems is accelerated due to the swift integration of inverter-based renewable energy resources (IBRs). The unique features of such systems, including rapid frequency changes resulting from potential generation outages or imbalances due to the unpredictability of renewable power, pose a significant challenge in maintaining the frequency nadir without external support. This paper presents a unit commitment (UC) model with data-driven frequency nadir constraints, including either frequency nadir or minimum inertia requirements, helping to limit frequency deviations after significant generator outages. The constraints are formulated using a linear regression model that takes advantage of real-world, year-long generation scheduling and dynamic simulation data. The efficacy of the proposed UC model is verified through a year-long simulation in an actual island power system using historical weather data. The alternative minimum inertia constraint, derived from actual system operation assumptions, is also evaluated. Findings demonstrate that the proposed frequency nadir constraint notably improves the system's frequency nadir under high photovoltaic (PV) penetration levels, albeit with a slight increase in generation costs, when compared to the alternative minimum inertia constraint.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Unexpected electrochemical behavior of an anolyte redoxmer in flow battery electrolytes: solvating cations help to fight against the thermodynamic–kinetic dilemma

Redoxmers are redox-active molecules that can store energy in electrolytes for redox flow batteries (RFBs), and their electrochemical properties are significantly affected by the choice of supporting electrolytes. Herein, we use 2,1,3-benzothiadiazole (BzNSN) as a model system to scrutinize the supporting electrolyte impact. By systemically varying the components of supporting salts, BzNSN not only shows substantial redox potential shifts but also exhibits varying electrochemical stabilities. Specifically, changing the size of cations can effectively alter the coordination between the supporting salt and BzNSN species. From Li + , Na + , K + , to NEt 4 + , the redox potential of BzNSN shifts negatively, from -1.63 V to -1.82 V vs. Ag/Ag + . Molecular dynamics and density functional theory simulations revealed that smaller cations, like Li + , are closer to the charged BzNSN when coordinated, implying stronger coordination, while larger cations, like K + and NEt 4 + , are farther away. Interestingly, the large cation electrolytes also lead to much improved electrochemical stability, evidenced by the extraordinarily enhanced kinetic lifetime from electron paramagnetic resonance measurement. This study demonstrates the first example of tuning an anolyte redoxmer toward a concurrent improvement of lowered redox potentials AND enhanced calendar lives via solvation means, which is usually constrained by the thermodynamic–kinetic relation.

2,1,3-benzothiadiazole↗

Planetary Boundary-Layer Height (PBLHT) Value-Added Product: Remote-Sensing Retrievals

The planetary boundary layer (PBL) is fundamental to numerous atmospheric processes, including aerosol mixing and transport, cloud evolution, and precipitation formation. A critical parameter in these studies is the PBL height (PBLHT). This vertical depth is essential for characterizing PBL structures in numerical simulations and serves as a primary metric for estimating flux exchanges between the Earth’s surface and the atmosphere. Radiosonde (SONDE) observations provide high-vertical-resolution measurements of temperature and moisture profiles and are widely used to estimate PBLHT (Liu and Liang 2010, Seidel et al. 2010). The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) User Facility’s PBLHT value-added product (VAP) for radiosonde measurements, known as PBLHTSONDE, applies three commonly used methods—the Heffter (1980) method, the Liu and Liang (2010) method, and the bulk Richardson number approach (Seibert et al. 2000)—to derive PBLHT. The PBLHTSONDE VAP operates routinely at ARM observatories and mobile facilities, with data available from the ARM Data Center shortly after sounding observations are collected (Sivaraman et al. 2013). However, radiosonde observations are limited by their low temporal resolution. Most stations launch soundings only twice daily, which constrains the ability to investigate and characterize the temporal evolution of the PBL using radiosonde data alone. The use of continuous remote-sensing observations provides high temporal resolution of PBLHT estimates. These observations include aerosol lidars (Dang et al. 2019, Su et al. 2020), Doppler lidar (DL; Tucker et al. 2009, Krishnamurthy et al. 2021), and water vapor and/or temperature lidars and radiometers (Turner et al. 2014). These observations provide valuable data on the PBL’s thermodynamic properties (e.g., water vapor and/or temperature lidars and radiometers), dynamic properties (e.g., DL), and distribution of tracer substances (e.g., aerosol lidars), all of which can be used to estimate PBLHT. ARM developed PBLHT estimates from the micropulse lidar (MPL; PBLHTMPL), Doppler lidar (PBLHTDL), and combined Raman lidar (RL)/atmospheric emitted radiance interferometer (AERI) thermodynamic profiles (PBLHTTHERMO). Each estimate captures different physical characteristics of the boundary layer—aerosol tracers, vertical velocity turbulence, and thermodynamic structure—and exhibits distinct strengths and limitations depending on the PBL regime and time of day. In addition, the ARM ceilometer (CEIL) provides three potential PBLHT candidates derived from the vendor's built-in algorithm. Building on these individual retrievals, ARM developed the PBLHTBEML VAP, which combines the four remote-sensing-based estimates with ancillary meteorological variables using the machine learning approach of Zhang et al. (2025) to produce a best-estimate PBLHT at 10-minute resolution.

54 ENVIRONMENTAL SCIENCES↗

Dynamically Learning Incentives for Load Control

As electrical generation becomes more distributed and volatile, and loads become more uncertain, controllability of distributed energy resources (DERs), regardless of their ownership status, will be necessary for grid reliability. Grid operators lack direct control over end-users' grid interactions, such as energy usage, but incentives can influence behavior -- for example, an end-user that receives a grid-driven incentive may adjust their consumption or expose relevant control variables in response. A key challenge in studying such incentives is the lack of data about human behavior, which usually motivates strong assumptions, such as distributional assumptions on compliance or rational utility-maximization. In this paper, we propose a general incentive mechanism in the form of a constrained optimization problem -- our approach is distinguished from prior work by modeling human behavior (e.g., reactions to an incentive) as an arbitrary unknown function. We propose feedback-based optimization algorithms to solve this problem that each leverage different amounts of information and/or measurements. We show that each converges to an asymptotically stable incentive with (near)-optimality guarantees given mild assumptions on the problem. Finally, we evaluate our proposed techniques in voltage regulation simulations on standard test beds. We test a variety of settings, including those that break assumptions required for theoretical convergence (e.g., convexity, smoothness) to capture realistic settings. In this evaluation, our proposed algorithms are able to find near-optimal incentives even when the reaction to an incentive is modeled by a theoretically difficult (yet realistic) function.

demand response↗

Low cost and massively parallel force spectroscopy with fluid loading on a chip

Current approaches for single molecule force spectroscopy are typically constrained by low throughput and high instrumentation cost. Herein, a low-cost, high throughput technique is demonstrated using microfluidics for multiplexed mechanical manipulation of up to ~4000 individual molecules via molecular fluid loading on-a-chip (FLO-Chip). The FLO-Chip consists of serially connected microchannels with varying width, allowing for simultaneous testing at multiple loading rates. Molecular force measurements are demonstrated by dissociating Biotin-Streptavidin and Digoxigenin-AntiDigoxigenin interactions along with unzipping of double stranded DNA of varying sequence under different dynamic loading rates and solution conditions. Rupture force results under varying loading rates and solution conditions are in good agreement with prior studies, verifying a versatile approach for single molecule biophysics and molecular mechanobiology. FLO-Chip enables straightforward, rapid, low-cost, and portable mechanical testing of single molecules that can be implemented on a wide range of microscopes to broaden access and may enable new applications of molecular force spectroscopy.

42 ENGINEERING↗

Using irradiation-induced defects as pinning sites to minimize self-alignment in twisted bilayer graphene

Preparing bi-layer graphene under a magic twisting angle of ~1.1° has been challenging due to its strong tendency for self-alignment. We propose a method to pin graphene layers and minimize their self-rotation when positioned close to each other. The feasibility is demonstrated by the present study using molecular dynamics simulations. C 60 clusters are used to bombard two individual graphene layers, creating damage on both layers. When two irradiated layers are moving closer to each other, defects from irradiation damaged zones can interact with each other, hence acting as pinning sites to immobilize graphene and minimize rotation or gliding. Dangling bonds from defective regions of each plane induce the formation of sp bonds. Upon sliding, the bond is strong enough to induce the formation of one-dimensional carbon single chain, acting as a thread to constrain the relative movements.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Dark matter density profiles in dwarf galaxies: linking Jeans modelling systematics and observation

ABSTRACT The distribution of dark matter in dwarf galaxies can have important implications on our understanding of galaxy formation as well as the particle physics properties of dark matter. However, accurately characterizing the dark matter content of dwarf galaxies is challenging due to limited data and complex dynamics that are difficult to accurately model. In this paper, we apply spherical Jeans modelling to simulated stellar kinematic data of spherical, isotropic dwarf galaxies with the goal of identifying the future observational directions that can improve the accuracy of the inferred dark matter distributions in the Milky Way dwarf galaxies. We explore how the dark matter inference is affected by the location and number of observed stars as well as the line-of-sight velocity measurement errors. We use mock observation to demonstrate the difficulty in constraining the inner core/cusp of the dark matter distribution with data sets of fewer than 10 000 stars. We also demonstrate the need for additional measurements to make robust estimates of the expected dark matter annihilation signal strength. For the purpose of deriving robust indirect detection constraints, we identify Ursa Major II, Ursa Minor, and Draco as the systems that would most benefit from additional stars being observed.

79 ASTRONOMY AND ASTROPHYSICS↗

Ergodicity breaking in rapidly rotating C 60 fullerenes

Ergodicity, the central tenet of statistical mechanics, requires an isolated system to explore all available phase space constrained by energy and symmetry. Mechanisms for violating ergodicity are of interest for probing nonequilibrium matter and protecting quantum coherence in complex systems. Polyatomic molecules have long served as a platform for probing ergodicity breaking in vibrational energy transport. Here, we report the observation of rotational ergodicity breaking in an unprecedentedly large molecule, 12 C 60 , determined from its icosahedral rovibrational fine structure. The ergodicity breaking occurs well below the vibrational ergodicity threshold and exhibits multiple transitions between ergodic and nonergodic regimes with increasing angular momentum. These peculiar dynamics result from the molecule’s distinctive combination of symmetry, size, and rigidity, highlighting its relevance to emergent phenomena in mesoscopic quantum systems.

Science & Technology - Other Topics↗

Physical, resource supply, and biological controls on nutrient processing along the river continuum

Nutrient impairment has led to damages to US surface and groundwater systems in excess of 100 billion dollars per year. Therefore, there is a strong need to develop methods to predict the transport, uptake, and export of nutrients along fluvial networks. We present results that are based on a data-driven mechanistic understanding of three factors that largely control nutrient uptake and export: 1) interactions between transport-related processes (mass transfer to metabolically active zones), 2) resource supply dynamics (nutrient concentration, stoichiometric constraints, etc.), and 3) biological controls (microbial community structure and function). Our results were generated from column experiments conducted along the Jemez River-Rio Grande continuum, which spans four orders of magnitude in mean annual discharge, more than 2000 m in altitude, and more than 500 km of stream longitude. Two resource supply injections were performed on each of the columns, i.e., a nitrate only addition, followed by a stoichiometrically ‘balanced’ 106Carbon:16Nitrogen:1Phosphorus addition. We quantified NO3-N uptake kinetics while constraining three variables: stream order, sediment type and type of injection (N vs stoichiometrically ‘balanced’ C:N:P). Following the laboratory nutrient uptake experiments, the columns were destructively sampled and the contents were homogenized to collect subsamples for DNA sequencing. Amplicon analysis was carried out as described by the Earth Microbiome Protocol for 16s and ITS sequencing.

54 ENVIRONMENTAL SCIENCES↗

The collapse of the Cordilleran–Laurentide ice saddle and early opening of the Mackenzie Valley, Northwest Territories, Canada, constrained by 10 Be exposure dating

Deglaciation of the northwestern Laurentide Ice Sheet in the central Mackenzie Valley opened the northern portion of the deglacial Ice-Free Corridor between the Laurentide and Cordilleran ice sheets and a drainage route to the Arctic Ocean. In addition, ice sheet saddle collapse in this section of the Laurentide Ice Sheet has been implicated as a mechanism for delivering substantial freshwater influx into the Arctic Ocean on centennial timescales. However, there is little empirical data to constrain the deglaciation chronology in the central Mackenzie Valley where the northern slopes of the ice saddle were located. Here, we present 30 new 10Be cosmogenic nuclide exposure dates across six sites, including two elevation transects, which constrain the timing and rate of thinning and retreat of the Laurentide Ice Sheet in the area. Our new 10Be dates indicate that the initial deglaciation of the eastern summits of the central Mackenzie Mountains began at ~15.8 ka (17.1–14.6 ka), ~1000 years earlier than in previous reconstructions. The main phase of ice saddle collapse occurred between ~14.9 and 13.6 ka, consistent with numerical modelling simulations, placing this event within the Bølling–Allerød interval (14.6–12.9 ka). Our new dates require a revision of ice margin retreat dynamics, with ice retreating more easterly rather than southward along the Mackenzie Valley. In addition, we quantify a total sea level rise contribution from the Cordilleran–Laurentide ice saddle region of ~11.2 m between 16 and 13 ka.

58 GEOSCIENCES↗