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Real-time radiative divertor feedback control development for the NSTX-U tokamak using a vacuum ultraviolet spectrometer
A radiative divertor technique is planned for the NSTX-U tokamak to prevent excessive erosion and thermal damage of divertor plasma-facing components in H-mode plasma discharges with auxiliary heating up to 12 MW. In the radiative (partially detached) divertor, extrinsically seeded deuterium or impurity gases are used to increase plasma volumetric power and momentum losses. A real-time feedback control of the gas seeding rate is planned for discharges of up to 5 s duration. The outer divertor leg plasma electron temperature T{sub e} estimated spectroscopically in real time will be used as a control parameter. A vacuum ultraviolet spectrometer McPherson Model 251 with a fast charged-coupled device detector is developed for temperature monitoring between 5 and 30 eV, based on the Δn = 0, 1 line intensity ratios of carbon, nitrogen, or neon ion lines in the spectral range 300–1600 Å. A collisional-radiative model-based line intensity ratio will be used for relative calibration. A real-time T{sub e}-dependent signal within a characteristic divertor detachment equilibration time of ∼10–15 ms is expected.
Local radiative feedbacks over the Arctic based on observed short-term climate variations
We compare various radiative feedbacks in response to short-term climate variations estimated from reanalysis, satellite, and global climate model datasets using the combined Kernel-Gregory approach over the Arctic (60-90°N). Except for the shortwave cloud feedback, all feedbacks are positive over the Arctic. Lapse rate feedback is comparable with surface albedo feedback. Relative to the tropics (30°S-30°N), the temperature feedback (lapse rate feedback plus Planck feedback deviation from its global mean) is the largest contributor to Arctic amplification among all feedbacks, followed by surface albedo feedback. The choice of meteorological fields has a small impact on the cloud feedback estimate, but different top-of-the-atmosphere clear-sky fluxes datasets can result in a wide spread of estimated cloud feedbacks. The net cloud feedback over the Arctic is positive due to a larger positive in longwave than the negative shortwave feedback, but has the largest uncertainty. Relative to the tropics, the longwave cloud feedback largely contributes to the Arctic amplification.
Characteristics of human-climate feedbacks differ at different radiative forcing levels
The human and Earth systems are intricately linked: climate influences agricultural production, renewable energy potential, and water availability, for example, while anthropogenic emissions from industry and land use change alter temperature and precipitation. Such feedbacks have the potential to significantly alter future climate change. These feedbacks may also exert significant changes on 21st-century energy, agriculture, land use and carbon cycle projections, but little is known about their possible magnitudes, or about regional and sector dynamics under different forcing scenarios. Here we use an integrated Earth System Model (ESM) featuring bidirectional information exchange between an economically-oriented integrated assessment model and the ESM to examine how human-natural feedbacks operate under high and medium radiative forcing (RF) scenarios. Specifically, we examine the effect of changing land productivity on human systems, and the effect of changing land use/land cover and CO2 emissions on the Earth system. We find that the effect of coupling differs across radiative forcing levels and across regions, due to differences in the climate signal, human responses to those signals, and regional characteristics. In particular, we find reductions in cropland area due to feedbacks in both the medium and high RF scenarios. In the medium RF scenario, these reductions result in increased area for bioenergy and afforestation and reduced energy system CO2 emissions, as the carbon price in this scenario incentivizes low carbon energy sources and terrestrial carbon storage; these incentives are absent in the high RF scenario. These differences are key to understanding the possible future evolution pathways of the integrated Earth system in response to 21st century climate change. Additional models and hypothesis testing are needed to determine exactly when and how bidirectional feedbacks between human and Earth systems should be considered in future assessments.
Economic carbon cycle feedbacks may offset additional warming from natural feedbacks
As the Earth warms, carbon sinks on land and in the ocean will weaken, thereby increasing the rate of warming. Although natural mechanisms contributing to this positive climate–carbon feedback have been evaluated using Earth system models, analogous feedbacks involving human activities have not been systematically quantified. Here we conceptualize and estimate the magnitude of several economic mechanisms that generate a carbon–climate feedback, using the Kaya identity to separate a net economic feedback into components associated with population, GDP, heating and cooling, and the carbon intensity of energy production and transportation. We find that climate-driven decreases in economic activity (GDP) may in turn decrease human energy use and thus fossil fuel CO 2 emissions. In a high radiative forcing scenario, such decreases in economic activity reduce fossil fuel emissions by 13% this century, lowering atmospheric CO 2 by over 100 ppm in 2100. The natural carbon–climate feedback, in contrast, increases atmospheric CO 2 over this period by a similar amount, and thus, the net effect including both feedbacks is nearly zero. Our work highlights the importance of improving the representation of climate–economic feedbacks in scenarios of future change. Although the effects of climate warming on the economy may offset weakening land and ocean carbon sinks, a loss of economic productivity will have high societal costs, potentially increasing wealth inequity and limiting resources available for effective adaptation.
Low-Cloud Feedback in CAM5-CLUBB: Physical Mechanisms and Parameter Sensitivity Analysis
Not Available
The Importance of Preventive Feedback: Inference from Observations of the Stellar Masses and Metallicities of Milky Way Dwarf Galaxies
Dwarf galaxies are known to have remarkably low star formation efficiency due to strong feedback. Adopting the dwarf galaxies of the Milky Way (MW) as a laboratory, we explore a flexible semi-analytic galaxy formation model to understand how the feedback processes shape the satellite galaxies of the MW. Using Markov Chain Monte Carlo, we exhaustively search a large parameter space of the model and rigorously show that the general wisdom of strong outflows as the primary feedback mechanism cannot simultaneously explain the stellar mass function and the mass–metallicity relation of the MW satellites. An extended model that assumes that a fraction of baryons is prevented from collapsing into low-mass halos in the first place can be accurately constrained to simultaneously reproduce those observations. The inference suggests that two different physical mechanisms are needed to explain the two different data sets. In particular, moderate outflows with weak halo mass dependence are needed to explain the mass–metallicity relation, and prevention of baryons falling into shallow gravitational potentials of low-mass halos (e.g., “pre-heating”) is needed to explain the low stellar mass fraction for a given subhalo mass.
Supervisory System for a Wide Area Damping Controller Using PDCI Modulation and Real-Time PMU Feedback.
Abstract not provided.
Weaker land–climate feedbacks from nutrient uptake during photosynthesis-inactive periods
Terrestrial carbon–climate feedbacks depend on two large and opposing fluxes—soil organic matter decomposition and photosynthesis—that are tightly regulated by nutrients. Earth system models (ESMs) participating in the Coupled Model Intercomparison Project Phase 5 represented nutrient dynamics poorly, rendering predictions of twenty-first century carbon–climate feedbacks highly uncertain. Here, we use a new land model to quantify the effects of observed plant nutrient uptake mechanisms missing in most other ESMs. In particular, we estimate the global role of root nutrient competition with microbes and abiotic processes during periods without photosynthesis. Nitrogen and phosphorus uptake during these periods account for 45 and 43%, respectively, of annual uptake, with large latitudinal variation. Globally, night-time nutrient uptake dominates this signal. Simulations show that ignoring this plant uptake, as is done when applying an instantaneous relative demand approach, leads to large positive biases in annual nitrogen leaching (96%) and N 2 O emissions (44%). Furthermore, this N 2 O emission bias has a GWP equivalent of ~2.4 PgCO 2 yr –1 , which is substantial compared to the current terrestrial CO 2 sink. Such large biases will lead to predictions of overly open terrestrial nutrient cycles and lower carbon sequestration capacity. Both factors imply over-prediction of positive terrestrial feedbacks with climate in current ESMs.
Cross-correlation of Dark Energy Survey Year 3 lensing data with ACT and Planck thermal Sunyaev-Zel’dovich effect observations. I. Measurements, systematics tests, and feedback model constraints
Here we present a tomographic measurement of the cross-correlation between thermal Sunyaev-Zel’dovich (TSZ) maps from Planck and the Atacama Cosmology Telescope and weak galaxy lensing shears measured during the first three years of observations of the Dark Energy Survey. This correlation is sensitive to the thermal energy in baryons over a wide redshift range and is therefore a powerful probe of astrophysical feedback. We detect the correlation at a statistical significance of 21σ, the highest significance to date. We examine the TSZ maps for potential contaminants, including cosmic infrared background and radio sources, finding that cosmic infrared background has a substantial impact on our measurements and must be taken into account in our analysis. We use the cross-correlation measurements to test different feedback models. In particular, we model the TSZ using several different pressure profile models calibrated against hydrodynamical simulations. Our analysis marginalizes over redshift uncertainties, shear calibration biases, and intrinsic alignment effects. We also marginalize over Ω m and σ 8 using Planck or DES priors. We find that the data prefer the model with a low amplitude of the pressure profile at small scales, compatible with a scenario with strong active galactic nuclei feedback and ejection of gas from the inner part of the halos. When using a more flexible model for the shear profile, constraints are weaker, and the data cannot discriminate between different baryonic prescriptions.
PROTOSTELLAR OUTFLOWS AND RADIATIVE FEEDBACK FROM MASSIVE STARS. II. FEEDBACK, STAR-FORMATION EFFICIENCY, AND OUTFLOW BROADENING
We perform two-dimensional axially symmetric radiation hydrodynamic simulations to assess the impact of outflows and radiative force feedback from massive protostars by varying when the protostellar outflow starts, and to determine the ratio of ejection to accretion rates and the strength of the wide-angle disk wind component. The star-formation efficiency, i.e., the ratio of final stellar mass to initial core mass, is dominated by radiative forces and the ratio of outflow to accretion rates. Increasing this ratio has three effects. First, the protostar grows slower with a lower luminosity at any given time, lowering radiative feedback. Second, bipolar cavities cleared by the outflow become larger, further diminishing radiative feedback on disk and core scales. Third, the higher momentum outflow sweeps up more material from the collapsing envelope, decreasing the protostar's potential mass reservoir via entrainment. The star-formation efficiency varies with the ratio of ejection to accretion rates from 50% in the case of very weak outflows to as low as 20% for very strong outflows. At latitudes between the low-density bipolar cavity and the high-density accretion disk, wide-angle disk winds remove some of the gas, which otherwise would be part of the accretion flow onto the disk; varying the strength of these wide-angle disk winds, however, alters the final star-formation efficiency by only ±6%. For all cases, the opening angle of the bipolar outflow cavity remains below 20° during early protostellar accretion phases, increasing rapidly up to 65° at the onset of radiation pressure feedback.
High Angular Momentum Halo Gas: A Feedback and Code-independent Prediction of LCDM
We investigate angular momentum acquisition in Milky Way-sized galaxies by comparing five high resolution zoom-in simulations, each implementing identical cosmological initial conditions but utilizing different hydrodynamic codes: Enzo, Art, Ramses, Arepo, and Gizmo-PSPH. Each code implements a distinct set of feedback and star formation prescriptions. We find that while many galaxy and halo properties vary between the different codes (and feedback prescriptions), there is qualitative agreement on the process of angular momentum acquisition in the galaxy’s halo. In all simulations, cold filamentary gas accretion to the halo results in ∼4 times more specific angular momentum in cold halo gas ( λ {sub cold} ≳ 0.1) than in the dark matter halo. At z > 1, this inflow takes the form of inspiraling cold streams that are co-directional in the halo of the galaxy and are fueled, aligned, and kinematically connected to filamentary gas infall along the cosmic web. Due to the qualitative agreement among disparate simulations, we conclude that the buildup of high angular momentum halo gas and the presence of these inspiraling cold streams are robust predictions of Lambda Cold Dark Matter galaxy formation, though the detailed morphology of these streams is significantly less certain. A growing body of observational evidence suggests that this process is borne out in the real universe.
Wildfire-Power Grid Interactions: Feedback, Impacts, Monitoring, Modeling, and Mitigation Strategies
Wildfires are increasingly interacting with electric power systems through a two-way hazard chain: fires damage grid assets and trigger cascading outages, while grid faults can ignite new fires under hot, dry, and windy conditions. This review synthesizes the state of knowledge across five domains: (i) physical impacts of flames, heat, and smoke on lines, towers, insulators, and substations; (ii) power-infrastructure-initiated ignitions via conductor clash, high-impedance faults, and corona discharge; (iii) widespread blackouts and disproportionate societal impacts; (iv) multi-scale monitoring spanning laboratory tests, in-situ and grid-integrated sensors, and Earth observation; (v) coupled modeling that links fire behavior with grid operations; and (vi) technological and strategic mitigation pathways spanning prevention, response, and recovery. We integrate these domains into a novel 'feedback-aware' socio-technical framework. Through a longitudinal analysis (2005-2025) of global incidents, we identify that while vegetation contact remains the most frequent ignition source, aging infrastructure failure has emerged as a critical driver of catastrophic 'mega-fires'. We further identify persistent gaps, including limited interoperability of high-frequency grid and environmental data, scarce real-time data assimilation, and under-developed equity metrics for outage management. We conclude by outlining a research agenda to (1) deploy interoperable sensing architectures, (2) advance feedback-coupled fire-grid simulations, and (3) evaluate mitigation portfolios through techno-economic and fairness lenses. Recognizing wildfire-grid interactions as coupled socio-technical systems is essential for protecting infrastructure and communities and for ensuring reliable, sustainable electricity in a changing world.
Autonomy Loops for Monitoring, Operational Data Analytics, Feedback, and Response in HPC Operations
Many High Performance Computing (HPC) facilities have developed and deployed frameworks in support of continuous monitoring and operational data analytics (MODA) to help improve efficiency and throughput. Because of the complexity and scale of systems and workflows and the need for low-latency response to address dynamic circumstances, automated feedback and response have the potential to be more effective than current human-in-the-loop approaches which are laborious and error prone. Progress has been limited, however, by factors such as the lack of infrastructure and feedback hooks, and successful deployment is often site- and case-specific. In this position paper we report on the outcomes and plans from a recent Dagstuhl Seminar, seeking to carve a path for community progress in the development of autonomous feedback loops for MODA, based on the established formalism of similar (MAPE-K) loops in autonomous computing and self-adaptive systems. By defining and developing such loops for significant cases experienced across HPC sites, we seek to extract commonalities and develop conventions that will facilitate interoperability and interchangeability with system hardware, software, and applications across different sites, and will motivate vendors and others to provide telemetry interfaces and feedback hooks to enable community development and pervasive deployment of MODA autonomy loops.
Tuning of Nacelle Feedback Gains for Floating Wind Turbine Controllers Using a Two-DOF Model
Designing a collective blade pitch controller for floating offshore wind turbines (FOWTs) poses unique challenges due to the interaction of the controller with the dynamics of the platform. The controller must also handle the competing objectives of power production performance and fatigue load management. Existing solutions either detune the controller with the result of slowed response, make use of complicated tuning methods, or incorporate a nacelle velocity feedback gain. With the goal of developing a simple control tuning method for the general FOWT researcher that is easily extensible to a wide array of turbine and hull configurations, this last idea is built upon by proposing a simple tuning strategy for the feedback gain. This strategy uses a two degree-of-freedom (DoF) turbine model that considers tower-top fore-aft and rotor angular displacements. For evaluation, the nacelle velocity term is added to an existing gain scheduled proportional-integral controller as a proportional gain. The modified controller is then compared to baseline land-based and detuned controllers on an example system for several load cases. First-pass results are favorable, demonstrating how researchers can use the proposed tuning method to efficiently schedule gains for adequate controller performance as they investigate new FOWT configurations.
Feedbacks among O2 and CO2 in deep soil gas, oxidation of ferrous minerals, and fractures: A hypothesis for steady-state regolith thickness
Not provided.
Biospheric feedback effects in a synchronously coupled model of human and Earth systems
Fossil fuel combustion and land-use change are the first and second largest contributors to industrial-era increases in atmospheric carbon dioxide concentration, which is itself the largest driver of present-day climate change1. Projections of fossil fuel consumption and land-use change are thus fundamental inputs for coupled Earth system models (ESM) used to estimate the physical and biological consequences of future climate system forcing2,3. While empirical datasets are available to inform historical analyses4,5, assessments of future climate change have relied on projections of energy and land use based on energy economic models, constrained using historical and present-day data and forced with assumptions about future policy, land-use patterns, and socio-economic development trajectories6. Here we show that the influence of biospheric change – the integrated effect of climatic, ecological, and geochemical processes – on land ecosystems has a significant impact on energy, agriculture, and land-use projections for the 21st century. Such feedbacks have been ignored in previous ESM studies of future climate. We find that synchronous exposure of land ecosystem productivity in the economic system to biospheric change as it develops in an ESM results in a 10% reduction of land area used for crop cultivation; increased managed forest area and land carbon; a 15-20% decrease in global crop price; and a 17% reduction in fossil fuel emissions for a low-mid range forcing scenario7. These simulation results demonstrate that biospheric change can significantly alter primary human system forcings to the climate system. This synchronous two-way coupling approach removes inconsistencies in description of climate change between human and biosphere components of the coupled model, mitigating a major source of uncertainty identified in assessments of future climate projections8-10.
Modeling and Feedback Compensator Design for Power-Hardware-in-the-Loop System for Medium-Voltage Grid-Connected Power Converters
Hardware-in-the-loop (HIL) evaluation is a method in which the test subject is split into a physical part and a simulated part, and these parts are connected with interfaces to form a combined physical-numerical system. Power-hardware-in-the-loop (PHIL) systems, where actual hardware is connected to a real-time model, can exhibit issues of instability, inaccuracy and errors when operating in a closed-loop. The challenges of generating a PHIL setup are that, first, because of the limited dynamic response of the different parts of the system, the test results might be inaccurate, and, second, because of the high frequency noise introduced by the sensors to the closed-loop system, it can be difficult to design a compensator for the real-time emulator response, while stabilizing the closed-loop system at the same time. In this paper, different parts of a PHIL system are characterized, and the feedback compensator system design is proposed for the stable operation of the closed-loop PHIL system. The issues as observed in a PHIL system without any compensator are demonstrated using experimental results, and the effectiveness of a first order phase lead compensator is validated.