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At least 1,243 records · Page 69
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Optimisation of the Kaplan hydropower system via PID 2 and digital twin

Here, this paper proposes a proportional–integral-double–derivative (PID 2 ) optimisation method for the Kaplan hydropower system by building a digital twin. The study first uses one multilayer perceptron (MLP) to model the hydroturbine dynamic and then adopts three connected MLPs to model the generator dynamic, both in an open-loop fashion. Inspired by stochastic distribution control (SDC) theory, we regard the training of the turbine's neural network model as a process control problem, and we propose minimising entropy loss to update the network parameters. The next step is to build the digital twin by connecting the neural network models with a PID 2 controller and a lead-lag exciter and run the whole model in a closed-loop fashion. After that, a binary search approach is applied to optimise the PID 2 parameters based on the obtained digital twin model. The simulation results show that the proposed method can reduce the mean square tracking error by more than 90%. Furthermore, the method is extended to jointly optimise the PID 2 controller and excitation system gains through multiobjective optimisation, leveraging Pareto frontier analysis to balance active power and voltage tracking performance. Simulation results confirm the effectiveness of the proposed method, achieving a 83.46% reduction in relative mean square error of active power, a 47.13% reduction in terminal voltage tracking error, and an 82.78% improvement in the overall scalarized objective.

Hydropower system↗
DOE OSTI2025

Energy-momentum-conserving stochastic differential equations and algorithms for the nonlinear Landau-Fokker-Planck equation

Coulomb collision is a fundamental diffusion process in plasmas that can be described by the Landau-Fokker-Planck (LFP) equation or the stochastic differential equation (SDE). While energy and momentum are conserved exactly in the LFP equation, they are conserved only on average by the conventional corresponding SDEs, suggesting that the underlying stochastic process may not be well defined by such SDEs. Here, in this study, we derive new SDEs with exact energy-momentum conservation for the Coulomb collision by factorizing the collective effect of field particles into individual particles and enforcing Newton's third law. These SDEs, when interpreted in the Stratonovich sense, have a particularly simple form that represents pure diffusion between particles without drag. To demonstrate that the new SDEs correspond to the LFP equation, we develop numerical algorithms that converge to the SDEs and preserve discrete conservation laws. Simulation results are presented in a benchmark of various relaxation processes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

Decadal Spiciness Variability in the Subtropical-Tropical Pacific in the CESM2 Large Ensemble

Tropical Pacific decadal variations impact weather and climate around the world and are also connected to variations in the global warming trend. The mechanisms driving these long-term modulations, particularly the role of subsurface ocean dynamics, are still debated. Here, we investigate the dynamics of spiciness (density-compensated temperature and salinity) anomalies in the tropical and subtropical Pacific, which are hypothesized as a possible driving mechanism of decadal climate variability. Based on the analysis of 100 realizations from the Community Earth System Model Version 2 Large Ensemble (CESM2-LE), we demonstrate a coupling between the subtropics and the equatorial Pacific by propagating spiciness anomalies at decadal time scales. The CESM2-LE simulates spiciness variability along a subduction path from the subtropics to the equator with frequency spectra that show the highest power at low frequencies and a power decay proportional to a −4 slope for frequencies greater than 0.01 cycles per months, corresponding to periods smaller than ∼8.5 years. Signals that originate in the Southern Hemisphere (SH) dominate and arrive with a larger magnitude at the equator compared to spiciness anomalies from the Northern Hemisphere (NH). Spiciness anomalies from the SH have shorter propagation times and are strengthened along their pathway as stochastic wind stress curl forcing generates anomalous baroclinic ocean pressure gradients. These pressure gradients generate spiciness anomalies via anomalous advection across climatological spiciness gradients in the SH. We conclude that the observed spiciness variance at decadal time scales is consistent with a forcing by stochastic wind variations that are low-pass filtered by ocean dynamics.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Modeling the Amplfied OSC Experiment at IOTA

Optical Stochastic Cooling (OSC), a beam cooling technique based on Stochastic Cooling, is in the early stages of experimental development. It uses radiation produced by the beam in an undulator magnet (the pickup) to correct the momentum deviation of particles downstream in another undulator (the kicker). The OSC mechanism was recently demonstrated at Fermilabʼs IOTA ring using a passive configuration. However, the cooling rate of OSC can be dramatically increased by first amplifying the undulator radiation before applying the corrective kick. In collaboration with the IOTA experiment, we developed a computational model of the OSC mechanism. This work presents beam‐dynamics simulations of the amplified‐OSC configuration. We implement a model of intrabeam scattering and study the effects on beam equilibrium and diffusion rate as a function of bunch charge. Finally, we investigate the phase‐space dynamics with various coupling configurations between the transverse and longitudinal planes.

Dick, A. J.↗
DOE OSTI2025

Realizing Steady-State Microbunching with Optical Stochastic Crystallization

Optical Stochastic Cooling (OSC) is a state-of-the-art beam cooling technology first demonstrated in 2021 at the IOTA storage ring at Fermilab's FAST facility. A second phase of the research program is planned to run in 2026 and will incorporate an optical amplifier to enable significantly increased cooling rates and greater operational flexibility. In addition to beam cooling, an OSC system can be configured to enable advanced control over the phase space of the beam. An example operational mode could enable crystallization, where the particles in a bunch are locked into a self-reinforcing, regular microstructure at the OSC fundamental wavelength; we refer to this as Optical Stochastic Crystallization (OSX). OSX represents a new path toward Steady-State Microbunching (SSMB), which may enable light sources combining the high brightness of a free-electron laser with the high repetition rate of a storage ring. Such a source has applications from the terahertz to the extreme ultraviolet (EUV), including high-power EUV generation for semiconductor lithography. This contribution will discuss the integration of OSX development as part of the OSC program at IOTA. The design of an accelerator lattice to enable the mechanism and associated high fidelity simulations will be shown, and a path to realizing an experimental demonstration will be discussed.

Wallbank, Michael James [Fermilab]↗
DOE OSTI2025

Steady-State Microbunching using Optical Stochastic Cooling

Optical Stochastic Cooling (OSC) is a state-of-the-art beam cooling technology first demonstrated in 2021 at the IOTA storage ring at Fermilab's FAST facility. A second phase of the research program is planned to run in 2026 and will incorporate an optical amplifier to enable significantly increased cooling rates and greater operational flexibility. In addition to beam cooling, an OSC system can be configured to enable advanced control over the phase space of the beam. An example operational mode could enable crystallization, where the particles in a bunch are locked into a self-reinforcing, regular microstructure at the OSC fundamental wavelength; we refer to this as Optical Stochastic Crystallization (OSX). OSX represents a new path toward Steady-State Microbunching (SSMB), which may enable light sources combining the high brightness of a free-electron laser with the high repetition rate of a storage ring. Such a source has applications from the terahertz to the extreme ultraviolet (EUV), including high-power EUV generation for semiconductor lithography. This contribution will discuss the integration of OSX development as part of the OSC program at IOTA. The design of an accelerator lattice to enable the mechanism and associated high fidelity simulations demonstrating the beam dynamics will be shown, and a path to realizing an experimental demonstration will be discussed.

Wallbank, Michael James [Fermilab]↗
NASA NTRS1977

Leaf optical system modeled as a stochastic process

A stochastic leaf radiation model based upon physical and physiological properties of dicot leaves has been developed. The model accurately predicts the absorbed, reflected, and transmitted radiation of normal incidence as a function of wavelength resulting from the leaf-irradiance interaction over the spectral interval of 0.40-2.50 micron. The leaf optical system has been represented as Markov process with a unique transition matrix at each 0.01-micron increment between 0.40 micron and 2.50 micron. Probabilities are calculated at every wavelength interval from leaf thickness, structure, pigment composition, and water content. Simulation results indicate that this approach gives accurate estimations of actual measured values for dicot leaf absorption, reflection, and transmission as a function of wavelength.

Tucker, C. J.↗
NASA NTRS1992

A stochastic damage model for the rupture prediction of a multi-phase solid. I - Parametric studies. II - Statistical approach

A stochastic damage model for predicting the rupture of a brittle multiphase material is developed, based on the microcrack-macrocrack interaction. The model, which incorporates uncertainties in locations, orientations, and numbers of microcracks, characterizes damage by microcracking and fracture by macrocracking. A parametric study is carried out to investigate the change of the stress intensity at the macrocrack tip by the configuration of microcracks. The inherent statistical distribution of the fracture toughness arising from the intrinsic random nature of microcracks is explored using a statistical approach. For this purpose, a computer simulation model is introduced, which incorporates a statistical characterization of geometrical parameters of a random microcrack array.

Lua, Yuan J.↗
NASA NTRS2010

Visual Performance Challenges to Low-Frequency Perturbations After Long-Duration Space Flight, and Countermeasure Development

Astronauts experience sensorimotor disturbances after long-duration space flight. After a water landing, crewmembers may need to egress the vehicle within a few minutes for safety and operational reasons in various sea state conditions. Exposure to even low-frequency motions induced by sea conditions surrounding a vessel can cause significant motor control problems affecting critical functions. The first objective of this study was to document human visual performance during simulated wave motion below 2.0 Hz. We examined the changes in accuracy and reaction time when subjects performed a visual target acquisition task in which the location of the target was offset vertically during horizontal rotation at an oscillating frequency of 0.8 Hz. The main finding was that both accuracy and reaction time varied as a function of target location, with greater performance decrements occurring when vertical targets were acquired at perturbing frequencies of 0.8 Hz in the horizontal plane. A second objective was to develop a countermeasure, base d on stochastic resonance (SR), to enhance sensorimotor capabilities with the aim of facilitating rapid adaptation to gravitational transitions after long-duration space flight. SR is a mechanism by which noise can enhance the response of neural systems to relevant sensory signals. Recent studies have shown that applying imperceptible stochastic electrical stimulation to the vestibular system (SVS) significantly improved balance and oculomotor responses. This study examined the effectiveness of SVS on improving balance performance. Subjects performed a standard balance task while bipolar SVS was applied to the vestibular system using constant current stimulation through electrodes placed over the mastoid process. The main finding of this study was that balance performance with the application of SR showed significant improvement in the range of 10%-25%. Ultimately an SR-based countermeasure might be fielded either as preflight training to enhance adaptability, or as a miniature patch-type stimulator worn post flight.

Mulavara, Ajitkumar↗
DOE OSTI2020

Gyrokinetic understanding of the edge pedestal transport driven by resonant magnetic perturbations in a realistic divertor geometry

Self-consistent simulations of neoclassical and electrostatic turbulent transport in a DIII-D H-mode edge plasma under resonant magnetic perturbations (RMPs) have been performed using the global total-f gyrokinetic particle-in-cell code x-point gyrokinetic code (XGC), in order to study density pump-out and electron heat confinement. The RMP field is imported from the extended magneto-hydrodynamics code M3D-C1, taking into account the linear two-fluid plasma response. With both neoclassical and turbulence physics considered together, the XGC simulation reproduces two key features of experimentally observed edge transport under RMPs: increased radial particle transport in the pedestal region that is sufficient to account for the experimental pump-out rate and suppression of the electron heat flux in the steepest part of the edge pedestal. In the simulation, the density fluctuation amplitude of modes moving in the electron diamagnetic direction increases due to interaction with RMPs in the pedestal shoulder and outward, while the electron temperature fluctuation amplitude decreases.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Hybridizing Machine Learning and Physically-based Earth System Models to Improve Prediction of Multivariate Extreme Events (AI Exploration of Wildland Fire Prediction)

Focal Areas: This project responds to two focal areas identified in the DOE Call for AI4ESP White Papers: 1) Predictive modeling through the use of artificial intelligence (AI) techniques, and 2) insights gleaned from complex data using explainable AI and big data analytics. Science Challenge: Large wildland fires (hereafter wildfires) appearing as high-impact compound climate extreme events are closely related to hydroclimate and water cycle extremes that modulate surface fuel supply and combustibility. These compound events have multivariate climatic features (e.g., temperature, precipitation, relative humidity, wind, lightning) and societal drivers (e.g., forest management, land use change, human caused ignitions). Meanwhile, they induce strong feedbacks to the coupled atmosphere, biosphere, and hydrosphere by perturbing regional and global radiation budget as well as ecological, biogeochemical, and water cycles across multiple spatiotemporal scales. The nonlinear interactions between these natural and anthropogenic components of the Earth system are too complex to be completely and adequately represented in today’s Earth system models (ESMs). The inherent stochastic nature of fire activity at all scales further increases the difficulty of its prediction using ESMs that are usually developed from deterministic equations and parameterizations. Besides, concurrence of long-term (decadal to interdecadal) global climate change and fire regime shifts overlapping with short-term (intraseasonal to interannual) variations of regional fire weather and burning activity confound predictability of these compound extreme events. We propose to address the above scientific challenges by using machine learning (ML)-based data-driven modeling techniques to integrate observations and physically-based ESMs’ simulations in a computationally efficient hybrid prediction system. This prediction system is supposed to characterize the wildfire’s sensitivity to climate and exogenous drivers at high resolution (~ 0.25°) on subseasonal to seasonal (S2S) timescales providing improved predictability and explainability. We will use the system to help identify: (1) What are the computational elements of a hybrid system needed to predict compound climate extreme events such as global wildfires? (2) What are the key drivers (either natural or anthropogenic) that modulate short-term variations of multivariate fire weather and burning activity over different regions? How can one take advantage of those driver-response relationships to improve the predictability of large wildfires on S2S time scales? (3) What are the underlying physical mechanisms and sources of improved predictability? Which ML techniques are optimal in revealing and adapting these mechanisms?

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2020

Underlying Fundamentals of Kalman Filtering for River Network Modeling

The grand challenge of producing hydrometeorological estimates every time and everywhere has motivated the fusion of sparse observations with dense numerical models, with a particular interest on discharge in river modeling. Ensemble methods are largely preferred as they enable the estimation of error properties, but at the expense of computational load and generally with underestimations. These imperfect stochastic estimates motivate the use of correction methods, that is, error localization and inflation, although the physical justifications for their optimality are limited. The purpose of this study is to use one of the simplest forms of data assimilation when applied to river modeling and reveal the underlying mechanisms impacting its performance. Our framework based on assimilating daily averaged in situ discharge measurements to correct daily averaged runoff was tested over a 4-yr case study of two rivers in Texas. Results show that under optimal conditions of inflation and localization, discharge simulations are consistently improved such that the mean values of Nash–Sutcliffe efficiency are enhanced from211.32 to 0.55 at observed gauges and from212.24 to21.10 at validation gauges. Yet, parameters controlling the inflation and the localization have a large impact on the performance. Further investigations of these sensitivities showed that optimal inflation occurs when compensating exactly for discrepancies in the magnitude of errors while optimal localization matches the distance traveled during one assimilation window. These results may be applicable to more advanced data assimilation methods as well as for larger applications motivated by upcoming river-observing satellite missions, such as NASA’s Surface Water and Ocean Topography mission.

Streamflow↗
DOE OSTI2022

Incorporate day-ahead robustness and real-time incentives for electricity market design

In this paper, we propose a two-stage electricity market framework to explore the participation of distributed energy resources (DERs) in a day-ahead (DA) market and a real-time (RT) market. The objective is to determine the optimal bidding strategies of the aggregated DERs in the DA market and generate online incentive signals for DER-owners to optimize the social-welfare taking into account network operational constraints. Distributionally robust optimization is used to explicitly incorporate data-based statistical information of renewable forecasts into the supply/demand decisions in the DA market. We evaluate the conservativeness of bidding strategies distinguished by different risk aversion settings. In the RT market, a bi-level time-varying optimization problem is proposed to design the online incentive signals to tradeoff the RT imbalance penalty for distribution system operators (DSOs) and the costs of individual DER-owners. This enables tracking their optimal dispatch to provide fast balancing services, in the presence of time-varying network states while satisfying the voltage regulation requirement. Simulation results on both DA wholesale market and RT balancing market demonstrate the necessity of this two-stage design, and its robustness to uncertainties, the performance of convergence, the tracking ability and the feasibility of the resulting network operations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

A new effective theory for stochastic relativistic hydrodynamics

Thermal fluctuations are a fundamental feature of dissipative systems that are essential for understanding physics near the expected critical point of QCD and in small systems. When such fluctuations are modeled naively in relativistic systems, strange features can appear such as negative self-correlation functions. We construct an effective theory for nonlinear stochastic relativistic hydrodynamics that ensure a well-posed mathematical formulation. Using Crooks fluctuation theorem, we derive a symmetry of the effective action that incorporates fluctuations through a suitable free energy functional. For divergence type theories, the action can then be fully specified using a single vector generating current. The equations of motion obtained using this procedure are guaranteed to be flux conservative and symmetric hyperbolic when the dynamics is causal. This ensures that these equations are well-posed (for suitable initial data) and are in a form that can easily be simulated, including with Metropolis techniques.

Mullins, Nicki [University of Illinois at Urbana-C↗
DOE OSTI2023

Modeling of the amplified optical stochastic cooling experiment at IOTA

Optical Stochastic Cooling (OSC), a beam cooling technique based on Stochastic Cooling, is in the early stages of experimental development. It uses radiation produced by the beam in an undulator magnet (the pickup) to correct the momentum deviation of particles downstream in another undulator (the kicker). The OSC mechanism was recently demonstrated at Fermilab’s IOTA ring using a passive configuration. However, the cooling rate of OSC can be dramatically increased by first amplifying the undulator radiation before applying the corrective kick. In collaboration with the IOTA experiment, we developed a computational model of the OSC mechanism. This paper presents beam-dynamics simulations of the amplified-OSC configuration. We implement a model of intrabeam scattering and study the effects on beam equilibrium and diffusion rate as a function of bunch charge. Finally, we investigate the phase-space dynamics with various coupling configurations between the transverse and longitudinal planes.

43 PARTICLE ACCELERATORS↗
NASA NTRS1991

Probabilistic Structural Analysis Methods (PSAM) for select space propulsion system components

The fourth year of technical developments on the Numerical Evaluation of Stochastic Structures Under Stress (NESSUS) system for Probabilistic Structural Analysis Methods is summarized. The effort focused on the continued expansion of the Probabilistic Finite Element Method (PFEM) code, the implementation of the Probabilistic Boundary Element Method (PBEM), and the implementation of the Probabilistic Approximate Methods (PAppM) code. The principal focus for the PFEM code is the addition of a multilevel structural dynamics capability. The strategy includes probabilistic loads, treatment of material, geometry uncertainty, and full probabilistic variables. Enhancements are included for the Fast Probability Integration (FPI) algorithms and the addition of Monte Carlo simulation as an alternate. Work on the expert system and boundary element developments continues. The enhanced capability in the computer codes is validated by applications to a turbine blade and to an oxidizer duct.

Source record↗
DOE OSTI2022

Improved Measurements of Galaxy Star Formation Stochasticity from the Intrinsic Scatter of Burst Indicators

Abstract Measurements of short-timescale star formation variations (i.e., “burstiness” or star formation stochasticity) are integral to our understanding of star formation feedback mechanisms and the assembly of stellar populations in galaxies. We expand upon the work of Broussard et al. by introducing a new analysis of galaxy star formation burstiness that accounts for variations in the Q sg = E B − V stars / E B − V gas distribution, a major confounding factor. We use Balmer decrements from the MOSFIRE Deep Evolution Field (MOSDEF) survey to measure Q sg , which we use to construct mock catalogs from the Santa Cruz Semi-Analytic Models and Mufasa cosmological hydrodynamical simulation based on 3D-HST, Fiber Multi-Object Spectrograph (FMOS)-COSMOS, and MOSDEF galaxies with H α detections. The results of the mock catalogs are compared against observations using the burst indicator η = log 10 ( SFR H α / SFR NUV ) , with the standard deviation of the η distribution indicating burstiness. We find decent agreement between mock and observed η distribution shapes; however, the FMOS-COSMOS and MOSDEF mocks show a systematically low median and scatter in η in comparison to the observations. This work also presents the novel approach of analytically deriving the relationship between the intrinsic scatter in η , scatter added by measurement uncertainties, and observed scatter, resulting in an intrinsic burstiness measurement of 0.06–0.16 dex.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2001

Stochastic Modeling and Generation of Partially Polarized or Partially Coherent Electromagnetic Waves

Many new Earth remote-sensing instruments are embracing both the advantages and added complexity that result from interferometric or fully polarimetric operation. To increase instrument understanding and functionality a model of the signals these instruments measure is presented. A stochastic model is used as it recognizes the non-deterministic nature of any real-world measurements while also providing a tractable mathematical framework. A stationary, Gaussian-distributed model structure is proposed. Temporal and spectral correlation measures provide a statistical description of the physical properties of coherence and polarization-state. From this relationship the model is mathematically defined. The model is shown to be unique for any set of physical parameters. A method of realizing the model (necessary for applications such as synthetic calibration-signal generation) is given and computer simulation results are presented. The signals are constructed using the output of a multi-input multi-output linear filter system, driven with white noise.

Davis, Brynmor↗