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Results for “Applied Dynamical Systems”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Interplay between hydrogen, temperature, and character angle on dissociated dislocation energies in Fe–Ni–Cr austenitic stainless steels

Dislocation energy has an important role in the mechanical performance of structural metals. While dislocation energies cannot be fully obtained from continuum theories due to the contribution of the dislocation core, they have been calculated via atomistic simulations in elemental metals. However, constraints on the local atomic environments have prevented the use of such approaches in systems that incorporate alloying or interstitial solutes. In this work, we develop robust molecular dynamics methods to resolve these issues through a geometric construction of dislocation dipoles and the calculation of time-averaged energies. Furthermore, we apply these methods to calculate dislocation energies (including core energies) in an Fe 70 Ni 11 Cr 19 austenitic steel at a variety of character angles, hydrogen concentrations, temperatures, and dipole spacings. The resulting highly converged energies show an excellent agreement with continuum expressions. Overall, hydrogen concentrations up to 1.0 % do not have a significant effect on the elastic parameters and dislocation energy. The methods and insights derived in this work have the potential to facilitate the calculation of dislocation energies in a wide range of systems, and to guide our understanding of hydrogen embrittlement.

Alloyed systems↗
DOE OSTI2024

A Generation-Storage Coordination Dispatch Strategy for Power System Based on Causal Reinforcement Learning

In the backdrop of global energy transformation, power systems integrating high proportions of renewable energy sources are facing unprecedented challenges in operational stability and dispatch efficiency. To address these challenges, this study introduces a generation-storage coordination real-time dispatch strategy based on Causal Power System Dynamic Reinforcement Learning (CPSDRL). Diverging from traditional reinforcement learning approaches, CPSDRL innovatively incorporates causal inference within the state prediction model - the crux of model-based reinforcement learning - thereby establishing the Power Causal Dynamic Model (PCDM). Assisted by the prior knowledge of power systems, the model significantly enhances prediction accuracy and reliability through a two-stage training process. Utilizing PCDM, this study further applies a direct policy search algorithm to optimize the real-time dispatch strategy. Experimental results indicate that the proposed method improves the stability of generation-storage coordination real-time dispatch and exhibits competitive advantages in sample efficiency and computational speed, compared to traditional model-based and model-free reinforcement learning algorithms. This method is expected to enhance the practicality and adaptability of causal reinforcement learning techniques in power system scheduling and control.

causal reinforcement learning↗
DOE OSTI2026

CLM5 Simulations of Soil Moisture and Gross Primary Productivity for CONUS at 0.125 degrees

This dataset provides 0.125-degree gridded simulations of soil moisture and gross primary productivity (GPP) for the Contiguous United States (CONUS), generated using the Community Land Model version 5 (CLM5) with the biogeochemistry module enabled. The data covers a historical baseline (1980-2015) and mid-century future projections (2020-2055). Future projections are organized into two sets of scenarios to distinguish the impacts of different drivers: (1) Atmospheric Only (ATM): These scenarios apply future atmospheric forcings while holding land use and land cover (LULC) at historical baseline levels. The atmospheric forcings represent moderately versus severely hotter/drier atmospheric conditions (dynamically downscaled perturbed thermodynamics simulations based on CMIP6 SSP245 and SSP585 warming signals), each with cooler versus hotter Earth System Model temperature sensitivity instantiations. These scenarios are identified in the folder names as rcp45_cooler_near, rcp45_hotter_near, rcp85_cooler_near, and rcp85_hotter_near. (2) Coupled Atmospheric and Land-Use (LAND+ATM): These scenarios apply future atmospheric forcing together with future LULC by pairing atmospheric pathways with lower versus higher population/economic growth scenarios representing Shared Socioeconomic Pathways 3 and 5 (SSP3 and SSP5). These scenarios are identified in the file names as ssp3_rcp45_cooler_near, ssp3_rcp45_hotter_near, ssp5_rcp85_cooler_near, and ssp5_rcp85_hotter_near. Please refer to the "README_first.md" file for detailed information on file structure, variables, units, and data formats.

drought↗
DOE OSTI2026

Magnonic spontaneous oscillation induced by parametric pumping

Spontaneous dynamic systems have attracted significant attention for their rich underlying physics such as phase-locking and synchronization. In this work, we report a new mechanism of generating magnetic spontaneous oscillation via parametric pumping. By applying a pump tone to excite propagating spin waves in a yttrium iron garnet delay line, four-wave mixing converts the pump mode into two phase-autonomous propagating magnon modes, i.e. a spontaneous mode with nearly twice the wavenumber of the pump mode and an idler mode with nearly zero wavenumber. This allows us to reliably generate ultrasharp spin wave dynamics with broad frequency tunability from the pump and magnetic field. We show that the spontaneous mode can be phase-locked to a probe tone, similar to an auto-oscillator. Furthermore, the spontaneous dynamics can be used to implement a high-gain magnonic parametric amplifier with a gain up to 40 dB. Our results open a new avenue for studying nonlinear magnonics and synchronization physics in propagating magnon geometry and for developing new magnonic devices.

Li, Yi↗
DOE OSTI2025

Towards provision of regularly updated climate data from the Coupled Model Intercomparison Project

The Coupled Model Intercomparison Project (CMIP) is a flagship of the World Climate Research Programme (WCRP). CMIP has become a recognised ‘brand’ in climate circles evolving over the last thirty years from a targeted research activity by a small number of climate modelling centres intercomparing their Earth System Model (ESM) simulations to a broad international coordinated research effort (Durack et al, 2025). CMIP is organized as a research activity leveraging funded and in-kind contributions from experts within modelling centres and the broader scientific community supported more recently by a fully-funded International Project Office. Within CMIP, Model Intercomparison Projects (MIPs) are community-designed to understand past, present and future climate. CMIP data provides a valuable resource for climate research and is routinely used to assess model representation of climate processes and test scientific hypotheses in the context of model uncertainty and (forced and internal) variability as evident from its prolific use in scientific publications1 . The impact relies on enabling infrastructure (most prominently via the Earth System Grid Federation (ESGF)), which allows sharing of simulation output, provision of the boundary conditions used in each simulation, and definition of the data standards that are essential to facilitating wide use of the data. The impact is supplemented by the wide-ranging scrutiny to which model simulations are subjected. Beyond its use in research, CMIP data is a key resource for communities producing derived climate information from downscaling and impact studies, such as the Coordinated Regional Downscaling Experiment (CORDEX; Gutowski et al., 2016) and the Intersectoral Impacts MIP (ISIMIP; Frieler et al., 2024). Government, academic and commercial entities also increasingly rely on CMIP and its downstream data for climate risk assessments and climate services (for example, Copernicus Climate Change Service and World Bank portal). This means that, although CMIP is a research activity, it increasingly serves a secondary and very relevant role as a provider of climate data – a long-recognised dichotomy (Stevens, 2024). Research and applications have distinct needs, with the former requiring flexibility and generality and the latter consistency. Here we explain how the design of the research activity has been adapted to reduce the burdens imposed by applications and how the research infrastructure might evolve to further enable scientific inquiry. We propose one possible approach to consistently providing model information and projections for applications in the future.

Environmental sciences↗
DOE OSTI2026

Memory-efficient nonsmooth dynamic optimization using adaptive randomized compression

Dynamic optimization problems arise in many applications including flow control, full waveform inversion, and medical imaging. These problems are plagued by significant computational challenges. One such challenge — and the focus of this work — is the memory limitation induced by the size of the underlying dynamical system. In particular, the entire dynamic trajectory is required for derivative computation and therefore must be stored or recomputed using, e.g., checkpointing. Although recent work demonstrated the use of adaptive randomized sketching to overcome the memory challenge, that work only applies to smooth unconstrained problems, prohibiting its use for nonsmooth regularized and constrained problems. The inclusion of nonsmooth regularizers and constraints is critical as they often arise in an attempt to preserve certain physical properties or to promote sparsity. To solve these problems, we introduce a trust-region algorithm for minimizing the sum of a smooth nonconvex function and a nonsmooth convex function that leverages randomized sketching to compress the dynamical system trajectories and adaptively adjust the sketch rank to satisfy a gradient inexactness condition. We prove convergence of this algorithm and demonstrate that it achieves substantial memory reduction on three discretized PDE-constrained optimization applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Evaluation of dynamical downscaling in a fully coupled regional earth system model

A set of decadal simulations has been completed and evaluated for gains using the Regional Arctic System Model (RASM) to dynamically downscale data from a global Earth system model and two atmospheric reanalyses. RASM is a fully coupled atmosphere–land–ocean–sea ice regional Earth system model. Nudging to the forcing data is applied to approximately the top half of the atmospheric domain. RASM simulations were also completed with a modification to the atmospheric physics for evaluating changes to the modeling system. The results show that for the top half of the atmosphere, the RASM simulations follow closely to that of the forcing data, regardless of the forcing data. The results for the lower half of the atmosphere, as well as the surface, show a clustering of atmospheric state and surface fluxes based on the modeling system. At all levels of the atmosphere the imprint of the weather from the forcing data is present as indicated in the pattern of the annual means. Biases, in comparison to reanalyses, are evident in the Earth system model forced simulations for the top half of the atmosphere but are not present in the lower atmosphere. This suggests that bias correction is not needed for fully coupled dynamical downscaling simulations. While the RASM simulations tended to go to the same mean state for the lower atmosphere, there are a differences in the variability and changes of weather patterns across the ensemble of simulations. These differences in the weather result in variances in the sea ice and oceanic states.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Fermi-Based Kinetic Model for the Sabatier Reaction: Sabatier Principle and Beyond It

The CO 2 methanation reaction (aka the Sabatier reaction) is one of the important carbon utilization technologies to reduce atmospheric greenhouse gases. In this study, kinetic modeling of the Sabatier reaction proceeding via the CO route has been presented by considering weak and strong chemisorption concepts rooted in electronic theory. Based on the single-route mechanism of the Sabatier reaction, the dependence of the reaction rate on the position of the catalyst Fermi level with respect to the antibonding states of the reagent (CO 2 ) and the product (CH 4 ), is demonstrated with the classic Sabatier volcano-shape. Furthermore, the model was applied to explain experimental results of reaction rates for Ni- and Ru-based catalytic systems and to understand origin of enhancement of turnover frequencies established for dynamic catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Aggregated DER_A Model Parameterization via Online Moving Horizon Estimation

Here, this paper introduces a methodology for parameterizing the DER_A model using a novel smooth mathematical representation, simplifying the process and preserving accuracy in modeling inverter-based generator (IBG). The methodology employs an online parameterization process that can operate in real-time. The model parameterization process is structured into five sequential steps, each targeting a specific aspect of the DER_A model through moving horizon estimation. This approach adapts to systems with varying voltage and frequency support requirements by selectively applying each step. Simulation results on systems with both known and unknown parameters validate the methodology’s effectiveness. The online moving horizon estimation technique accurately captures the dynamics of the overall system and ensures that the parameterized DER_A model closely mirrors the real system’s voltage, current, and power dynamics. The findings highlight the potential of this methodology to substantially improve and simplify the dynamic modeling of power systems, paving the way for more reliable and robust IBG and grid integration.

42 ENGINEERING↗
DOE OSTI2026

CFD-Enhanced Calibration of a Multihole Probe for Small Uncrewed Aircraft Systems

A robust calibration method with a 9-hole probe (9HP) for inertial wind vector measurements from a small uncrewed aircraft system (sUAS) is presented. Calibration accuracy is improved by using computational fluid dynamics (CFD) to estimate corrections, such as those for test section blockage, that are generally applied in wind tunnel testing. A method for estimating experimental bias is presented to account for flow variations over the pressure taps as the 9HP is repositioned in the test section. Installation effects from flow over the airframe and upwash produced by the wings are estimated from CFD simulations of the entire airframe at the expected cruise speed. An initial CFD analysis has demonstrated a quantifiable linear relationship between the measured and actual angle of attack as measured from the relative wind frame. In conclusion, the objective of these additional steps is to increase the accuracy of 9HP calibration.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Fast methods for multisite charge transfer. Processes II. Analytic nuclear gradients and nonadiabatic dynamics for cCASSCF(1,n) and cCASSCF(2n-1,n) wavefunctions

In this work we derive and implement analytic nuclear gradients and derivative couplings for a constrained complete active space self-consistent field with a small active space designed to model electron or hole transfer. Using a Lagrangian formalism, we are able to differentiate both the CASSCF energy and the constraint (which is required for smooth surfaces over a wide range of parameter space), and the resulting efficient algorithm can be immediately applied to nonadiabatic dynamics simulations of charge transfer processes. Here, we run initial surface-hopping simulations of a proton coupled electron transfer event for a phenoxyl–phenol system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Frequency-domain modeling of floating wind arrays with shared mooring lines

A frequency-domain model for floating wind turbine dynamics has been extended to model floating wind farms with couplings from shared mooring systems. The model, called RAFT, could previously calculate the mean offsets and wave-induced response spectra for single floating wind turbines. Now, the model supports multiple floating wind turbines, each with their own properties and responses, along with mooring lines that run directly between floating wind turbines in the array, meaning that shared mooring lines or fully suspended dynamic power cables can be included. This capability is achieved by setting up an array-level solution of the system mean offsets and assembling the full system matrices for solving the dynamic response. The quasi-static mooring model MoorPy is used to linearize the mooring system properties. To compute the floating wind turbine relative motions, phase offsets are applied to each turbine's response as a function of wave frequency based on the wavelength and relative positions in the array. These differential motions are then applied to mooring system tension Jacobians to compute the tension loads in the shared mooring lines. Overall, the capability provides a frequency-domain analog to the modeling capabilities of the floating support structure in FAST.Farm. Mean offsets and power spectral density plots of responses are compared between RAFT and FAST.Farm to verify the implementation. The results indicate good agreement within the expectations of a frequency-domain modeling approach and suggest correct implementation of the shared mooring aspects. Additionally, a unique comb-like frequency response in the shared mooring line tensions has been observed. This phenomenon has a clear physical basis and may be an important design consideration for future shared mooring systems.

17 WIND ENERGY↗
DOE OSTI2025

Mesoscale Convective Systems Tracking Method Intercomparison (MCSMIP): Application to DYAMOND Global km‐Scale Simulations

Abstract Global kilometer‐scale models represent the future of Earth system modeling, enabling explicit simulation of organized convective storms and their associated extreme weather. Here, we comprehensively evaluate tropical mesoscale convective system (MCS) characteristics in the DYAMOND (DYnamics of the atmospheric general circulation modeled on non‐hydrostatic domains) simulations for both summer and winter phases. Using 10 different feature trackers applied to simulations and satellite observations, we assess MCS frequency, precipitation, and other key characteristics. Substantial differences (a factor of 2–3) arise among trackers in observed MCS frequency and their precipitation contribution, but model‐observation differences in MCS statistics are more consistent across trackers. DYAMOND models are generally skillful in simulating tropical mean MCS frequency, with multi‐model mean biases ranging from −2%–8% over land and −8%–8% over ocean (summer vs. winter). However, most DYAMOND models underestimate MCS precipitation amount (23%) and their contribution to total precipitation (17%). Biases in precipitation contributions are generally smaller over land (13%) than over ocean (21%), with moderate inter‐model variability. While models better simulate MCS diurnal cycles and cloud shield characteristics, they overestimate MCS precipitation intensity and underestimate stratiform rain contributions (up to a factor of 2), particularly over land, albeit observational uncertainties exist. Additionally, models exhibit a wide range of precipitable water in the tropics compared to reanalysis and satellite observations, with many models showing exaggerated sensitivity of MCS precipitation intensity to precipitable water. The MCS metrics developed here provide process‐oriented diagnostics to guide future model development.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Charge Transfer Dynamics in Dye-Sensitized Photocatalysts Using Metal Complex Sensitizers with Long-Wavelength Visible Light Absorption Based on Singlet–Triplet Excitation

An Os(II) polypyridyl complex was applied as a photosensitizer in dye-sensitized photocatalyst systems based on Pt-intercalated HCa 2 Nb 3 O 10 and Pt-loaded TiO 2 . The Os(II) complex exhibits a spin-forbidden but partially allowed triplet metal-to-ligand charge transfer ( 3 MLCT) transition, enabling broad visible light absorption up to 800 nm, which surpasses that of conventional Ru(II)-based dyes. Despite its shorter excited-state lifetime compared to Ru(II) complexes, efficient electron injection from the excited Os(II) dye into the semiconductor was confirmed. Under visible-light irradiation, the Os(II)- sensitized photocatalysts showed higher H 2 evolution activity than the Ru(II)-sensitized photocatalysts when sodium ascorbate was used as an electron donor, demonstrating effective utilization of long-wavelength visible light. In contrast, negligible H 2 evolution was observed when NaI was employed as a redox mediator for Z-scheme water splitting. Transient absorption spectroscopy revealed that the lack of activity stemmed from inefficient electron transfer from I − to oxidized Os(II). These findings highlight the importance of selecting appropriate redox mediators to fully exploit long-wavelength dyes for overall water splitting under visible light.

artificial photosynthesis↗
DOE OSTI2024

Expanding the representation of aerosol, cloud, and precipitation processes with graph network-based simulators

We explored a novel framework for simulating the small-scale processes that drive the evolution of aerosol, cloud, and precipitation particles, which are a critical gap in the predictive understanding of weather and climate. Particle-based methods have emerged as an effective tool for modeling aerosol-cloud-precipitation interactions, but existing particle-based models are computationally too expensive to simulate the large domains relevant for the atmosphere or to represent the full suite of relevant processes. The lack of a comprehensive and efficient reference model is a critical bottleneck in our understanding of cloud and precipitation processes and our ability to parameterize these processes for regional- and global-scale simulations. To address this need, we explored an approach to accelerate and expand particle-based models using a new machine learning approach, graph network-based simulators (GNS). Rather than modeling the evolution of the system by numerically integrating continuity equations, the GNS represents dynamics through learned message passing. Our aim was to develop fast and accurate surrogate models for particle-based simulations. We explored applying GNS to simulate cloud droplet transport, growth, and evaporation under turbulent conditions, but we found the GNS over-smoothed the simulations. We then applied the GNS to simulate aerosol dynamics through gas condensation and found the GNS was able to reproduce the benchmark, physics-based simulation with high accuracy.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Enhancing Coherence Limits in Superconducting Quantum Systems for Computing and Sensing

This talk will highlight recent efforts at the SQMS Center to develop qudit-based quantum computing architectures using superconducting three-dimensional (3D) cavities, as well as the use of these ultra-coherent cavities for quantum sensing. I will present systematic studies of materials and devices aimed at identifying and mitigating the dominant sources of decoherence—including two-level systems (TLS), quasiparticles, and other noise mechanisms—in both transmons and 3D cavities. These investigations include microwave loss characterization of niobium, tantalum, aluminum, their native oxides, and substrate materials such as silicon and sapphire. By combining measurements on qubits and cavities, we disentangle subsystem-specific loss mechanisms and establish a hierarchy of mitigation strategies, leading to transmon coherence times exceeding one millisecond. I will also discuss studies of quasiparticle dynamics, including quasiparticle bursts observed in qubits operated both above ground and at the Gran Sasso underground laboratory, and the observation that applied magnetic fields can suppress temporal T₁ fluctuations. Building on these advances, we demonstrate a record-coherence two-cell cavity-qudit system with coherence times exceeding 20 milliseconds. Leveraging tunable sideband interactions together with error-resilient protocols, including measurement-based error correction and post-selection, we achieve high-fidelity quantum state control, including the preparation of Fock states up to N=20 with fidelities above 95% and the generation of high-fidelity two-mode entangled states. Finally, I will discuss how these ultra-coherent quantum systems are enabling emerging quantum sensing applications, including searches for dark matter and gravitational waves.

Roy, Tanay [Fermilab] (ORCID:000000019442862X)↗
DOE OSTI2025

High-throughput spin-bath characterization of spin defects in semiconductors

Detailed knowledge of the local environments of spin defects in semiconductors, such as nitrogenvacancy (NV) centers in diamond or divacancies in silicon carbide, is crucial for optimizing control and entanglement protocols in quantum sensing and information applications. However, at present a direct experimental characterization of individual defect environments is not scalable, as conventional spin-bath measurements are time consuming and difficult to automate. Achieving high-throughput characterization requires short experiments to probe the spin bath. However, with fewer and noisier measurements, the inverse problem of recovering spin-bath properties from measured data becomes ill posed, with multiple spin baths having a high likelihood of yielding the same data. In this work, we present a set of computational tools to resolve the ill-posed inverse problem of recovering the atomic positions and hyperfine couplings of random nuclei surrounding spin defects from sparse, noisy experimental coherence data, which can be obtained in hours. Here, we use a trans-dimensional Bayesian approach that incorporates ab initio data to yield full posterior distributions over nuclear spin environments, enabling robust recovery from limited data. We also provide practical tools and guidelines to determine the limits of detectability for hyperfine couplings under specific dynamical decoupling sequences and sampling conditions. In addition, we demonstrate how the tools developed here, in combination with ab initio simulations of spin baths, can guide the design of efficient experimental protocols for application-specific high-throughput screening. To showcase the utility of our approach, we apply it to design fast dynamical decoupling experiments to characterize the spin baths often individual NV centers in diamond. While the primary focus is on accelerating spin-bath characterization of spin defects, this Bayesian approach also lays the foundation for digital-twin studies of spin defects, where a virtual model of the spin-defect system evolves in real time with ongoing experimental measurements. Together, the set of tools we designed and applied paves the way for scalable deployment of spin defects in semiconductors for quantum sensing and information applications.

Bayesian methods↗
DOE OSTI2024

False vacuum decay and nucleation dynamics in neutral atom systems

Metastable states of quantum many-body systems with confinement offer a means to simulate false vacuum phenomenology, including nonequilibrium dynamical processes like decay by nucleation, in truncated limits. Recent work has examined the decay process in one-dimensional (1D) ferromagnetic Ising spins and superfluids. Here, in this paper, we study nucleation dynamics in 1D antiferromagnetic neutral atom chains with Rydberg interactions, using both numerical simulations and analytic modeling. We apply a staggered local detuning field to generate the metastable and ground states. Our efforts focus on two dynamical regimes: decay and annealing. In the first, we corroborate the phenomenological decay rate scaling and determine the associated parameter range for the decay process; in the second, we uncover and elucidate a procedure to anneal the metastable state from the initial to the final system, with intermediate nucleation events. We further propose experimental protocols to prepare the required states and perform quenches on near-term neutral atom quantum simulators, examining the experimental feasibility of our proposed setup and parameter regime.

97 MATHEMATICS AND COMPUTING↗