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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Systematic multi-machine analysis of the exhaust time-dependent behavior in tokamaks

The understanding of the time-scales and associated transient behavior of fusion exhaust plasmas plays a crucial role in its dynamic modeling and its control. This work presents an overview of experimental investigations of the exhaust dynamics in TCV, MAST-U, ASDEX-Upgrade, WEST, DIII-D, and JET. From the presented experiments, a clear picture arises on properties of the exhaust dynamics across machines. Particularly, we observe that the scrape-off layer equilibrates on fast time-scales ($>$ 70 Hz) and that exhaust dynamics measured in response to gas valve modulations mostly behave smoothly and linearly, with similarities across devices, across scenarios (H-mode, L-mode), injected species, and injection locations. The measurements presented have formed the basis for systematic exhaust control on the considered devices. We now present this database for the essential validation of dynamic exhaust models for reactor design and control.

control↗
DOE OSTI2023

Time-Dependent Corrosion Behavior of Aluminum Using Advanced Electrochemical and Characterization Techniques

The time-dependent corrosion behavior of pure aluminum (Al) in a chloride-containing environment was investigated using various electrochemical and characterization techniques for up to 336 h. Transmission electron microscopic and secondary ion mass spectroscopic analysis revealed the continuous dissolution of the surface film over the immersion time. In the meantime, the increasing passive oxide thickness resulted in the surface film resistance enhancement over the immersion time, as indicated by the electrochemical impedance spectroscopic analysis. The electrochemical noise measurements showed an increase in the corrosion kinetics with immersion time until 60 h because of the accelerated localized corrosion in the early stage of immersion. However, an inhibition in corrosion kinetics occurred after longer immersion times due to corrosion product deposition inside the pit.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Eigenmode Analysis of Pulsed Neutron Transport Simulations

We discuss the time dependent behavior of some simple pulsed neutron simulations of subcritical problems in slab geometry. Our intent is to investigate the eigenvalue structure of the discretized neutron transport equation and to show under some reasonable assumptions that a dominant time eigenvalue exists that has a nonnegative eigenvector that determines the long time dependent behavior of the solution.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Robust Distribution System Load Restoration With Time-Dependent Cold Load Pickup

Service restoration is one of the critical functions to enable the future self-healing distribution system. To restore the distribution system in a timely and reliable manner, the realistic system operating conditions need to be accurately characterized. Here, two main factors that have great impacts on distribution system restoration (DSR) in practice are investigated. First, cold load pickup (CLPU), generally caused by thermostatically controlled loads (TCLs), is a common phenomenon after an outage and shaped by the outage duration. However, the time-dependent behaviors of CLPU are rarely considered in literature. In this paper, the operating state evolution of TCLs after an outage is analyzed to characterize time-dependent CLPU. And the time-dependent CLPU is analytically embedded in DSR to accurately represent the actual behaviors of the restored loads. Second, it is difficult to predict loads that fluctuate during DSR due to the lack of real-time measurement data. Accordingly, a robust DSR based on the information gap decision theory (IGDT) is proposed to address this challenge, fully considering the uncertainty of CLPU. The proposed models are tested in IEEE 13-node and 123-node test feeders. Simulation results demonstrate that the time-dependent CLPU model and the uncertainty modeling of CLPU can accurately capture the actual behaviors of loads with TCLs after an outage, which greatly improves DSR decisions in practice.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Experimental workflow to estimate model parameters for evaluating long term viscoelastic response of CO2 storage caprocks

Understanding the time-dependent behavior of reservoir and sealing formations is critical to assessing risks associated with geological carbon storage since time-dependent deformation strongly influences mechanical responses of some rock types. Many studies have evaluated the risk of CO2 leakage and induced seismicity by assuming poroelastic rheology in sealing formations. Few have considered viscoelastic or other time-dependent responses, where the existing literature adopts 1D models to represent long-term time-dependent responses. This is primarily because to date, the general form of a reasonable 3D time-dependent model for rocks remains unclear. In this paper, we address this unclear issue by proposing a new workflow to select constitutive modeling parameters to evaluate if a 3D viscoelastic model is reasonable using several-hour-long experimental data and a power-law response to extrapolate to the decades-long time frames of interest in geologic carbon storage. To provide experimental data, we conducted multi-level loading/unloading triaxial relaxation tests with four rock types. The experimental results showed that the maximum load relaxation observed is approximately 49%, with some rock types showing as little as 1.4%. Using a simple linear viscoelastic model, parameters were chosen such that a maximum deviation of 1.5 MPa in axial stress and 7 MPa in radial stress was attained with the extrapolated 30-year data. We found that a reasonable parameter range for the normalized elastic modulus is 0.1~2 for rocks with significant time-dependent responses and 0.01~0.06 for those with small time-dependent responses. No matter how significant time-dependent responses are for rocks considered, our results showed that the relaxation time has a general range of 1~10^10 s, whose time scale can be one or two orders higher than a time frame typically envisioned for CO2 injection projects.

Stress relaxation, 3D time-dependent model, viscoe↗
DOE OSTI2026

The Role of Nuclear Data Sensitivities in Prompt α-Eigenvalue Predictions of Delayed Critical Benchmarks

Alpha (α) eigenvalues, which describe the logarithmic time derivative of the neutron population in a multiplying system, are integral to time-dependent behavior and diagnostic applications. However, uncertainties in the evaluated nuclear data can significantly impact the accuracy of transport simulations for such quantities. This work explores the use of machine learning models to predict two key outputs, α-eigenvalues and keff bias, using input features derived from α-eigenvalue sensitivities to nuclear data. The criticality safety benchmark models used in this study come from the International Handbook of Evaluated Criticality Safety Benchmark Experiments. Three models, random forest, XGBoost, and NGBoost, are trained on both energy-resolved and energy-summed α sensitivities. For the α-eigenvalue bias prediction, NGBoost achieved the highest R 2 (0.9476) using energy-resolved features, while XGBoost performed best using summed sensitivities. In contrast, when predicting the keff bias, all the models showed moderate predictive capability (best R 2 ≈ 0.72), as the mapping from the static α-sensitivities to the static keff bias was less direct. SHAP (SHapley Additive exPlanations) analysis was used to interpret the model predictions. Across both prediction tasks, the features associated with neutron capture [H-1 (n, γ)], uranium scattering reactions (such as 235 U elastic/inelastic), and actinide capture/fission reactions (such as 239 Pu and 234 U) were consistently identified as the most impactful. This highlights the key role of specific nuclear reactions and energy ranges in shaping both time-dependent and steady-state criticality behavior. These results demonstrated that α-sensitivities, despite being computed for time-dependent metrics, can provide valuable insights for predicting both α-eigenvalues and the keff bias. Moreover, machine learning models offer a promising pathway for uncovering important nuclear data dependencies and guiding future data evaluation efforts.

Nuclear data↗
DOE OSTI2021

A Time-Dependent Directional Damage Theory for Brittle Rocks Considering the Kinetics of Microcrack Growth

In this work, a novel microcrack damage theory for describing the time-dependent behavior of brittle rocks is proposed. Instead of using scalar or tensorial variables to approximate the effect of microcracks, the concept of directional damage is introduced by upscaling the directional distribution density of microcracks through the noninteracting homogenization scheme. The contribution of an individual crack on global strain is first derived from the crack-opening displacements including sliding, closure, and dilation. The model is then cast in the free energy form, and the range of parameters ensuring compliance with the second law of thermodynamics is derived rigorously. Considering that the subcritical propagation of microcracks is the dominant mechanism behind the time-dependent deformation and failure of brittle rocks, the driving force for directional damage is defined as the corresponding energy release rate, and the effect of time is introduced through a damage evolution law inspired from the kinetics of subcritical crack growth. The model is applied to simulate the behavior of basalt rock under various loading conditions. In addition to predicting the stress–strain–time response, the model offers enhanced resolution in representing the anisotropic characteristics of microcrack-induced damage in brittle rocks and their time-dependent evolutions.

58 GEOSCIENCES↗
DOE OSTI2021

Geomechanical and flow implications with continued bioconversion of coal to methane: Experiments and modeling

Microbial conversion of coal to methane is a promising technology during transition of coal-based energy from conventional coal mining to natural gas recovery from coal. Significant research advances have been made towards engineering ideal microbial communities and nutrients for bio-stimulation of coal. However, actual field applications require geomechanical and flow behavior characterization of coal during the bioconversion process as well as gas production over the life of the created “biogenic gas reservoirs”. This work presents the results of an experimental investigation to estimate gas/methane production using bioconversion of coal and analyses of variations in bulk modulus, strain and permeability. Bulk modulus of coal demonstrated time-dependent behavior with continued bioconversion of solid coal. The phenomenon was modeled using mass balancing in a closed environment and the logistic equation based biogenic gas production with time. The modeled gas production and changes in modulus of coal showed excellent agreement with the corresponding experimental results. Next, numerical simulation of biogenic conversion of coal in a constant stress in-situ condition, replicating the Huff ‘n Puff method under field conditions, was carried out. The results showed that bioconversion can lead to decrease in effective stress, increase in permeability and decrease in the modulus of coal with time. Repeated recharge of coal with nutrients and recovering the produced gas, that is, sequential cycles of Huff n’ Puff, showed further increase in permeability and decrease in coal strength, potentially leading to coal failure in-situ, further increasing the permeability, thus enhancing the prospect of field application of the technology.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2024

Non-equilibrium rate theory for polariton relaxation dynamics

We derive an analytic expression of the non-equilibrium Fermi’s golden rule (NE-FGR) expression for a Holstein–Tavis–Cumming Hamiltonian, a universal model for many molecules collectively coupled to the optical cavity. These NE-FGR expressions capture the full-time-dependent behavior of the rate constant for transitions from polariton states to dark states. The rate is shown to be reduced to the well-known frequency domain-based equilibrium Fermi’s golden rule (E-FGR) expression in the equilibrium and collective limit and is shown to retain the same scaling with the number of sites in non-equilibrium and non-collective cases. We use these NE-FGR to perform population dynamics with a time-non-local and time-local quantum master equation and obtain accurate population dynamics from the initially occupied upper or lower polariton states. Furthermore, NE-FGR significantly improves the accuracy of the population dynamics when starting from the lower polariton compared to the E-FGR theory, highlighting the importance of the non-Markovian behavior and the short-time transient behavior in the transition rate constant.

Chemical dynamics↗
DOE OSTI2025

Differentiable hybrid neural network approach for enhancing reactor dynamics simulations

Reactor dynamics simulations provide essential insights into the time-dependent behavior of nuclear reactors under various operating conditions. However, high-fidelity simulations can be computationally intensive, requiring significant computational resources. Here, to address this challenge, this study employs a differentiable hybrid model that utilizes neural networks as a corrector to enhance the performance of a low-fidelity simulation, aligning its predictions with those of a high-fidelity simulation. Low-fidelity and high-fidelity simulations were obtained by adjusting the mesh size in the System Dynamics Analysis Tool. The differentiable hybrid model was trained in two approaches: time-step-wise and sequence-wise. It was then applied to simulate various transients in a molten salt reactor. Its performance was evaluated by comparing its responses to transients against those of the high-fidelity simulation. An additional approach was performed using a data-driven model to correct the low-fidelity simulation. In comparison, the differentiable hybrid model showed significant improvements in transient prediction, effectively addressing the limitations of the low-fidelity simulations. The results highlighted the robustness of the differentiable hybrid model in both training approaches. It delivered simulations that were at least 3.8 times faster than high-fidelity models. In the time-step-wise approach, it achieved at least a 39% improvement in accuracy. In the sequence-wise approach, it showed at least an 81% accuracy improvement over the full transient. This approach offers a promising path for improving computational efficiency without compromising accuracy in nuclear reactor simulations, making it suitable for real-time digital twin applications.

42 - ENGINEERING↗
DOE OSTI2022

Micromechanics of Fracture Propagation During Multistage Stress Relaxation and Creep in Brittle Rocks

Time-dependent rock deformation caused by the initiation and growth of fractures leads to the weakening of the rock mass. Understanding the fracturing mechanisms involved in the time-dependent behavior in brittle rocks is very important and to achieve this goal, a systematic series of three types of experiments was performed on double-flawed prismatic Barre granite specimens under unconfined compression. The first series aimed to identify the failure mechanism in the short-term failure mode under monotonic loading, the, second series involved multistage relaxation (constant strain) experiments to analyze the damage at different strain levels, and the third series explored the fracture propagation under multistage creep (constant load) experiments. The spatial and temporal evolution of cracking mechanisms were evaluated using the acoustic emission (AE) and two-dimensional digital image correlation (2D-DIC) techniques to observe the whole crack growth process as well as the accumulated inelastic strain at the specified region of interest. Results suggest that in the case of multistage creep experiments, the time to failure was less compared to the multistage relaxation, when loaded above the crack damage threshold (CD) estimated from the monotonic testing. Furthermore, the frequency magnitude distribution of the AE events generated in the three loading conditions followed the Gutenberg Richter model. A relatively lower b-value was obtained for the creep experiments, indicative of high energy AE events and faster crack growth. In addition, the AE and DIC results also revealed high evolution of tensile cracks at-different stages of creep and relaxation compared to shear and mixed-mode cracks.

58 GEOSCIENCES↗
DOE OSTI2021

Viscous Behavior of Clay‐Rich Rocks and Its Role in Focused Fluid Flow

Abstract Focused fluid flow is common in sedimentary basins worldwide, where flow structures often penetrate through sandy reservoir rocks, and clay‐rich caprocks. To better understand the mechanisms forming such structures, the impacts of the viscoelastic deformation and strongly nonlinear porosity‐dependent permeability of clay‐rich materials are assessed from an experimental and numerical modeling perspective. The experimental methods to measure the poroviscoelastic and transport properties of intact and remolded shale have been developed, and the experimental data is used to constrain the numerical simulations. It is demonstrated that viscoelastic deformation combined with nonlinear porosity‐dependent permeability triggers the development of localized flow channels, often imaged as seismic chimneys. The permeability inside a channel increases by several orders of magnitude compared to the background values. In addition, the propagation time scale and the channel size strongly depend on the material properties of the fluid and the rock. The time‐dependent behavior of the clay‐rich rock may play a key role in the long‐term integrity of the subsurface formations.

58 GEOSCIENCES↗
DOE OSTI2022

Calibrating the SPECTACULAR constitutive model using legacy Sandia data for two filled epoxy systems: 828/CTBN/DEA/GMB and 828/DEA/GMB

The SPECTACULAR model is a development extension of the Simplified Potential Energy Clock (SPEC) model. Both models are nonlinear viscoelastic constitutive models used to predict a wide range of time-dependent behaviors in epoxies and other glass-forming materials. This report documents the procedures used to generate SPECTACULAR calibrations for two particulate-filled epoxy systems, 828/CTBN/DEA/GMB and 828/DEA/GMB. No previous SPECTACULAR or SPEC calibration exists for 828/CTBN/DEA/GMB, while a legacy SPEC calibration exists for 828/DEA/GMB. To generate the SPECTACULAR calibrations, a step-by-step procedure was executed to determine parameters in groups with minimal coupling between parameter groups. This procedure has often been deployed to calibrate SPEC, therefore the resulting SPECTACULAR calibration is backwards compatible with SPEC (i.e. none of the extensions specific to SPECTACULAR are used). The calibration procedure used legacy Sandia experimental data stored on the Polymer Properties Database website. The experiments used for calibration included shear master curves, isofrequency temperature sweeps under oscillatory shear, the bulk modulus at room temperature, the thermal strain during a temperature sweep, and compression through yield at multiple temperatures below the glass transition temperature. Overall, the calibrated models fit the experimental data remarkably well. However, the glassy shear modulus varies depending on the experiment used to calibrate it. For instance, the shear master curve, isofrequency temperature sweep under oscillatory shear, and the Young's modulus in glassy compression yield values for the glassy shear modulus at the reference temperature that vary by as much as 15 %. Also, for 828/CTBN/DEA/GMB, the temperature dependence of the glassy shear modulus when fit to the Young's modulus at different temperatures is approximately four times larger than when it is determined from the isofrequency temperature sweep under oscillatory shear. For 828/DEA/GMB, the temperature dependence of the shear modulus determined from the isofrequency temperature sweep under oscillatory shear accurately predicts the Young's modulus at different temperatures. When choosing values for the shear modulus, fitting the glassy compression data was prioritized. The new and legacy calibrations for 828/DEA/GMB are similar and appear to have been calibrated from the same data. However, the new calibration improves the fit to the thermal strain data. In addition to the standard calibrations, development calibrations were produced that take advantage of development features of SPECTACULAR , including an updated equilibrium Helmholtz free energy that eliminates undesirable behavior found in previous work. In addition to the previously mentioned experimental data, the development calibrations require data for the heat capacity during a stress-free temperature sweep to calibrate thermal terms.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Sample environment effects on synchrotron-measured temperature profiles in an approximant of optical floating zone crystal growth

Even though the growth of crystals using optical floating zone furnaces has had an immense scientific impact, the implementation of this method remains more of an art than a science due to the difficulty of obtaining quantitative information about the sample thermal profile during crystal growth. Building on recent work demonstrating that in situ synchrotron studies can be used to map sample rod temperatures during heating, investigations were carried out to better understand how the sample environment affects the sample temperature profile. Through a combination of experimental studies and modeling efforts, it is shown that the environment in the furnace can strongly influence the sample temperature at the lamp focus, the steepness of the vertical temperature gradient, and the timescale required for sample heating and cooling - effects which can combine to produce a strong history-dependence to sample temperature profiles. It is demonstrated that the furnace effects can be effectively captured in thermal models, allowing both the steady-state and time-dependent behavior of the sample to be accurately reproduced with predictive models, and providing a launching point for improved furnace designs that can more readily deliver desired thermal profiles.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Fluid model for the piezothermal effect

When a gas in an externally imposed potential field is compressed, temperature gradients appear. This has been called the piezothermal effect. It is possible to analytically calculate the time-dependent behavior of the piezothermal effect using a linearized fluid model. Quantitative differences between the fluid-model results and previous numerical calculations can be explained by the effects of viscosity and heat conductivity. Here, the fluid model casts the piezothermal effect as a spectrum of buoyancy oscillations, which yields new physical insights into the effect.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Non-Stationary Policy Learning for Multi-Timescale Multi-Agent Reinforcement Learning

In multi-timescale multi-agent reinforcement learning (MARL), agents interact across different timescales. In general, policies for time-dependent behaviors, such as those induced by multiple timescales, are non-stationary. Learning non-stationary policies is challenging and typically requires sophisticated or inefficient algorithms. Motivated by the prevalence of this control problem in real-world complex systems, we introduce a simple framework for learning non-stationary policies for multi-timescale MARL. Our approach uses available information about agent timescales to define and learn periodic multi-agent policies. In detail, we theoretically demonstrate that the effects of non-stationarity introduced by multiple timescales can be learned by a periodic multi-agent policy. To learn such policies, we propose a policy gradient algorithm that parameterizes the actor and critic with phase-functioned neural networks, which provide an inductive bias for periodicity. The framework's ability to effectively learn multi-timescale policies is validated on a gridworld and building energy management environment.

control↗
DOE OSTI2021

Quantification of Variation in Combustion Instability Amplitude in a Multi-Nozzle Can Combustor

In this work, we quantify the level of variation in unstable combustion oscillation amplitudes and identify the source of this variation in a multi-nozzle can combustor. At conditions where pollutant emissions are reduced, lean-premixed combustors can undergo thermoacoustic instability when pressure and heat release rate oscillations couple. A commonly used method for suppressing instability is fuel staging, which is a method where fuel is unevenly distributed between nozzles in a multi-nozzle combustor. Our work follows others who have characterized the effect of fuel staging on combustion instability and the mechanisms by which it works during both steady-state and transient operation. One of the outcomes from our previous work was that certain instability operating points display a high level of pressure oscillation amplitude variation. Instead of oscillating at a constant limit-cycle amplitude, the pressure oscillation amplitude varies significantly in time. In this work, we use the concept of permutation entropy to quantify the level of variation in the pressure fluctuation amplitude. We correlate the level of variation with a number of state variables over a range of operating conditions, 291 test cases in all. These state variables include mixture equivalence ratio; transient timescale, amplitude, and direction; hardware temperatures; gas temperatures; and thermoacoustic damping and growth rates. Significant pressure oscillation amplitude variation occurs when the thermoacoustic damping rate is low. The damping and growth rates can be low for a number of reasons, but they are highly correlated with the metal temperature of the centerbody, where the flames are anchored; lower temperatures result in lower damping rates during stable operation and lower growth rates during unstable operation. These results show the importance of the thermal boundary condition on the time-dependent behavior of the thermoacoustic instability.

Westfall, Seth↗
DOE OSTI2020

Density Tailored Capillary Discharge (Final Technical Report)

This final report describes efforts to validate a novel way to drive capillary discharges in order to achieve true matched guiding of a focused laser beam traveling along the capillary. Achieving such matched guiding is important for laser plasma accelerators, such as ones based upon laser wakefield acceleration. During this Phase II program, a computer model, which was specifically designed to predict the time-dependent behavior of the capillary discharge, was exercised to determine whether unconventional ways to drive the discharge may yield matched guiding. A custom power supply was built to drive the capillary discharge in the unconventional manner specified by the model. Experiments performed at STI Optronics seemed to support the predictions of this model; however, subsequent more accurate measurements performed at Lawrence Berkeley National Laboratory did not agree with the model predictions.

43 PARTICLE ACCELERATORS↗