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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Adversarial classification via distributional robustness with Wasserstein ambiguity

Abstract We study a model for adversarial classification based on distributionally robust chance constraints. We show that under Wasserstein ambiguity, the model aims to minimize the conditional value-at-risk of the distance to misclassification, and we explore links to adversarial classification models proposed earlier and to maximum-margin classifiers. We also provide a reformulation of the distributionally robust model for linear classification, and show it is equivalent to minimizing a regularized ramp loss objective. Numerical experiments show that, despite the nonconvexity of this formulation, standard descent methods appear to converge to the global minimizer for this problem. Inspired by this observation, we show that, for a certain class of distributions, the only stationary point of the regularized ramp loss minimization problem is the global minimizer.

Ho-Nguyen, Nam (ORCID:0000000344647730)↗
DOE OSTI2022

Multiscale simulation of integrated energy system and electricity market interactions

Accelerating the deep decarbonization of the world's electric grids requires the coordination of complex energy systems and infrastructures across timescales from seconds to decades. Here, we present a new multiscale simulation framework that integrates process- and grid-centric modeling paradigms to better design, operate, and control integrated energy systems (IESs), which combine multiple technologies, in wholesale energy markets. Traditionally, IESs are analyzed with a process-centric paradigm such as levelized cost of electricity (LCOE) or annualized net revenue, ignoring important interactions with electricity markets. This framework explicitly models the complex interactions between an IES's bidding, scheduling, and control decisions and the energy market's clearing and settlement processes, while incorporating operational uncertainties. Through two case studies, we show the importance of understanding and quantifying complex resource-grid interactions. In case study 1, we demonstrate that optimized bidding from one resource shifts the profit distribution for all energy systems in the market. This result suggests new and more flexible IES technologies can disrupt the economics of all market participants, possibly leading to accelerated retirements of less flexible resources. Interestingly, the optimized bidding has little impact on grid-level aggregate statistics, such as total generation costs and renewable penetration rate. While aggregate modeling strategies may remain valid under some IES adoption scenarios for analysis focused on regional outcomes, direct comparisons of IES technologies at specific locations without considering these interactions may lead to misleading or incorrect conclusions. In case study 2, we consider the design and flexible operation of IESs that hybridize conventional generators with energy storage. Through a sensitivity analysis, we find that as the size of the storage system increases, the total number of start-ups for coal- and natural gas-based IESs reduced by 25% and 33.6%, and the total thermal generator ramping (i.e., mileage) reduced by 86.5% and 62.5%, respectively. This shows the primary benefit of storage may not be reduced operational costs (which do not change significantly) but fewer start-ups and less ramping, which may greatly simplify the design, operation, and control of carbon capture systems. The new modeling and optimization capabilities from this work enable the coupling of rigorous, dynamic process models with grid-level production cost models to quantitatively identify the nuanced interdependencies across these vast timescales that must be addressed to realize clean, safe, and secure energy production. Moreover, the proposed general multiscale simulation framework is applicable to all IES technologies and can be easily extended to consider other energy carriers (e.g., hydrogen, ammonia) and energy infrastructures (e.g., natural gas pipelines).

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

A bilevel multistage stochastic self-scheduling model with indivisibilities for trading in the continuous intraday electricity market

In this paper, we study the profit maximization problem of a virtual power plant trading in the continuous intraday electricity market. Our virtual power plant model is compatible with renewable, and thermal assets, covering a range of virtual power plants currently participating in energy markets. We model the trading problem as a bilevel multistage stochastic program. The upper level of the problem accounts for the profit maximization of the virtual power plant with explicit modeling of the technical constraints of the operational status of the thermal power plant including minimum start-up and shut-down times, ramp-up and ramp-down rates, and minimum generation level. The upper level also decides which continuous and indivisible (fill-or-kill) orders are submitted to the market. The lower-level problem accounts for the clearing of the continuous intraday market, i.e., matching of buy and sell orders. Because of the presence of fill-or-kill orders, the lower-level problem is mixed-integer, which prevents its direct conversion to a single-level problem using duality. In order to solve this challenging problem, we develop a convex-hull extended formulation for the lower-level problem, apply duality theory to obtain a single-level stochastic equivalent formulation, and employ McCormick envelopes to turn the problem into a multistage stochastic mixed-integer linear problem, which we solve using the stochastic dual dynamic integer programming algorithm. We conduct numerical experiments and analyze the optimal trading behavior of a virtual power plant trading in an ideal continuous market without arbitrage.

Bilevel multistage stochastic programming problem↗
DOE OSTI2025

Plasma shape and position control development for NSTX-U using the GSEvolve plasma simulator

NSTX-U discharges have been reproduced using the GSEvolve plasma simulator in order to improve their control and reduce oscillations during the plasma current (Ip) ramp-up phase, and with the ultimate goal of enabling reliable H-mode access with a double-null shape at high elongation, low internal inductance, and high plasma performance. The control objective is to eliminate undesired oscillations in the plasma shape and vertical position that start when the plasma diverts during the Ip ramp-up phase, and that happened recurrently during the first NSTX-U experimental campaign. Model-based control solutions have been developed, including alternative H-mode access recipes and a Multi-Input Multi-Output (MIMO) decoupling controller. These solutions have demonstrated their capability to reduce or eliminate the aforementioned oscillations in GSEvolve simulations, enabling reproducible H-mode access. The results of this work aim to inform NSTX-U experimental operations on potential control developments to maximize its scientific output, and highlight the powerful capabilities of high-fidelity control-simulation frameworks like GSEvolve.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Thermal mechanical assessment of a SiC-SiC-composite clad fuel pin concept in a light water reactor environment

Accident Tolerant Fuels (ATFs) are designed to increase coping time following an accident scenario while preserving or improving current steady state reactor operational performance. A potential ATF concept is SiC-SiC composite claddings. Fuel performance simulations were conducted on a SiC-SiC based cladding concept utilizing a multilayered approach for improved performance. This cladding concept referred to as the Duplex concept is a duplex structure composed of a monolithic SiC layer placed on the outside of a SiC-SiC composite. A liquid metal is added to fuel-cladding gap for improved heat dissipation from the fuel. The monolithic SiC layer is used to improve the coolant corrosion characteristics and protect the SiC-SiC composite layer from exposure to the coolant. The fuel performance code BISON was used to conduct fuel performance simulations on the cladding concepts. Comparisons are made with a current prototypic fuel rod design (UO 2 fuel enclosed in Zircaloy-4 cladding). Representative steady-state cases were considered for normal power and two cycle power histories. Additionally, a PCI ramp case was simulated to analyze potential anticipated operational occurrences. Transient response during a Loss of Coolant Accident and a Reactivity Initiated Accident were also simulated. This computational study demonstrated that for normal operating conditions, the SiC concept cladding performed as well as the baseline for the standard power cases evaluated. The ramping evaluations indicate potential fracturing of the SiC-SiC composite of the composite cladding compared to the Zircaloy-4 cladding due to the temperature gradient and the subsequent differential thermal conductivity degradation and swelling across the composite thickness. In conclusion, the rod fails early at low enthalpy for RIA but survives a LOCA with minimal material loss due to high temperature steam corrosion.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Enhancement of Uranium Ionization Efficiencies Using Zn-MOF-74 Derived Nanoporous Ion Emitters for Thermal Ionization Mass Spectrometry

The recent introduction of nano-porous ion emitters (nano-PIEs) formed from metal organic frameworks (MOFs) has demonstrated the potential to enhance sensitivity for thermal ionization mass spectrometry (TIMS). Nano-PIEs take advantage of the parent MOF’s chemical and structural tunability to form scaffolds for ion emitters. A study by Barpaga et al. 2023 on MOF-74 as the parent material found that with high volatility metals in their framework uranium sample utilization efficiency (SUE) increases by up to nine-fold (e.g., Zn-MOF-74) compared to that of the analyte on a bare filament (~0.05%). Here, in this study, we investigate the performance of Zn-MOF-74 to maximize uranium efficiencies at the trace level (= 10 -12 g) by altering the parent MOF morphology and chemistry (i.e., MOF crystal sizes and thermal degradation) and optimizing its integration with TIMS (i.e., MOF mass on a filament and ramp conditions). We observed improvement in SUE up to 20 times (≤1.0%) that of a bare filament load when nano-PIEs derived from nanocrystals of Zn-MOF-74 were heated under a specific current ramp condition. This demonstrates that rates of nano-PIE structural collapse during TIMS analysis and the subsequently formed nanomaterials (and their features) can be tuned to control analyte ionization.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Dynamic Modeling and Simulation of a Subcritical Coal-Fired Power Plant under Load-Following Conditions

Dynamic models for power plants that capture realistic general process trends and effects of manipulated variables are needed to improve load-following, while minimizing carbon footprint. In this work, a dynamic modeling approach and simulation results for subcritical coal-fired power plant components are presented. These encompass simulation of the dynamics in the fireside, including the effects of fuel, air combustion, and the dynamics of the entire waterside and power generation sections. This model development enables the simulation and analysis of the important short and long-time scale dynamics of components such as heaters, evaporative loop, and power generation units. Furthermore, additional variables in the power generation section are introduced to improve model accuracy, extending the prediction capability of subcritical power plant models and opening new opportunities for research in operator training, optimization, and advanced model-based controller design that are based on these models. The change in process gain for different ramp rates associated with disturbance signals that affect process variables is also explored and a correlation developed. This provides opportunities to study disturbance rejection control implementation and adaptation for scenarios with such variations in ramp rates. The prediction capabilities of selected components are compared to data available in literature, with the obtained root mean squared error ranges that reflect the model performance and quality of predictions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Effect of Radical Initiators on Polypropylene Thermal Deconstruction

A new route for polypropylene (PP) deconstruction through radical pathways based on thermodynamic and kinetic considerations has been investigated. Radical polypropylene (PP) deconstruction, activated through small quantities of initiators, can enable the deconstruction of waste POs into unsaturated products. We found that stirring was detrimental to the β-scission extent because it accelerates radical termination reactions through mixing. The best results were achieved by using a semibatch process that included mechanical mixing during the temperature ramp, static heating of the polymer/initiator mixture at the final temperature, and volatile product removal with N 2 . Dicumyl peroxide and alkylated dicumene initiators produced similar liquid and solid products after a 30 min thermal treatment. Terminal alkenes were formed in the liquid products of reactions at 375 and 400 °C, with about 5% of the protons in the liquid product ascribed to terminal alkenes. Yields of liquid products increased with temperature, reaching 60% w/w at 400 °C; at the same time, yields of solid products decreased with temperature to 16% w/w at 400 °C. Although radical initiators decrease PP molecular weight during the temperature ramp, at 400 °C, initiators only marginally increased the liquid product fraction compared to control experiments. Finally, the terminal double bonds in the liquid product mixture (C8–C36) provide multiple pathways for upgrading to surfactants, plasticizers, lube oils, and other valuable products.

liquids↗
DOE OSTI2025

Machine-Learned Force Field for Molecular Dynamics Simulations of Nonequilibrium Ammonia Synthesis on Iron Catalysts

Ammonia (NH 3 ) is one of the most important industrial chemicals. The conventional NH 3 synthesis method-the Haber–Bosch process-converts atmospheric nitrogen (N 2 ) into NH 3 using H 2 with an iron (Fe) catalyst. However, this process requires high pressures (100–200 atm) and temperatures (700–800 K) near thermal equilibrium. Recently, Fe-based nanocatalysts have been reported to produce promising NH 3 yields under atmospheric pressures and temperature-modulated nonequilibrium conditions. Understanding the mechanism of nonequilibrium catalysis with programmed temperature variation could help to optimize this fully electrified and less energy-intensive process. Although reactive molecular dynamics (RMD) simulations can be a useful tool to model nonequilibrium catalytic processes, they require the development of accurate force fields (i.e., interatomic potentials). Here, we present a machine-learned (ML) force field within the Deep Potential MD (DPMD) framework, trained using periodic density functional theory (DFT) calculations, to model NH 3 synthesis on Fe catalysts with various surface adsorbates such as *N, *H, *N 2 , *H 2 , *NH, *NH 2 , and *NH 3 . Here, we generated the DFT data from static models of elementary reactions on the most stable (110) surface of body-centered cubic Fe, which then were augmented by data from constant number of particles–volume–temperature (NVT) DFT-MD trajectories at various temperatures. Finally, we utilized the fully optimized ML force field to investigate reaction dynamics at an Fe(110) surface at linearly increasing temperatures using NVT-DPMD simulations. Our simulations indicate that pulsed temperature ramping could prove favorable for NH3 synthesis. For example, we conducted ramping under multiple sets of conditions: (i) from 900 to 1200 K over periods of 0.1–0.3 ns for Fe surfaces precovered with N or NH along with H; and (ii) from 300 to 600 K over 0.1–0.3 ns for Fe surfaces precovered with NH 3 . While our simulations so far are limited to short time scales (very rapid heating), these observations shed light on the mechanism of the high NH 3 synthesis rate achieved in a novel temperature-modulated nonequilibrium catalytic reactor using pulsed heating and cooling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Transient behavior of oxide fuels with controlled microstructure and Cr2O3 additive

Abstract Microstructure and Cr 2 O 3 doping profoundly impact the thermal-mechanical properties and fracture of oxides fuels. It is a challenge to study the transient behavior of nuclear fuels under loss-of-coolant-event (LOCA). In this study, the crack behavior of UO 2 pellets with controlled grain structure and Cr 2 O 3 doping was tested with rapid power ramping (300−900 °C per min) mimicking a prototypical LOCA heating profile. Dense micron-sized UO 2 pellets display well-maintained integrity without cracking with the ramping up to 1500 °C at a heating rate of 8 °C per second. Fracture occurs in both pure and Cr 2 O 3 -doped dense nano-sized UO 2 pellets. The Cr 2 O 3 doped oxide fuel pellet with a larger grain size (~ 22.2 μm) displays the best performance under LOCA testing due to its highest thermal conductivity under high temperature. FEA calculations suggest a temperature gradient across the fuel pellet during transient testing, resulting in residual stress and cracking, which can be correlated with their thermal-mechanical properties.

Zhao, Dong (ORCID:0000000191377257)↗
DOE OSTI2025

ORBITaL-Net: A labeled training library for large-scale building feature extraction

Over the course of several years, nearly 1.5 million building outlines have been created from approximately 128,000 training tiles covering roughly 7,000 km 2 of very high-resolution multispectral overhead imagery, primarily dated between 2010 and 2020. This dataset, dubbed the Oak Ridge Building Image and TrAining Label Net (ORBITaL-Net), is designed for machine learning applications and is global in scope, with samples drawn from 72 countries across North America, South America, Africa, Europe, and Asia. ORBITaL-Net captures a great diversity in geographic setting, structural characteristics, land use (urban and rural), terrain, and imagery conditions. While the labeled building outlines are themselves valuable, the dataset’s true strength lies in the pairing of these labels with corresponding reference imagery, which is being released for open source use. Similar to SpaceNet and Replicable AI For Microplanning (ramp), this building outline dataset will allow the larger computer vision community from academia, government, and industry the opportunity to develop robust, scalable, and generalizable geospatial machine learning techniques. Unlike SpaceNet and ramp, which offer high resolution labels and imagery primarily for large urban cities, ORBITaL-Net is not focused on training samples from heavily populated areas but instead aims to capture the innate variability of conditions present in both the physical environment and imagery collections.

Geography↗
DOE OSTI2024

Modelling and analysis of nuclear reactor system coupled with a liquid metal battery

Traditionally, nuclear power plants in the U.S. provide baseload power to the power grid because they have less flexibility for ramping their output power than natural gas peaking plants. However, achieving climate goals to reduce the consumption of fossil‐based natural gas places pressure on nuclear power plants and other power generators to ramp up their power output to balance grid generation with demand. This paper presents the modelling and performance analysis of a nuclear reactor system (NRS) coupled to a liquid‐metal battery (LMB) to improve its dynamic response and enable its black start capability. The NRS and LMB thermal behaviour are modelled in Dymola, while the electrical dynamics of the LMB and power grid are modelled in RTDS‐RSCAD. Both simulation platforms are coupled and share their thermal and electrical data using a Transmission Control Protocol/Internet Protocol (TCP/IP) communication protocol. The dynamic performance of the NRS‐LMB integration is tested on the IEEE 9 bus, which demonstrates its ability to respond and provide frequency and voltage regulation. The black start capability of the NRS‐LMB is also evaluated by simulating a grid outage and using the LMB to supply the auxiliary loads required to bring the NRS back online as soon as possible. The results show that coupling an NRS to an LMB improves the system dynamic performance and enables it to black start after being disconnected from the grid for several days.

25 ENERGY STORAGE↗
DOE OSTI2020

Machine learning control for disruption and tearing mode avoidance

In this work, real-time feedback control based on machine learning algorithms (MLA) was successfully developed and tested on DIII-D plasmas to avoid tearing modes and disruptions while maximizing the plasma performance, which is measured by normalized plasma beta. Control uses MLAs that were trained with ensemble learning methods using only the data available to the real-time Plasma Control System (PCS) from several thousand DIII-D discharges. A `tearability' metric that quantifies the likelihood of the onset of 2/1 tearing modes (TM) in a given time window, and a 'disruptivity' metric that quantifies the likelihood of the onset of plasma disruptions were first tested o -line then implemented on the PCS. A real-time control system based on these MLAs was successfully tested on DIII-D discharges, using feedback algorithms to maximize β Ν while avoiding tearing modes and to dynamically adjust ramp down to avoid high-current disruptions in ramp down.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

A simple model of a strong shock driven by a spherical or cylindrical piston

A simple model of piston-driven spherical and cylindrical shocks is suggested. The model is based on a consistent use of two factors: (a) an almost uniform pressure across the shocked layer and, (b) continuous geometrical stretching of the surface elements of the expanding piston. It turns out that for a uniform pre-shock medium the gas between the piston and the shock behaves essentially as an incompressible fluid. An algebraic equation for the shock vs piston position is obtained. Detailed evaluation of the accuracy of the proposed solution shows that its accuracy is a few percent for the adiabatic index γ = 5/3 (as in ideal plasma). A closed-form solution describing enhancement of a weak ambient magnetic field by the shock is presented. The proposed model of piston-driven shocks goes beyond the classical self-similar solutions in that it: (1) naturally covers an early, non-asymptotic dynamics and its transition to asymptotic regime; (2) allows for smooth radial density variation of an ambient gas of the form of bumps, dimples or ramps between two constant values; and (3) allows for smooth temporal variation of piston velocity of the form of bumps, dimples, or ramps. Furthermore, this simple and versatile model provides some new insights into a classical hydrodynamical problem.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Study of dielectric breakdown in liquid xenon with XeBrA: The xenon breakdown apparatus

Maintaining the electric fields necessary for the current generation of noble liquid time projection chambers (TPCs), with drift lengths exceeding 1 m, requires a large negative voltage applied to their cathode. Delivering such high voltage is associated with an elevated risk of electrostatic discharge and electroluminescence, which would be detrimental to the performance of the experiment. The Xenon Breakdown Apparatus (XeBrA) is a 5-l, high voltage test chamber built to investigate the contributing factors to electrical breakdown in noble liquids. Here, in this work, we present the main findings after conducting scans over stressed electrode areas, surface finish, pressure, and high voltage ramp speed in the medium of liquid xenon. Area scaling and surface finish were observed to be the dominant factors affecting breakdown, whereas no significant changes were observed with varying pressure or ramp speed. A general rise in both the anode current and photon rate was observed in the last 30 s, leading up to a breakdown, with a marked increase in the last couple of seconds. In addition, the position of breakdowns was reconstructed with a system of high-speed cameras and a moderate correlation with the Fowler–Nordheim field emission model was found. Tentative evidence for bubble nucleation being the originating mechanism of breakdown in the liquid was also observed. We deem the results presented in this work to be of particular interest for the design of future, large TPCs, and practical recommendations are provided.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Quantifying uncertainty in analysis of shockless dynamic compression experiments on platinum. I. Inverse Lagrangian analysis

Absolute measurements of solid-material compressibility by magnetically driven shockless dynamic compression experiments to multi-megabar pressures have the potential to greatly improve the accuracy and precision of pressure calibration standards for use in diamond anvil cell experiments. Here, to this end, we apply characteristics-based inverse Lagrangian analysis (ILA) to 11 sets of ramp-compression data on pure platinum (Pt) metal and then reduce the resulting weighted-mean stress–strain curve to the principal isentrope and room-temperature isotherm using simple models for yield stress and Grüneisen parameter. We introduce several improvements to methods for ILA and quasi-isentrope reduction, the latter including calculation of corrections in wave speed instead of stress and pressure to render results largely independent of initial yield stress while enforcing thermodynamic consistency near zero pressure. More importantly, we quantify in detail the propagation of experimental uncertainty through ILA and model uncertainty through quasi-isentrope reduction, considering all potential sources of error except the electrode and window material models used in ILA. Compared to previous approaches, we find larger uncertainty in longitudinal stress. Monte Carlo analysis demonstrates that uncertainty in the yield-stress model constitutes by far the largest contribution to uncertainty in quasi-isentrope reduction corrections. We present a new room-temperature isotherm for Pt up to 444 GPa, with 1-sigma uncertainty at that pressure of just under ±1.2%; the latter is about a factor of three smaller than uncertainty previously reported for multi-megabar ramp-compression experiments on Pt. The result is well represented by a Vinet-form compression curve with (isothermal) bulk modulus K 0 = 270.3 ± 3.8 GPa, pressure derivative K$^{'}_{0}$= 5.66 ± 0.10, and correlation coefficient $R_{K_{0},K^{'}_{0}}$= –0.843.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Temporal pre-pulse shaping in dual pulse laser produced plasma for the optimization of the EUV source in tin microdroplet system

Dual-laser beams interacting with small droplets of liquid tin are currently the most efficient systems for producing the 13.5 nm EUV photon radiation source required for the next generation microchips. Usually, EUV light is produced during the second main-pulse stage, while the pre-pulse (PP) is used for target preparation, i.e., droplet preheating, vaporization, and target deformation. However, the PP laser energy can be utilized more efficiently if the EUV producing plasma is being developed during the PP stage as well. In this work, we study the ways of optimization of the PP laser temporal shape to achieve conditions for maximum EUV output during the pre-pulse. The size of the deformed droplet is kept optimized for the following main laser pulse. Our simulations showed a significant increase in the EUV output at the pre-pulse stage when a ramping profile is used for the laser temporal shape. Using the ramped square pre-pulse produces 24% gain in the EUV output in comparison with the standard Gaussian temporal profile (i.e., regular Nd:YAG shape) for the same energy of the laser pulse.

36 MATERIALS SCIENCE↗