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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Residual Stress Modeling and Advanced Diffraction Measurements of 347H Steel Weldments

The 347H stainless steel is a primary high-temperature material for many energy and power generation industries. Stress relief cracking (SRC) has been a particular concern in welding of this material. The residual stress induced by welding and its evolution during post-welding heat treatment (PWHT) and subsequent operating and service conditions is one of the primary factors contributing to SRC. The lifetime of welded structure components is also controlled by the precipitation kinetics that accompanies PWHT, stress relaxation process, and long-term aging and complex synergistic factors. Various theories have been proposed in the past to explain SRC. However, a widely accepted approach to predicting the entire damage evolution and the resulting performance reduction is still lacking. This study is to demonstrate a reliable solution for two critical issues that affect the predictions. First, the residual stress distribution obtained from both simulation and neutron diffraction is compared, which increases the accuracy of mechanical analysis simulation model and therefore builds a solid basis for the lifetime prediction model. Second, the generation, evolution, and annihilation of precipitates are monitored by the synchrotron diffraction experiment. Preliminary results demonstrate the critical importance of precipitation kinetics on the residual stress distribution/redistribution during heat treatments.

Yang, Yi↗
DOE OSTI2015

Modeling defect cluster evolution in irradiated structural materials: Focus on comparing to high-resolution experimental characterization studies

Exposure of metallic structural materials to irradiation environments results in significant microstructural evolution, property changes, and performance degradation, which limits the extended operation of current generation light water reactors and restricts the design of advanced fission and fusion reactors. Further, it is well recognized that these irradiation effects are a classic example of inherently multiscale phenomena and that the mix of radiation-induced features formed and the corresponding property degradation depend on a wide range of material and irradiation variables. This inherently multiscale evolution emphasizes the importance of closely integrating models with high-resolution experimental characterization of the evolving radiation-damaged microstructure. Lastly, this article provides a review of recent models of the defect microstructure evolution in irradiated body-centered cubic materials, which provide good agreement with experimental measurements, and presents some outstanding challenges, which will require coordinated high-resolution characterization and modeling to resolve.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2022

DIII-D research advancing the physics basis for optimizing the tokamak approach to fusion energy

DIII-D physics research addresses critical challenges for the operation of ITER and the next generation of fusion energy devices. This is done through a focus on innovations to provide solutions for high performance long pulse operation, coupled with fundamental plasma physics understanding and model validation, to drive scenario development by integrating high performance core and boundary plasmas. Substantial increases in off-axis current drive efficiency from an innovative top launch system for EC power, and in pressure broadening for Alfven eigenmode control from a co-/counter-I p steerable off-axis neutral beam, all improve the prospects for optimization of future long pulse/steady state high performance tokamak operation. Fundamental studies into the modes that drive the evolution of the pedestal pressure profile and electron vs ion heat flux validate predictive models of pedestal recovery after ELMs. Understanding the physics mechanisms of ELM control and density pumpout by 3D magnetic perturbation fields leads to confident predictions for ITER and future devices. Validated modeling of high-Z shattered pellet injection for disruption mitigation, runaway electron dissipation, and techniques for disruption prediction and avoidance including machine learning, give confidence in handling disruptivity for future devices. For the non-nuclear phase of ITER, two actuators are identified to lower the L–H threshold power in hydrogen plasmas. With this physics understanding and suite of capabilities, a high poloidal beta optimized-core scenario with an internal transport barrier that projects nearly to Q = 10 in ITER at ~8 MA was coupled to a detached divertor, and a near super H-mode optimized-pedestal scenario with co-I p beam injection was coupled to a radiative divertor. The hybrid core scenario was achieved directly, without the need for anomalous current diffusion, using off-axis current drive actuators. Also, a controller to assess proximity to stability limits and regulate β N in the ITER baseline scenario, based on plasma response to probing 3D fields, was demonstrated. Finally, innovative tokamak operation using a negative triangularity shape showed many attractive features for future pilot plant operation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Ethanol-fueled metal supported solid oxide fuel cells with a high entropy alloy internal reforming catalyst

High-performance metal supported solid oxide fuel cells (MS-SOFC) with an integrated high entropy alloy (HEA) internal reforming catalyst (IRC) are demonstrated for transportation applications using ethanol and methanol as fuels. Addition of the HEA IRC dramatically improves cell performance and stability when using ethanol/water blend fuel. Absence of carbon deposition predicted by thermodynamic calculations is confirmed by Raman spectroscopy analysis of posttest anodes. Optimal catalyst processing (deposition technique, loading, firing temperature) and cell operation conditions (flow rates, temperature, fuel compositions) are explored. Infiltrated HEA reforming catalyst provides a highly porous structure and low catalyst loading (6 mg cm –2 ). The designed structure and catalysts achieve small mass transport resistances in the fuel electrode (26.2 s m –1 ) and oxygen electrode (41.6 s m –1 ). The best ethanol concentration (60:40 v% ethanol: water) provides 0.83 W cm –1 at 700 °C, without carbon deposition. The ethanol-fueled MS-SOFC is operated for 500 h, including five thermal cycles. As a result, cell evolution is similar to that reported previously for hydrogen fuel; nickel aggregation and chromia deposition were the major observed changes, and carbon formation can be avoided even after long-term operation.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2025

Leveraging the Run 3 experience for the evolution of the ATLAS software-based readout towards HL-LHC

The High-Luminosity Large Hadron Collider (HL-LHC), scheduled to start operating in 2030, aims to increase the instantaneous luminosity by a factor of 10 compared to the LHC. To match this increase, the ATLAS experiment has been implementing a major upgrade program divided into two phases. The first phase (Phase-I), completed in 2022, introduced new trigger and detector systems that have been used during the Run 3 data taking period which began in July 2022. These systems have been used in conjunction with the new Data Acquisition (DAQ) Readout system, based on a software application called Software Readout Driver (SW ROD). SW ROD receives and aggregates data from the front-end electronics via the Front-End Link eXchange (FELIX) system and passes aggregated data fragments to the High-Level Trigger (HLT) system. During Run 3, SW ROD operates in parallel with the legacy Readout System (ROS) at an input rate of 100 kHz. For the Phase-II, the legacy ROS will be completely replaced with a new system based on the next generation of FELIX and an evolution of the SW ROD application called Data Handler. Data Handler has the same functional requirements as SW ROD but must be able to operate at an input rate of 1 MHz. To facilitate this evolution the SW ROD has been implemented using plugin architecture. This contribution presents the design and implementation of the SW ROD application for Run 3, along with the strategy for its evolution to the Phase-II Readout system. It discusses the lessons learned during Run 3 and describes the challenges that have been addressed to accomplish the demanding performance requirements of HL-LHC.

Kolos, Serguei [Univ. of California, Irvine, CA (U↗
DOE OSTI2021

Adaptive differentiation and rapid evolution of a soil bacterium along a climate gradient

Significance Increasing evidence suggests that evolutionary processes frequently shape ecological patterns; however, most microbiome studies thus far have focused on only the ecological responses of these communities. By using parallel field experiments and focusing in on a model soil bacterium, we showed that bacterial “species” are differentially adapted to local climates, leading to changes in their composition. Furthermore, we detected strain-level evolution, providing direct evidence that both ecological and evolutionary processes operate on annual timescales. The consideration of eco-evolutionary dynamics may therefore be important to understand the response of soil microbiomes to future environmental change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

A hybrid deep neural operator/finite element method for ice-sheet modeling

One of the most challenging and consequential problems in climate modeling is to provide probabilistic projections of sea level rise. A large part of the uncertainty of sea level projections is due to uncertainty in ice sheet dynamics. At the moment, accurate quantification of the uncertainty is hindered by the cost of ice sheet computational models. In this work we develop a hybrid approach to approximate existing ice sheet models at a fraction of their cost. Our approach consists of replacing the finite element model for the momentum equations for the ice velocity, the most expensive part of an ice sheet model, with a Deep Operator Network, while we retain a classic finite element discretization for the evolution of the ice thickness. We show that the resulting hybrid model is very accurate and it is an order of magnitude faster than the traditional finite element model. Further, a distinctive feature of the proposed model, compared to other neural network approaches, is that it can handle high-dimensional parameter spaces (parameter fields) such as the basal friction at the bed of the glacier and can therefore be used for generating samples for uncertainty quantification. Further, we study the impact of hyper-parameters, number of unknowns and correlation length of the parameter distribution on the training and accuracy of the Deep Operator Network on a synthetic ice sheet model. We then target the evolution of the Humboldt glacier in Greenland and show that our hybrid model can provide accurate statistics of the glacier mass loss and can be effectively used to accelerate the quantification of uncertainty.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2026

Engineering CoO x ‑Based Self-Supported Anodes for Pure-Water-Fed Anion-Exchange-Membrane Electrolysis

Commercial membrane electrolyzers rely on acidic fluorocarbon membranes and ionomers, requiring the use of expensive IrO x -based oxygen-evolution catalysts. Anion-exchange-membrane water electrolyzers (AEMWEs) operate in an alkaline environment, enabling the use of non-precious-metal catalysts. Here, we study and engineer CoO x -based catalyst-coated anodes deposited via hydrothermal synthesis directly onto porous transport layers both with and without thermal annealing. The self-supported, nanoneedle-structured Co3O4 anode, formed by annealing the as-synthesized cobalt carbonate hydroxide, Co­(CO3) x (OH) y , outperforms the baseline Co3O4 nanoparticle ink-based anode in pure-water-fed AEMWE due to the improved catalyst-layer continuity and thus number of electroactive Co species. The as-synthesized and unannealed Co­(CO3) x (OH) y , however, appears to undergo substantial conversion to a more-active CoO x (OH) y phase predominantly at the surface, with nominal Co3+ present and higher electrical conductivity, lowering the cell voltage to ∼200 mV at 1.0 A·cm–2 in pure-water-fed AEMWE compared to the conventional Co3O4 nanoparticle anodes. We analyze the differences in electrode electrochemical response between pure-water and KOH feed modes, finding distinct activation and degradation modes. The Co­(CO3) x (OH) y anode shows significant activation and slower degradation linked to the conversion to oxyhydroxide. We propose catalyst layer designs that promote both hydroxide and electron transport, alongside interfacial engineering strategies to obtain high performance while mitigating anode degradation.

anion-exchange-membrane water electrolysis↗
DOE OSTI2022

A reinforcement learning approach to long-horizon operations, health, and maintenance supervisory control of advanced energy systems

In this work, we develop a Reinforcement Learning (RL) approach to the supervisory control problem for advanced energy systems, such as novel nuclear reactors and other demand-driven, mission-critical, and component-health-sensitive energy plants. The inclusive problem landscape considered captures the stochastic confluence of plant performance, component health evolution, power demand from the grid, diverse maintenance actions, and operator-defined goals and constraints, all considered over meaningfully long-enough reasoning horizons. Key aspects of the proposed approach are a receding horizon control-inspired technique dictating time- or event-triggered supervisory policy (re-)constructions, as well as additional capability-enabling contributions such as timescale compression, to handle long reasoning horizons and uncertainty in parts of the problem, and practical yet demonstrably-effective handling of hybrid action spaces with continuous and discrete decision variables. The resulting algorithm consists of a simulation-based RL agent constructing stochastic supervisory control policies over nontrivial action spaces and for long horizons, applying the learned policy to the system for a much shorter interval, and perpetually repeating, to construct the next long-horizon policy. That next policy will only be applied, again, for a short interval, yet originally far-in-time events move progressively closer, their associated uncertainty decreases, and new events and aspects enter the reasoning horizon. The proposed methodology bridges fundamental receding horizon concepts with the unequivocally stronger and more scalable reasoning of contemporary RL. Numerical examples using Soft Actor–Critic Deep RL illustrate the operation and efficacy of the proposed technique for a power plant tasked with health-aware load following missions in a dynamic electricity market landscape.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Thermal Dynamics and Lithium Plating Detection in High‐Power Li‐Ion Batteries for eVTOL Applications

The rapid electrification of aerial transportation is driving the need for high‐performance Li‐ion batteries that can operate reliably under stringent thermal and safety constraints. The unique mission profile of electric Vertical Take‐off and Landing (eVTOL) aircraft necessitates a focused investigation into the thermal behavior and safety characteristics of these batteries. Here, in this study, operando isothermal microcalorimetry is employed to examine the thermal evolution of Li‐ion batteries under cycling conditions representative of eVTOL operations. These findings reveal that high‐power discharge events—such as those during take‐off and landing—shift the thermal response toward exothermic behavior, in contrast to the typically endothermic response expected under near‐equilibrium cycling conditions. Additionally, the results suggest that advanced electrolyte formulations may help suppress excess heat generation, thereby improving battery safety. Notably, the calorimetric results exhibit a distinct thermal signature associated with lithium plating, offering a potential diagnostic for detecting Li plating during eVTOL operation. Overall, this study demonstrates the utility of isothermal microcalorimetry as a valuable tool for assessing thermal risks in Li‐ion batteries for eVTOL applications, and highlights the importance of targeted design strategies to mitigate safety hazards during high‐power demand scenarios.

Li plating↗
DOE OSTI2018

The Fourteenth Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the Extended Baryon Oscillation Spectroscopic Survey and from the Second Phase of the Apache Point Observatory Galactic Evolution Experiment

The fourth generation of the Sloan Digital Sky Survey (SDSS-IV) has been in operation since July 2014. This paper describes the second data release from this phase, and the fourteenth from SDSS overall (making this, Data Release Fourteen or DR14). This release makes public data taken by SDSS-IV in its rst two years of operation (July 2014{2016). Like all previous SDSS releases, DR14 is cumulative, including the most recent reductions and calibrations of all data taken by SDSS since the rst phase began operations in 2000. New in DR14 is the rst public release of data from the extended Baryon Oscillation Sky Survey (eBOSS); the rst data from the second phase of the Apache Point Observatory (APO) Galactic Evolution Experiment (APOGEE-2), including stellar parameter estimates from an innovative data driven machine learning algorithm known as The Cannon; and almost twice as many data cubes from the Mapping Nearby Galaxies at APO (MaNGA) survey as were in the previous release (N = 2812 in total). This paper describes the location and format of the publicly available data from SDSS-IV surveys. We provide references to the important technical papers describing how these data have been taken (both targeting and observation details) and processed for scienti c use. The SDSS website (www.sdss.org) has been updated for this release, and provides links to data downloads, as well as tutorials and examples of data use. SDSS-IV is planning to continue to collect astronomical data until 2020.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

NRAP-Open-IAM Analytical Reservoir Model: Development and Testing

Geological carbon sequestration (GCS) is a key technology for reducing global carbon dioxide (CO 2 ) emissions. Over the last decade, the U.S. Department of Energy has invested in understanding the science base, developing practical implementation methods, and demonstrating secure GCS technologies to mitigate the environmental impacts associated with the atmospheric release of CO 2 . As part of the National Risk Assessment Partnership, a systems-level risk assessment tool, called the NRAP-Open-IAM, has been developed to conduct risk assessment and enable safe operations at a GCS site. The current NRAP-Open-IAM contains a simple reservoir model component that calculates the evolution of CO 2 saturation and fluid pressure in a storage reservoir during CO 2 injection operations. This report presents the development and testing of a new analytical reservoir reduced-order model (ROM), which is extended from an existing semi-analytical model for estimation of CO 2 and brine leakage along legacy wells, and enhances the capability of the NRAP-Open-IAM to simulate more types of reservoir conditions. The developed model is validated against three reference studies, and the results indicate that the new ROM predicts the behavior of the two-phase fluids (brine and injected CO 2 ) well and is applicable to different reservoir simulation boundary conditions (i.e., constant pressure boundary and infinite-acting boundary) without a priori user specification of the boundary type. Sensitivity analysis for a set of model parameters is performed using 4,000 synthetic cases prepared via a fully automated process and using machine-learning-based feature selection. The stochastic analysis identifies gravitational number (i.e., ratio of gravitational forces to viscous force) and distance between the injection well and observation location as the most impactful parameters for matching the pressure and CO 2 saturation, respectively, between the numerical simulations and the ROM. This report details the possible ROM uncertainties and serves as a guide for users to understand the use and limitations of this ROM. The code implementation of the model will be released as a module within the NRAP-Open-IAM.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Angular momentum transport within evolved low-mass stars

Asteroseismology of 1.0-2.0 M {sub ☉} red giants by the Kepler satellite has enabled the first definitive measurements of interior rotation in both first ascent red giant branch (RGB) stars and those on the helium burning clump. The inferred rotation rates are 10-30 days for the ≈0.2 M {sub ☉} He degenerate cores on the RGB and 30-100 days for the He burning core in a clump star. Using the Modules for Experiments in Stellar Evolution code, we calculate state-of-the-art stellar evolution models of low mass rotating stars from the zero-age main sequence to the cooling white dwarf (WD) stage. We include transport of angular momentum due to rotationally induced instabilities and circulations, as well as magnetic fields in radiative zones (generated by the Tayler-Spruit dynamo). We find that all models fail to predict core rotation as slow as observed on the RGB and during core He burning, implying that an unmodeled angular momentum transport process must be operating on the early RGB of low mass stars. Later evolution of the star from the He burning clump to the cooling WD phase appears to be at nearly constant core angular momentum. We also incorporate the adiabatic pulsation code, ADIPLS, to explicitly highlight this shortfall when applied to a specific Kepler asteroseismic target, KIC8366239.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Comparison of Rotor Wake Identification and Characterization Methods for the Analysis of Wake Dynamics and Evolution

Optimal wind power plant design requires understanding of wind turbine wake physics and validation of engineering wake models under wake-controlled operating conditions. In this work, we have developed and investigated several different wake identification and characterization methods for analyzing wake evolution and dynamics. The accuracy and robustness of these methods, based on Gaussian function fitting and adaptive contour identification, have been assessed by application to a large-eddy simulation data set. A new contour-based method based on downstream momentum deficit has been considered. Uncertainties arising from wake-identification errors result in characterizations of the wake expansion, recovery, and meandering motion that differ by 19% of the rotor area, 4% of the freestream, and 15% rotor diameter, respectively.

17 WIND ENERGY↗
DOE OSTI2022

Using Systems Theoretic Process Analysis and Causal Analysis to Map and Manage Organizational Information to Enable Digitalization and Information Automation

The overarching goal of this Light Water Reactor Sustainability Program–supported research and development project is to provide planning tools and comprehensive guidance to utilities considering or undertaking full nuclear plant modernization. The results of this research will provide the nuclear industry with a comprehensive and usable solution, including guidance, lessons learned, methods, and planning tools. This research is currently working to provide guidance on digitalization and information automation to enable the evolution of data to information, insight, and action—thereby allowing utilities to operate safely and cost-competitively with all other electrical generation sources. Light Water Reactor Sustainability Program researchers have also recently started investigating how human and technology integration principles, information automation, and digitalization enable data evolution. These researchers are currently in the process of validating the use of System-Theoretic Process Analysis to define high-level safety constraints in the United States Nuclear Regulatory Commission’s problem identification and resolution process (i.e., a plant compliance information gathering activity). The next step in this research, which is described in the following sections of this report, is to map out data evolution in a use case to identify inefficiencies in another aspect of plant compliance information gathering and communication activities—event investigations and root cause analyses.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Data-Driven Operator Theoretic Methods for Global Phase Space Learning

In this work, we propose to apply the recently developed Koopman operator techniques to explore the global phase space of a nonlinear system from time-series data. In particular, we address the problem of identifying various invariant subsets of a phase space from the spectral properties of the associated Koopman operator constructed from time-series data. Moreover, in the case when the system evolution is known locally in various invariant subspaces, then a phase space stitching result is proposed that can be applied to identify a global Koopman operator. A biological system, bistable toggle switch and a second-order nonlinear system example are considered to illustrate the proposed results. The construction of this global Koopman operator is very helpful in experimental works as multiple experiments can't be run at the same time starting from several initial conditions.

Nandanoori, Sai Pushpak↗
DOE OSTI2015

The impact of plasma dynamics on the self-magnetic-pinch diode impedance

In this study, the self-magnetic-pinch diode is being developed as an intense electron beam source for pulsed-power-driven x-ray radiography. The basic operation of this diode has long been understood in the context of pinched diodes, including the dynamic effect that the diode impedance decreases during the pulse due to electrode plasma formation and expansion. Experiments being conducted at Sandia National Laboratories' RITS-6 accelerator are helping to characterize these plasmas using time-resolved and time-integrated camera systems in the x-ray and visible. These diagnostics are analyzed in conjunction with particle-in-cell simulations of anode plasma formation and evolution. The results confirm the long-standing theory of critical-current operation with the addition of a time-dependent anode-cathode gap length. The results may suggest that anomalous impedance collapse is driven by increased plasma radial drift, leading to larger-than-average ion v r × B θ acceleration into the gap.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

A direct numerical simulation study of the dilution tolerance of propane combustion under spark-ignition engine conditions

Modern spark ignition internal combustion (IC) engines rely on highly diluted fuel-air mixtures to achieve high brake thermal efficiencies. To support this, new engine designs have introduced high stroke-to-bore ratios and cylinder head designs that promote high tumble flow and turbulence intensities. However, mixture dilution through exhaust gas recirculation (EGR) is limited by combustion instabilities manifested in the form of cycle-to-cycle variability. Propane has been observed to have superior EGR dilution tolerance than gasoline, which makes it a very competitive low-carbon fuel for the new IC engines without sacrificing efficiency. Two-dimensional direct numerical simulations (DNS) are performed with detailed chemistry to study and contrast the effect of turbulence intensity and dilution on propane and iso-octane premixed flames at high pressure conditions similar to those in-cylinder. A new reduced mechanism for propane consisting of 53 transported species and 17 quasi-steady state species is developed based on a previously published mechanism and used in these simulations. Three levels of turbulence intensity and two levels of exhaust gas dilution are chosen based on conditions relevant to IC engine operation. The DNS results are analyzed based on the evolution of the flame surface area and the statistics of its driving terms, which are found to be similar for both fuels when there is no dilution but considerably different under high dilution. The analysis of the DNS data provides fundamental insights into the underlying mechanisms for improved stability under dilution.

42 ENGINEERING↗