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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 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Influence of initial conditions on data-driven model identification and information entropy for ideal mhd problems

Data-driven methods of model identification are able to discern governing dynamics of a system from data. Such methods are well suited to help us learn about systems with unpredictable evolution or systems with ambiguous governing dynamics given our current understanding. Many plasma problems of interest fall into these categories as there are a wide range of models that exist, however each model is only useful in a certain regime and often limited by computational complexity. To ensure data-driven methods align with theory, they must be consistent and predictable when acting on data whose governing dynamics are known. Weak Sparse Identification of Nonlinear Dynamics (WSINDy) is a recently developed data-driven method that has shown promise in learning governing dynamics from data with high noise levels [1]. This work examines how WSINDy acts on ideal MHD test problems as the initial conditions are varied and specifies limiting requirements for successful equation identification. Furthermore, it is hard to recover the governing dynamics from data that emphasize a single dominant behavior. In these low information cases, Shannon information entropy is able to pick up on the redundancies in the data that affect recoverability.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Predicting stress response and improved protein overproduction in Bacillus subtilis

Abstract Bacillus subtilis is a well-characterized microorganism and a model for the study of Gram-positive bacteria. The bacterium can produce proteins at high densities and yields, which has made it valuable for industrial bioproduction. Like other cell factories, metabolic modeling of B. subtilis has discovered ways to optimize its metabolism toward various applications. The first genome-scale metabolic model (M-model) of B. subtilis was published more than a decade ago and has been applied extensively to understand metabolism, to predict growth phenotypes, and served as a template to reconstruct models for other Gram-positive bacteria. However, M-models are ill-suited to simulate the production and secretion of proteins as well as their proteomic response to stress. Thus, a new generation of metabolic models, known as metabolism and gene expression models (ME-models), has been initiated. Here, we describe the reconstruction and validation of a ME model of B. subtilis , i JT964-ME. This model achieved higher performance scores on the prediction of gene essentiality as compared to the M-model. We successfully validated the model by integrating physiological and omics data associated with gene expression responses to ethanol and salt stress. The model further identified the mechanism by which tryptophan synthesis is upregulated under ethanol stress. Further, we employed i JT964-ME to predict amylase production rates under two different growth conditions. We analyzed these flux distributions and identified key metabolic pathways that permitted the increase in amylase production. Models like i JT964-ME enable the study of proteomic response to stress and the illustrate the potential for optimizing protein production in bacteria.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Role of 3D neoclassical particle flux in density pump-out during ELM control by RMP in DIII-D

Application of three-dimensional (3-D) resonant magnetic perturbations, for the purpose of controlling edge localized modes (ELMs) in high confinement (H-mode) tokamak fusion operations, routinely leads to significantly reduction of the plasma density during the discharge, a phenomenon termed 'density pump-out'. Understanding the density pump-out phenomenon due to 3-D fields is a longstanding challenging issue. This work discusses a self-consistent toroidal model that allows initial value simulation of the density pump-out effect. The model successfully reproduces pump-out phenomenology in DIII-D ELM suppression experiments. The radial particle flux, associated with the 3-D neoclassical effects (the neoclassical toroidal viscosity, NTV), is discovered to play an important role in producing the observed large density pump- out. The key physics is associated with the drift kinetic Landau resonances between the toroidal precession of trapped thermal ions and electrons from one side, and the magnetic field perturbation from the other side. Such resonances, occurring near the top of the pedestal region, substantially enhances the radial particle flux associated with NTV. As a general consequence of the resonant NTV flux, larger density pump- out occurs in plasmas with lower collisionality and slower toroidal rotation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Survey of Modeling and Simulation Techniques for Advanced Manufacturing Technologies Volume I – Predicting Initial Microstructures

This report summarizes the current state of modeling and simulation methods for predicting the initial structure and properties of material in components assembled using advanced manufacturing technologies (AMTs). The report is the first volume in a two-volume series. This first volume focuses on predicting initial microstructures of AM material. The second volume discusses predicting material properties given the initial microstructure. The focus is on technologies of particular relevance to the design and manufacture of nuclear reactor components. The purpose of the report is to help develop the technical knowledge base to support regulatory decisions that will be needed to assess nuclear components manufactured with AMTs as these components are installed at nuclear power plants (NPPs). The report develops a list of AMTs of particular interest to the NRC and summarizes the key microstructural features and corresponding processing parameters relevant to each technology. Further sections describe available physically-based and data-driven prediction methods and survey widely available software tools. The report concludes with a summary of gaps that may be of particular interest to the NRC when evaluating modeling and simulation methods for AMTs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Core Model Proposal #390: Base Year Update: Initial Updates Preparing for the New Base Year

GCAM's current base year – the last historical year used for calibration – 2015, is considerably lagged compared to the present year, indicating out-of-date assumptions about near-past state of the resources, commodities, and technologies represented in GCAM. This proposal makes data and code changes to enable updating the GCAM base year easier by making the processing code more flexible and robust.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Chemistry and Reactivity of Oxide Films on Aluminum Clad Test Reactor Fuels - 19294

This paper describes recent work performed to assess the degradation of aluminum spent nuclear fuel (ASNF) as part of an ongoing Department of Energy project. As part of a multi-task effort, this paper specifically describes efforts initiated in 2018 to better understand chemical phenomena and degradation in ASNF). In this paper experimental and modeling activities are described. The modeling effort presents initial results in two areas potentially influencing stability. Using an established electrolyte model based on experimental data, the solubility of aluminum as a function of temperature and pH was examined. This work describes interesting results for the minimum pH providing relevant data that was not available from the literature. It was found that solubility increases with temperature and that the minimum pH shifts to low pH with increase in temperature. The second area involves understanding the metallurgy of aluminum alloys during fuel drying. In this study, the temperature range from 100 deg. C to 300 deg. C was analyzed. Thermodynamic models predict that AA1100 will not experience significant phase changes while the more highly alloyed AA6061 and AA5052 may experience significant phase changes. These thermodynamic measurements establish a potential for phase changes during drying, however they do not predict the kinetics for such processes. Phase 1 of the experimental program has initiated and results are forthcoming. The test program will examine aluminum oxidation under anticipated dry storage conditions (temperature and humidity). Examination of localized corrosion due to tight crevices and galvanic contact (with stainless steel) will be included. Finally, water deliquescence will be assessed using thermogravimetric analysis with dynamic humidity profiles. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

Chemistry and Reactivity of Oxide Films on Aluminum Clad Test Reactor Fuels

This paper describes recent work performed to assess the degradation of aluminum spent nuclear fuel (ASNF) as part of an ongoing Department of Energy project. As part of a multi-task effort, this paper specifically describes efforts initiated in 2018 to better understand chemical phenomena and degradation in ASNF). In this paper experimental and modeling activities are described. The modeling effort presents initial results in two areas potentially influencing stability. Using an established electrolyte model based on experimental data, the solubility of aluminum as a function of temperature and pH was examined. This work describes interesting results for the minimum pH providing relevant data that was not available from the literature. It was found that solubility increases with temperature and that the minimum pH shifts to low pH with increase in temperature. The second area involves understanding the metallurgy of aluminum alloys during fuel drying. In this study, the temperature range from 100°C to 300°C was analyzed. Thermodynamic models predict that AA1100 will not experience significant phase changes while the more highly alloyed AA6061 and AA5052 may experience significant phase changes. These thermodynamic measurements establish a potential for phase changes during drying, however they do not predict the kinetics for such processes. Phase 1 of the experimental program has initiated and results are forthcoming. The test program will examine aluminum oxidation under anticipated dry storage conditions (temperature and humidity). Examination of localized corrosion due to tight crevices and galvanic contact (with stainless steel) will be included. Finally, water deliquescence will be assessed using thermogravimetric analysis with dynamic humidity profiles.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Toward particle accelerator machine state embeddings as a modality for large language models

Understanding and diagnosing the state of a particle accelerator requires navigating high-dimensional control system data, often involving hundreds of interdependent parameters. We propose a novel multimodal embedding framework that jointly learns representations of machine states from both numerical control system readouts and natural language descriptions. This enables the translation of complex machine conditions into human-readable summaries while maintaining fidelity to the underlying physical system. The obtained embeddings are subsequently adapted to an open-weights large language model via cross-attention conditioning. We demonstrate a first implementation trained on European XFEL machine state data. This work covers the embedding model architecture, training methodology, and presents initial examples demonstrating the model's capabilities in action. Due to the general concept of machine state, the model can be easily adapted to other facilities and control system environments.

Accelerator Physics↗
DOE OSTI2021

PMIP: Looking back to its first phase

The Paleoclimate Modelling Intercomparison Project celebrates its 30th anniversary in 2021. The first phase initiated systematic model-model and model-data comparisons for the Last Glacial Maximum and Mid-Holocene. Here, we describe the historical context of PMIP, the experiment design, and the project’s early impacts.

58 GEOSCIENCES↗
DOE OSTI2023

Stellar Neutrino Emission across the Mass–Metallicity Plane

We explore neutrino emission from nonrotating, single-star models across six initial metallicities and 70 initial masses from the zero-age main sequence to the final fate. Overall, across the mass spectrum, we find metal-poor stellar models tend to have denser, hotter, and more massive cores with lower envelope opacities, larger surface luminosities, and larger effective temperatures than their metal-rich counterparts. Across the mass–metallicity plane we identify the sequence (initial CNO → 14 N → 22 Ne → 25 Mg → 26 Al → 26 Mg → 30 P → 30 Si) as making primary contributions to the neutrino luminosity at different phases of evolution. For the low-mass models we find neutrino emission from the nitrogen flash and thermal pulse phases of evolution depend strongly on the initial metallicity. For the high-mass models, neutrino emission at He-core ignition and He-shell burning depends strongly on the initial metallicity. Antineutrino emission during C, Ne, and O burning shows a strong metallicity dependence with 22 Ne(α, n) 25 Mg providing much of the neutron excess available for inverse-β decays. We integrate the stellar tracks over an initial mass function and time to investigate the neutrino emission from a simple stellar population. We find average neutrino emission from simple stellar populations to be 0.5–1.2 MeV electron neutrinos. Lower metallicity stellar populations produce slightly larger neutrino luminosities and average β decay energies. This study can provide targets for neutrino detectors from individual stars and stellar populations. We provide convenient fitting formulae and open access to the photon and neutrino tracks for more sophisticated population synthesis models.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Dislocation Density-Based Model for Flow Behavior of a Near-α Titanium Alloy Considering Effects of Initial Lamellar Thickness

A dislocation density-based constitutive model that considered the effects of initial lamellar thickness was proposed to predict the flow behavior of a near-α high-temperature Ti-5.4Al-3.7Sn-3.3Zr-0.5Mo-0.4Si alloy. The evolution equations of dislocation density were improved by introducing the influence of the dynamic globularization of lamellar microstructure with different initial thicknesses. The evolution equations and Hall-Petch behavior were coupled into the constitutive model, which was composed of athermal and thermal stresses. According to the established constitutive equations, the variation and contributions of corresponding stress components were analyzed. The calculated dislocation densities were compared with the experimental values obtained by electron backscattered diffraction data to verify the model. Moreover, the flow stresses of the studied alloy with different initial lamellar microstructures under various deformation conditions were predicted. Good agreements between the predicted and experimental results were obtained. Additionally, steady-state flow behavior was further analyzed and the relationship between the calculated steady-state flow stress and the equiaxed α-phase size was quantitatively obtained. The results indicated the validity of the proposed constitutive model for predicting the flow behavior of the alloy with different initial lamellar microstructures over a range of deformation temperatures and strain rates.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Mathematical Modeling on the Influence of Casting Parameters on Initial Solidification at the Meniscus of Slab Continuous Casting

In the current study, the two-dimensional mold model was applied to investigate the influence of different casting parameters on the initial solidification at the meniscus of the continuous casting mold. The profile of the meniscus and the slag rim, and the heat flux on the hot face of the copper plate, were compared with different locations of the mold and different casting parameters. The depth of the oscillation marks and solidified meniscus through simulation was measured with different casting parameters. With the mold oscillating downward from the peak to the valley, the maximum heat flux on the hot face of the copper plate near the meniscus increased from 4.3 to 5.5 MW/m{sup 2}, the thickness of the slag rim decreased from 4.7 to 4.2 mm, and the height of the curved meniscus also decreased. With the increase of casting speed from 1.2 to 1.45 m/min, the maximum speed of the upper backflow increased from 0.6 to 0.8 m/s, and the lowest location of the meniscus at approximately 310 mm from the copper plate decreased from 22 to 12 mm below the meniscus near the nozzle, where the slag entrapment easily occurred. With the increase of the casting speed, casting superheat, and oscillation frequency, and the decrease of the water flow rate in the mold and oscillation amplitude, the thickness of the slag rim decreased. With the increase of casting speed and superheat, and the decrease of the water flow rate in the mold, oscillation frequency, and oscillation amplitude, the depth of the solidified meniscus decreased. The regression equation was fitted to estimate the depth of hooks at the subsurface of slabs.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Quantitative Prediction of Perovskite Stability Using Accelerated Testing and Machine Learning

PV technologies based on hybrid perovskites offer the potential for reducing solar cell costs, but they are particularly vulnerable to degradation by environmental factors such as moisture, oxygen, and illumination. Commercialization will require not only stable materials and device architectures but also accelerated testing protocols and models that can predict degradation from the accelerated testing data. Here, we report results from in situ photoluminescence (PL) and photoconductivity (PC) measurements during perovskite degradation with simultaneous optical transmittance (Tr) measurements or reflected dark field (DF) imaging. From PL, PC, Tr, and DF, we determine (respectively) the steady-state quasi-Fermi level splitting, the mean effective carrier diffusion length, the extent of conversion of perovskite to higher bandgap degradation products, and the extent of scattering from domains with different orientation or composition, all as a function of time during degradation. Simultaneous measurement of PL-PC-Tr or PL-PC-DF on perovskite absorbers in an environmental chamber over a wide range of humidity, oxygen, temperature, and illumination levels yields a rich data set. We use machine learning to develop a model that accurately predicts (within 10%) the time for the diffusion length to decrease to 85% of its initial value. The model takes the environmental conditions and the first few measurements from the PL-PC-Tr or PL-PC-DF experiment as input. Thus, the model provides a framework to interpret the results of accelerated testing of absorber materials. One of the dominant features in the model of degradation for CH 3 NH 3 PbI 3 is the initial rate at which transmittance increase. For devices with opaque contacts, the pixel-averaged rate of change of the intensity in dark-field images can be used in place of transmittance. Results are also presented on full PV devices with in-situ current-voltage (JV) measurements. Here, the data from simultaneous PL-DF-JV under environmental stresses reveal intimate connection between degradation and shunts and provide a framework to extend accelerated testing to devices. Further, the presentation reveals underlying universal behavior in degradation pathways over a broad range of environmental stresses and perovskite compositions.

14 SOLAR ENERGY↗
DOE OSTI2019

Hybrid model with dynamical sources for heavy-ion collisions at BES energies

We develop a (3+1)-dimensional hybrid evolution model for heavy-ion collisions with dynamical sources for the energy-momentum tensor and baryon current. During an initial pre-equilibrium stage based on UrQMD, the four-momenta and baryon numbers carried by secondary particles created within UrQMD are fed continuously, after a short thermalization time, into a (3+1)-dimensional viscous hydrodynamic evolution module including baryon transport. The sensitivity of the initial conditions to model parameters and the effect of baryon diffusion on the hydrodynamic evolution are studied.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗