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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

Microwave radiative transfer through horizontally inhomogeneous precipitating clouds

Recent advances in cloud microphysical models have led to realistic three-dimensional distributions of cloud constituents. Radiative transfer schemes can make use of this detailed knowledge in order to study the effects of horizontal as well as vertical inhomogeneities within clouds. This study looks specifically at the differences between three-dimensional radiative transfer results and those obtained by plane parallel, independent pixel approximations in the microwave spectrum. A three-dimensional discrete ordinates method as well as a backward Monte Carlo method are used to calculate realistic radiances emerging from the cloud. Analyses between these models and independent pixel approximations reveal that plane parallel approximations introduce two distinct types of errors. The first error is physical in nature and is related to the fact that plane parallel approximations do not allow energy to leak out of dense areas into surrouding areas. In general, it was found that these errors are quite small for emission-dominated frequencies (37 GHz and lower) and that physical errors are highly pronounced only at scattering frequencies (85 GHz) where large deviations and biases up to 8 K averaged over the entire cloud were found. The second error is more geometric in nature and is related to the fact that plane parallel approximations cannot accommodate physical boundaries in the horizontal dimension for off-nadir viewing angles. The geometric errors were comparable in magnitude for all frequencies. Their magnitude, however, depends on a number of factors including the scheme used to deal with the edge, the nature of the surface, and the viewing angle.

Roberti, Laura↗
DOE OSTI2022

Preparing for the next pandemic via transfer learning from existing diseases with hierarchical multi-modal BERT: a study on COVID-19 outcome prediction

Abstract Developing prediction models for emerging infectious diseases from relatively small numbers of cases is a critical need for improving pandemic preparedness. Using COVID-19 as an exemplar, we propose a transfer learning methodology for developing predictive models from multi-modal electronic healthcare records by leveraging information from more prevalent diseases with shared clinical characteristics. Our novel hierarchical, multi-modal model ( $${\textsc {TransMED}}$$ T R A N S MED ) integrates baseline risk factors from the natural language processing of clinical notes at admission, time-series measurements of biomarkers obtained from laboratory tests, and discrete diagnostic, procedure and drug codes. We demonstrate the alignment of $${\textsc {TransMED}}$$ T R A N S MED ’s predictions with well-established clinical knowledge about COVID-19 through univariate and multivariate risk factor driven sub-cohort analysis. $${\textsc {TransMED}}$$ T R A N S MED ’s superior performance over state-of-the-art methods shows that leveraging patient data across modalities and transferring prior knowledge from similar disorders is critical for accurate prediction of patient outcomes, and this approach may serve as an important tool in the early response to future pandemics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Aspects of Assessment of Packages with Wood Filled Impact Limiters during Fire Tests - 17191

Packages for the transport of radioactive material are often equipped with impact limiters consisting of wood, encapsulated by steel sheets. These impact limiters shall ensure that the transport casks meet the mechanical and thermal IAEA regulatory test requirements. According to the accident conditions of transport it is mandatory to expose the specimens to a cumulative effect by mechanical and thermal impacts. The mechanical tests consist of a free drop from 9 m onto a flat unyielding target and a 1 m drop onto a puncture bar. After damage caused by mechanical test sequences the package has to withstand a severe fire scenario. Corresponding to the IAEA advisory material it is required that the impact attitudes for the 9 m drop test and for the puncture test have to be such as to produce maximum damage, taking into account the thermal test. Moreover, any damage, which would give rise to increased radiation or loss of containment or affect the confinement system after the thermal test, should be considered. During and following the thermal test, the specimen shall not be artificially cooled and any combustion of materials of the package shall be permitted to proceed naturally. Different works from the French Institute for Radiological Protection and Nuclear Safety (IRSN) and BAM show that additional energy supply from a pre-damaged impact limiter to the cask could occur. This effect should be considered within the safety assessment of the containment. Thermal effects at the closure system of the cask, which might result in an elevated activity release, have to be excluded. BAM conducted small scale tests with wood filled metal buckets showing continuing combustion processes during the cooling down phase. These test results are presented. As not much is known about smouldering processes in wood filled impact limiters, it is highly complex to define pre-damage of impact limiters, which are conservative, regarding the maximum damaging energy flow from the impact limiter to the containment system. More research has to be done to develop models to examine the effects of smouldering impact limiters on the containment of packages for the transport of radioactive material. Aspects of assessment and its difficulties are shown. BAM as a competent authority for the approval of transport casks for radioactive material in Germany operates the test facilities to examine the issue of mechanical damage, combustion and heat transfer for such kind of package systems. For this purpose, the knowledge from real drop tests with casks of a mass partly over 100 tons was transferred to a test application. A thermal test will take place with a wood filled test specimen with a diameter of about 2.3 meters. The aim is to understand the phenomena of smouldering under the consideration of relevant regulatory boundary conditions. The process of smouldering is described with regard to the requirements in the thermal assessment of safety of packages for the transport of radioactive material. Requirements concerning the pre-damage of packages for the maximum damage of impact limiters are discussed. Parameters influencing the smouldering process are identified. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

Tracking Electron Uptake from a Cathode into Shewanella Cells: Implications for Energy Acquisition from Solid-Substrate Electron Donors

While typically investigated as a microorganism capable of extracellular electron transfer to minerals or anodes, Shewanella oneidensis MR-1 can also facilitate electron flow from a cathode to terminal electron acceptors, such as fumarate or oxygen, thereby providing a model system for a process that has significant environmental and technological implications. This work demonstrates that cathodic electrons enter the electron transport chain of S. oneidensis when oxygen is used as the terminal electron acceptor. The effect of electron transport chain inhibitors suggested that a proton gradient is generated during cathode oxidation, consistent with the higher cellular ATP levels measured in cathode-respiring cells than in controls. Cathode oxidation also correlated with an increase in the cellular redox (NADH/FMNH 2 ) pool determined with a bioluminescence assay, a proton uncoupler, and a mutant of proton-pumping NADH oxidase complex I. This work suggested that the generation of NADH/FMNH 2 under cathodic conditions was linked to reverse electron flow mediated by complex I. A decrease in cathodic electron uptake was observed in various mutant strains, including those lacking the extracellular electron transfer components necessary for anodic-current generation. While no cell growth was observed under these conditions, here we show that cathode oxidation is linked to cellular energy acquisition, resulting in a quantifiable reduction in the cellular decay rate. This work highlights a potential mechanism for cell survival and/or persistence on cathodes, which might extend to environments where growth and division are severely limited. The majority of our knowledge of the physiology of extracellular electron transfer derives from studies of electrons moving to the exterior of the cell. The physiological mechanisms and/or consequences of the reverse processes are largely uncharacterized. This report demonstrates that when coupled to oxygen reduction, electrode oxidation can result in cellular energy acquisition. This respiratory process has potentially important implications for how microorganisms persist in energy-limited environments, such as reduced sediments under changing redox conditions. From an applied perspective, this work has important implications for microbially catalyzed processes on electrodes, particularly with regard to understanding models of cellular conversion of electrons from cathodes to microbially synthesized products.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1990

Mechanical system diagnostics using vibration testing techniques

The 'Cepstrum' technique of vibration-path identification allows the recovery of the transfer function of a system with little knowledge as to its excitation force, by means of a mathematical manipulation of the system output in conjunction with subtraction of part of the output and suitable signal processing. An experimental program has been conducted to evaluate the usefulness of this technique in the cases of simple, cantilever-beam and free-free plate structures as well as in that of a complex mechanical system. On the basis of the transfer functions thus recovered, it was possible to evaluate the shifts in the resonance frequencies of a structure due to the presence of defects.

Mcleod, Catherine D.↗
DOE OSTI2019

Integration of Local Knowledge is a Key for the Remediation Success of Legacy Uranium Mine Sites - 19564

A key to success, during all aspects of the remediation process on legacy uranium sites, and easily transferable between countries and projects, is the integration of local knowledge. However, before this knowledge can be integrated, local trust and project understanding must be developed. Local trust and project understanding can only be developed through a principle-centred approach to a shared project vision, two-way communication of knowledge, alignment of project goals, and understanding the local needs early in the remediation process. Once public confidence is obtained, local trust and project understanding must be maintained throughout the entirety of the remediation process. Project understanding is an ongoing endeavor that needs continuous communication and varied methods to succeed. During the management of assessment, remediation, and post remediation monitoring on the Saskatchewan Research Council's CLEANS project (remediation of 37 legacy uranium mine sites in Northern Saskatchewan, Canada), integration of local knowledge has been an instrumental tool attributing to success. During site assessment, integration of local knowledge has included the development and implementation of land use surveys to determine realistic travel and occupancy on and adjacent to these legacy sites, and site specific traditional knowledge and land use studies that have contributed to the development of a detailed knowledge of local land use, resource utilization, country food intake, and human history of the sites. The local knowledge gained during the assessment process is invaluable as it provides information required to support remediation planning, such as: valued ecosystem components, human trophic utilization, length of site occupancy, cultural value assessment, and future land use considerations. During remediation planning, local and traditional knowledge can also be incorporated through determination of plant species suitability for revegetation, development and selection of remediation options, and setting realistic sustainable development targets for local project inclusion. During site remediation operations, local involvement can be utilized through direct labour and equipment, cultural resource monitoring (i.e. archaeological and heritage protection), local logistics and historic information transfer, and stakeholder communications and engagement support. Post remediation, local involvement is an efficient mechanism for long-term monitoring, and care and maintenance activities. Although there may be differences between countries, regions and sites, the remediation process on legacy uranium mines can universally be more successful through the integration of local knowledge; while developing rights/stakeholder engagement and capacity building. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1992

NASA/DOD Aerospace Knowledge Diffusion Research Project. Paper 23: Information technology and aerospace knowledge diffusion: Exploring the intermediary-end user interface in a policy framework

Federal attempts to stimulate technological innovation have been unsuccessful because of the application of an inappropriate policy framework that lacks conceptual and empirical knowledge of the process of technological innovation and fails to acknowledge the relationship between knowled reproduction, transfer, and use as equally important components of the process of knowledge diffusion. It is argued that the potential contributions of high-speed computing and networking systems will be diminished unless empirically derived knowledge about the information-seeking behavior of the members of the social system is incorporated into a new policy framework. Findings from the NASA/DoD Aerospace Knowledge Diffusion Research Project are presented in support of this assertion.

Pinelli, Thomas E.↗
DOE OSTI2024

Investigating explainable transfer learning for battery lifetime prediction under state transitions

Battery lifetime prediction at early cycles is crucial for researchers and manufacturers to examine product quality and promote technology development. Machine learning has been widely utilized to construct data-driven solutions for high-accuracy predictions. However, the internal mechanisms of batteries are sensitive to many factors, such as charging/discharging protocols, manufacturing/storage conditions, and usage patterns. These factors will induce state transitions, thereby decreasing the prediction accuracy of data-driven approaches. Transfer learning is a promising technique that overcomes this difficulty and achieves accurate predictions by jointly utilizing information from various sources. Hence, we develop two transfer learning methods, Bayesian Model Fusion and Weighted Orthogonal Matching Pursuit, to strategically combine prior knowledge with limited information from the target dataset to achieve superior prediction performance. From our results, our transfer learning methods reduce root-mean-squared error by 41% through adapting to the target domain. Furthermore, the transfer learning strategies identify the variations of impactful features across different sets of batteries and therefore disentangle the battery degradation mechanisms and the root cause of state transitions from the perspective of data mining. These findings suggest that the transfer learning strategies proposed in our work are capable of acquiring knowledge across multiple data sources for solving specialized issues.

25 ENERGY STORAGE↗
DOE OSTI2025

Impacts of Biomass Feedstock Pre-Processing on Heat and Mass Transfer During Pyrolysis Using X-Ray Computed Tomography and Multiscale Modeling

Knowledge of the transport properties of biomass particles such as porosity, tortuosity, and permeability is paramount for high-fidelity modeling of biomass pyrolysis due to the heat and mass transfer limitations imposed by particle microstructure. X-ray computed tomography (XCT) is a non-destructive imaging method that enables full 3D reconstructions of the biomass particle microstructure with high resolution, permitting direct calculation of porosity, tortuosity, and permeability from real particle geometries. In this study, XCT imaging revealed the 3D microstructures of particles and chars from pyrolytic conversion of cylindrically cut or milled/pelletized loblolly pine samples. The porosity, tortuosity, and permeability were calculated directly from the XCT geometries via open-source microstructural analysis tool MATBOX+TauFactor (https://github.com/NREL/MATBOX_Microstructure_analysis_toolbox) and computational fluid dynamics (CFD) simulations using our solver, Mesoflow (https://github.com/NREL/mesoflow). These properties were used in a reactor scale model developed in COMSOL of the single particle reactor at NREL to investigate the impact of feedstock pre-processing on biomass conversion during pyrolysis with rigorous experimental validation.

biomass↗
NASA NTRSDate not supplied

Harnessing Artificial Intelligence for Medical Diagnosis and Treatment During Space Exploration Missions

From May 8th to June 9th, 2023, I had the opportunity to participate in an experiential learning experience at Johnson Space Center in Houston, TX with Exploration Medical Capability (ExMC), an element of the NASA Human Research Program. During this research experience, I was not only able to work on the above titled research project, but also gain an immense exposure to the field of aerospace medicine, make numerous connections within the field, tour NASA facilities, as well as travel to the Aerospace Medical Association Annual Conference (AsMA) in New Orleans. To briefly introduce my project, it is well understood that the medical capabilities available to crew medical officers (CMOs) on the International Space Station will be different than the capabilities available and needed during deep space exploration missions to the Moon, Mars, and beyond. Ground support is particularly limited due to distance, communication delays (or lack of communication), and lack of resupply. Therefore, to support medical care by CMOs on these missions, robust clinical decision support systems (CDSSs) must be designed. The recent publication and public launch of generative artificial intelligence (AI) tools based upon large language models (LLM) such as ChatGPT provides the opportunity to create a smart assistant for onboard triage, diagnosis, and treatment of medical conditions. Ultimately, the overall purpose of the project was to research what AI tools currently exist or are in development, and to see how they might be implemented onboard during exploration class spaceflights of the future. The ExMC element is actively developing several tools to be used in preparation for and during deep space exploration missions. One of those tools, known as IMPACT, is a probabilistic risk assessment model which can be used to propose a desired medical system (based on mass and volume) and suggest the clinical outcomes likely to occur for a design reference mission (DRM). The group recently presented the IMPACT model and a DRM of interest titled “Modified Long Duration Lunar Orbital and Lunar Surface” (mLDLOLS) at the recent AsMA conference. The mLDLOLS mock mission is a 9 month and 6-day deep space exploration mission consisting of time in Moon’s orbit (3 months on the Gateway space station), on the lunar surface (3 months within habitat), and another 3 months on Gateway before return to Earth. For this DRM, IMPACT ultimately outlined a preferred medical system that was then associated with medical conditions considered to be most likely based on frequency, most likely to cause astronaut task time loss (TTL), most likely to cause return to definitive care (RTDC), and most likely cause loss of crew life (LOCL). IMPACT also highlighted the medical capabilities/skills that would be required to care for those medical conditions, such as performing a history of present illness or musculoskeletal exam with ultrasound. The primary objective of the project was to perform a survey of the AI tools and systems applicable to the conditions outlined for the proposed mLDLOLS mission. Using PubMed (including most relevant MeSH terms) and Google Scholar, we then created a robust annotated bibliography organized by condition. The 56-page and over 500 reference annotated bibliography was subsequently used to create a review outline that would become the basis for drafting of a future publication. For the review outline, we took those medical conditions researched within the annotated bibliography (condition-based approach) and deployed a systems-based approach, combining those medical conditions and related tools into ten categories. These categories included general/all-purpose CDSSs, tools to diagnose or manage respiratory, dermatologic, neurologic, auditory and vestibular, ophthalmic, musculoskeletal, infection-associated, and gynecologic conditions, as well as tools that could be deployed in the setting of trauma/emergency. With the completion of the 30-page outline, we then began drafting the review paper. To conclude the research experience, I presented the findings from our survey to the ExMC Clinical and Science team. With these objectives, I ultimately learned about the number of AI tools that exist today to assist medical professionals with the triage, diagnosis, and management of several medical conditions. These tools can span from chatbot assistants to help triage knee pain to vision transformer models that can identify ophthalmic conditions based on ocular surface images captured with a cell phone. We also highlighted the current gaps that exist in the literature alongside the advancements that are needed to make the desired CDSS for deep space exploration missions. With this experience, I certainly confirmed an existing career goal and identified several additional skills needed to become an aerospace medical doctor including knowledge of critical care in an extreme medicine setting, aerospace engineering and human integration systems, artificial intelligence, machine learning, and risk models. I also identified numerous transferable skills for this career goal including the basic knowledge of medicine (MD), deployment of the scientific method for critical thought about new scientific questions (PhD), review of published literature, including creating an annotated bibliography (PhD), as well as detailed scientific writing (PhD). The results of my research will likely guide the design of an all-encompassing onboard medical assistant for use during deep space exploration missions of the future. I plan on sharing the outcomes from this experience with my peers at a student seminar in the Fall semester on August 30th. During the seminar, I will detail the project, my experience at NASA and AsMA, as well as offer best practice guidelines for students entertaining similar experiences or careers. In conclusion, I would like to thank the WVU School of Medicine, Research and Graduate Education office, as well as NASA ExMC for the unwavering support of this life-changing experience.

Ryan A. Lacinski↗
DOE OSTI2022

Simultaneous measurement of visible energy and momentum transfer in anti-electron neutrino interactions on hydrocarbon

Precise knowledge of neutrino interaction cross sections is required for current and future accelerator-based neutrino oscillation experiments. Precision neutrino oscillation measurements require inference of the neutrino energy and flavor from the visible particles in the neutrino interaction in the detector. This inference is different for the true neutrino flavors measured, electron and muon neutrinos, and can be studied by observation of neutrino interactions in an experiment’s near detector. However, anti-electron neutrinos make up only a few percent of an anti-muon neutrino beam and pose a challenge in making cross section measurements and predictions. The reported measurements were made using data from MINERvA, a neutrino-nucleus scattering experiment, with an anti-neutrino beam configuration of mean energy ~ 6 GeV. This thesis provides two double-differential cross sections of anti-electron neutrino inclusive charged-current reactions using the kinematics of visible energy, three-momentum transfer, and transverse momentum. The analysis is carried out at low three-momentum transfer, making it sensitive to regions with multi-nucleon effects.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Characterization of ferredoxins involved in electron transfer pathways for nitrogen fixation implicates differences in electronic structure in tuning 2[4Fe 4S] Fd activity

Ferredoxins (Fds) are small proteins which shuttle electrons to pathways like biological nitrogen fixation. Physical properties tune the reactivity of Fds with different pathways, but knowledge on how these properties can be manipulated to engineer new electron transfer pathways is lacking. Recently, we showed that an evolved strain of Rhodopseudomonas palustris uses a new electron transfer pathway for nitrogen fixation. This pathway involves a variant of the primary Fd of nitrogen fixation in R. palustris, Fer1, in which threonine at position 11 is substituted for isoleucine (Fer1 T11I ). To understand why this substitution in Fer1 enables more efficient electron transfer, we used in vivo and in vitro methods to characterize Fer1 and Fer1 T11I . Electrochemical characterization revealed both Fer1 and Fer1 T11I have similar redox transitions (–480 mV and – 550 mV), indicating the reduction potential was unaffected despite the proximity of T11 to an iron-sulfur (Fe—S) cluster of Fer1. Additionally, disruption of hydrogen bonding around an Fe—S cluster in Fer1 by substituting threonine with alanine (T11A) or valine (T11V) did not increase nitrogenase activity, indicating that disruption of hydrogen bonding does not explain the difference in activity observed for Fer1 T11I . Electron paramagnetic resonance spectroscopy studies revealed key differences in the electronic structure of Fer1 and Fer1 T11I , which indicate changes to the high spin states and/or spin-spin coupling between the Fe—S clusters of Fer1. Finally, our data implicates these electronic structure differences in facilitating electron flow and sets a foundation for further investigations to understand the connection between these properties and intermolecular electron transfer.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Thermal Safety Analyses for the Production of Plutonium-238 at the High Flux Isotope Reactor

There has been a considerable effort over the previous few years to demonstrate and optimize the production of plutonium-238 ( 238 Pu) at the High Flux Isotope Reactor (HFIR). This effort has involved resources from multiple divisions and facilities at the Oak Ridge National Laboratory (ORNL) to demonstrate the fabrication, irradiation, and chemical processing of targets containing neptunium-237 ( 237 Np) dioxide (NpO 2 )/aluminum (Al) cermet pellets. A critical preliminary step to irradiation at the HFIR is to demonstrate the safety of the target under irradiation via documented experiment safety analyses. The steady-state thermal safety analyses of the target are simulated in a finite element model with the COMSOL Multiphysics code that determines, among other crucial parameters, the limiting maximum temperature in the target. Safety analysis efforts for this model discussed in the present report include: (1) initial modeling of single and reduced-length pellet capsules in order to generate an experimental knowledge base that incorporate initial non-linear contact heat transfer and fission gas equations, (2) modeling efforts for prototypical designs of partially loaded and fully loaded targets using limited available knowledge of fabrication and irradiation characteristics, and (3) the most recent and comprehensive modeling effort of a fully coupled thermo-mechanical approach over the entire fully loaded target domain incorporating burn-up dependent irradiation behavior and measured target and pellet properties, hereafter referred to as the production model. These models are used to conservatively determine several important steady-state parameters including target stresses and temperatures, the limiting condition of which is the maximum temperature with respect to the melting point. The single pellet model results provide a basis for the safety of the irradiations, followed by parametric analyses in the initial prototypical designs that were necessary due to the limiting fabrication and irradiation data available. The calculated parameters in the final production target model are the most accurate and comprehensive, while still conservative. Over 210 permutations in irradiation time and position were evaluated, and are supported by the most recent inputs and highest fidelity methodology. The results of these analyses show that the models presented in this report provide a robust and reliable basis for previous, current and future experiment safety analyses. In addition, they reveal an evolving knowledge of the steady-state behavior of the NpO 2 /Al pellets under irradiation for a variety of target encapsulations and potential conditions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1993

NASA/DOD Aerospace Knowledge Diffusion Research Project. Paper 35: The US government technical report and aerospace knowledge diffusion: Results of an on-going investigation

The U.S. government technical report is a primary means by which the results of federally funded research and development (R&D) are transferred to the U.S. aerospace industry. However, little is known about this information product in terms of its actual use, importance, and value in the transfer of federally funded (U.S.) R&D. To help establish a body of knowledge, the U.S. government technical report is being investigated as part of the NASA/DOD Aerospace Knowledge Diffusion Research Project. In this paper, we summarize the literature on technical reports and provide a model that depicts the transfer of federally funded aerospace R&D via the U.S. government technical report. We present results from two surveys (one of five studies) of our investigation of aerospace knowledge diffusion vis-a-vis the U.S. government technical report and close with a brief overview of on-going research into the use of the U.S. government technical report as a rhetorical device for transferring federally funded aerospace R&D.

Pinelli, Thomas E.↗
DOE OSTI2025

Impact of Domain Knowledge on the Property Prediction of Specialized Machine Learning Models

Developing transferable machine learning models is trending in data-driven materials research. However, how to apply such models to a specific research domain remains unclear. Here, in this work, we choose high-entropy materials as a platform with a specialized data set containing 145,323 DFT-relaxed materials. This data set is used to explore the role of domain-specific knowledge in training effective models. Our tests with three representative graph neural network architectures indicate the model complexity has much smaller influence on performance than the data itself. Specifically, the consideration of low-energy atomic ordering, structures with diverse elemental coverage, and high-order interactions significantly influences the model performance. We also find that domain knowledge-driven sampling can greatly enhance unsupervised learning techniques. This research highlights that developing specialized data sets is more beneficial than further complicating deep learning architectures. Additionally, physics-inspired sampling algorithms are crucially needed for better machine learning models for a specific materials research domain.

36 MATERIALS SCIENCE↗
DOE OSTI2019

The Importance of Viscous and Interfacial Forces in the Hydrodynamics of the Top-Submerged-Lance Furnace

The purpose of this work is to focus on the hydrodynamics of a Top-Submerged-Lance (TSL) smelting furnace, understanding how liquid properties and operational parameters act on key factors of a TSL process, such as splashing, mixing, mass transfer area, and bubble development. A deep knowledge of all those aspects is needed since they all influence the smelting reaction rates; hence the efficiency of the reactor. The characterization and scaling of the TSL gas injection are commonly based on the modified Froude number, the ratio of dynamic and gravitational forces. Detailed literature research reveals a potential weakness of this approach, since it does not consider the effects of viscosity and surface tension. To investigate this question an extensive parametric study was performed applying computational fluid dynamics to cold and non-reactive flows, which provided a broad overview of the physics of the flow. The analysis was performed on fluid dynamic properties (liquid density, liquid viscosity, surface tension) and operational variables (gas volume flow, lance immersion depth). The coupled Level Set—Volume of Fluid model, available in the commercial solver ANSYS Fluent{sup ®}, was used to resolve the gas–liquid interface in the multiphase flow. The results of the work underscore the significance of the viscous and interfacial forces for gas injection in smelting slags, confirming the incompleteness of applying only the Froude number to describe such flows.

36 MATERIALS SCIENCE↗
DOE OSTI2026

A Field Guide to Corralling the Chaos: A Conceptual Framework for Using Models to Guide Opportunistic Field Studies of Natural Disturbances

Watersheds regulate biogeochemical processes and provide ecosystem services to human societies, but disturbances can fundamentally alter these processes across space and time. Determining when and where to sample to capture disturbance impacts in watersheds remains a central challenge. Manipulation studies and long-term monitoring are often constrained by scope, and opportunistic studies often lack pre-disturbance data needed to statistically determine disturbance impacts. We identify a persistent knowledge gap: the absence of a clear, transferable framework to guide opportunistic disturbance research where pre-disturbance data collection is not a feasible option. To address this gap, we present a conceptual framework that intentionally integrates modeling and empirical observation in an iterative, stepwise model–experiment workflow. We demonstrate its application through two contrasting case studies: wildfire impacts on headwater streams using a pre-disturbance preparedness approach, and saltwater flooding impacts on coastal forests using an ‘ex-post-facto’ approach. From these applications, we assess strengths, limitations, and the critical role of team science for transferability across disturbance types and study designs. Broadly, this framework offers a scalable path towards more rigorous, timely, and actionable disturbance science that can inform watershed management, hazard risk reduction, and ecosystem resilience.

Coastal Biogeochemistry↗
DOE OSTI2021

Watch and learn—a generalized approach for transferrable learning in deep neural networks via physical principles

Transfer learning refers to the use of knowledge gained while solving a machine learning task and applying it to the solution of a closely related problem. Such an approach has enabled scientific breakthroughs in computer vision and natural language processing where the weights learned in state-of-the-art models can be used to initialize models for other tasks which dramatically improve their performance and save computational time. Here we demonstrate an unsupervised learning approach augmented with basic physical principles that achieves fully transferrable learning for problems in statistical physics across different physical regimes. By coupling a sequence model based on a recurrent neural network to an extensive deep neural network, we are able to learn the equilibrium probability distributions and inter-particle interaction models of classical statistical mechanical systems. Our approach, distribution-consistent learning, DCL, is a general strategy that works for a variety of canonical statistical mechanical models (Ising and Potts) as well as disordered interaction potentials. Using data collected from a single set of observation conditions, DCL successfully extrapolates across all temperatures, thermodynamic phases, and can be applied to different length-scales. This constitutes a fully transferrable physics-based learning in a generalizable approach.

97 MATHEMATICS AND COMPUTING↗