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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Confinement and manipulation of electron plasmas in a multicell trap

Plasma dynamics and transport are studied experimentally in a multicell Penning-Malmberg trap. The goal is to develop methods for accumulation and long-term confinement of larger numbers of charged particles (e.g., positrons) than is presently possible. In this scheme, the particles constitute non-neutral plasmas which are confined separately in a parallel array of storage cells. Experiments are presented in which pure electron plasmas are transferred from a large-diameter “master cell” trapping region into four smaller, parallel “storage cells,” three of which are offset from the magnetic symmetry axis. The physics of the transfer process, as well as the confinement properties of plasmas in the storage cells, is discussed. We show that plasmas can be transferred into the storage cells and held there for up to a day or more using the rotating wall technique, provided that the plasma radius is sufficiently small compared to that of the cell wall. Experiments regarding the confinement of plasmas with kilovolt space charge are discussed. Recommendations are provided for future efforts with high-capacity multicell traps.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Tearing Stable Stationary ITER Baseline Operation in DIII-D

We present a tearing stable, stationary and reproducible operating solution for DIII-D plasmas characterized by the ITER Baseline Scenario normalized parameter set and shape. In these plasmas low differential rotation (Δf1,2) between the core and edge is identified as the single root cause of the onset of the primary limiting instability, the 2,1 Neoclassical Tearing Mode (NTM), while a group of other examined parameters have a much weaker impact on the stability. Explanation is offered by drift kinetic simulations, which show a six-fold reduction in the NTM onset threshold due to diminished stabilizing ion polarization currents when the seed island drift frequency ceases in the local plasma frame. Based on the experimental observation and the explanation provided by the theory, a new method is developed to sustain Δf1,2 by modifying the edge neoclassical potential through neutral gas fueling. This method enables stationary ITER baseline operation free of disruptive 2,1 tearing modes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Probe microscopy is all you need *

We pose that microscopy offers an ideal real-world experimental environment for the development and deployment of active Bayesian and reinforcement learning methods. Indeed, the tremendous progress achieved by machine learning (ML) and artificial intelligence over the last decade has been largely achieved via the utilization of static data sets, from the paradigmatic MNIST to the bespoke corpora of text and image data used to train large models such as GPT3, DALL·E and others. However, it is now recognized that continuous, minute improvements to state-of-the-art do not necessarily translate to advances in real-world applications. We argue that a promising pathway for the development of ML methods is via the route of domain-specific deployable algorithms in areas such as electron and scanning probe microscopy and chemical imaging. This will benefit both fundamental physical studies and serve as a test bed for more complex autonomous systems such as robotics and manufacturing. Favorable environment characteristics of scanning and electron microscopy include low risk, extensive availability of domain-specific priors and rewards, relatively small effects of exogenous variables, and often the presence of both upstream first principles as well as downstream learnable physical models for both statics and dynamics. Recent developments in programmable interfaces, edge computing, and access to application programming interfaces (APIs) facilitating microscope control, all render the deployment of ML codes on operational microscopes straightforward. We discuss these considerations and hope that these arguments will lead to create novel set of development targets for the ML community by accelerating both real world ML applications and scientific progress.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

WfCommons: Data Collection and Runtime Experiments using Multiple Workflow Systems

Scientific workflows have become ubiquitous across scientific fields, and their execution methods and systems continue to be the subject of research and development. Most experimental evaluations of these workflows rely on workflow instances, which can be either real-world or synthetic, to ensure relevance to current application domains or explore hypothetical/future scenarios. The WfCommons project addresses this need by providing data and tools to support such evaluations. In this paper, we present an overview of WfCommons and describe two recent developments. Firstly, we introduce a workflow execution "tracer" for Nextflow, which significantly enhances the set of real-world instances available in WfCommons. Secondly, we describe a workflow instance "translator" that enables the execution of any real-world or synthetic WfCommons workflow instance using Dask. Our contributions aim to provide researchers and practitioners with more comprehensive resources for evaluating scientific workflows.

Casanova, Henri↗
DOE OSTI2018

Theory and Computation for Mesoscopic Materials Modeling

Accurate and efficient computational modeling of material behavior is essential to the DOE's mission of advancing the development of devices and components needed for power generation and storage. One of the outstanding challenges in atomistic simulation of condensed systems, such as solids, liquids, and glasses, is access to experimentally meaningful length and time scales. The project developed and improved several solution methods to overcome these challenges: diffusive molecular dynamics, adaptive kinetic Monte Carlo, coarse-graining of transition state theory, finite temperature coarse-graining methods for crystalline defects, and optimization-based atomistic-to-continuum coupling methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Polarized Radar for Detection and Automatic Non-Visual Assessment of Unmanned Aerial Systems

This Laboratory Directed Research and Development (LDRD) effort performed fundamental Research and Development (R&D) to develop a robust radar processing algorithm capable of assessing the difference between an Unmanned Aerial System (UAS) and a biological target such as a bird, based on mathematics applied to the polarized radar returns of the target object, alone. The current threats of using such a UAS as a delivery platform for a host of destructive components is a major concern for the protection of various assets. Most recently, on 14th Sept. 2019, dozens of suicide or kamikaze drones (UAV-X) coordinated an attack on two Saudi oil facilities that demonstrated the potential to disrupt global oil supplies. While radar-based UAS detection systems can detect UAS at ranges greater than 1-km, the issues of excessive Nuisance/False Alarm Rates (NAR/FAR) from natural sources (birds in particular) has not been sufficiently addressed. In this effort we describe and utilize the Adaptive Polarization Difference Imaging-based (APDI) algorithms for the detection and automatic non-visual assessment of Unmanned Aerial System applications. Originally developed for optical imaging and sensing of polarization information in nature, the algorithms developed here are modified to serve for the target detection purposes in counter-UAS (cUAS) environments. We exploit the polarization statistics of the observing scene for detection and identification of changes within the scene and assess from these changes for UAS/bird classifications. Several cases are considered from independent data sources, including numerically generated data, anechoic chamber data as well as experimental radar data, to show the applicability of the techniques developed here. The methods developed in this effort are designed to be used in cUAS setups but have shown promise for a multitude of other radar-based classification uses as well.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Characterization and Modeling of Deformation Induced Damage in Titanium Alloys

Over the lifetime of their DOE support, and specifically during the past funding cycle, the PIs have primarily focused on ambient temperature studies of the mechanisms of heterogeneous deformation and shear transfer at GBs. The PIs have developed and applied a broad array of experimental approaches complemented by advanced computational methods and simulations to enable new understanding of GB shear transfer, and a new approach for modeling this behavior at the mechanistic level has been established. The PIs have examined how slip behavior differs on the surface and interior of polycrystals using a variety of approaches. Some of the associated data has been used to generate 3-D models of experimentally-characterized microstructures that both support interpretation of deformation mechanisms as well as reveal where modeling needs to be improved to more closely agree with what is experimentally observed. The PIs progress in constitutive modeling of crystal plasticity has introduced explicit GB resistance to shear that depends on the mutual geometry of active slip systems. This past work places the PIs in a good position to take on the challenges associated with mechanistically understanding the interplay between GBS and slip interactions.

42 ENGINEERING↗
DOE OSTI2016

Nanoscale effects in the characterization of viscoelastic materials with atomic force microscopy: Coupling of a quasi-three-dimensional standard linear solid model with in-plane surface interactions

Significant progress has been accomplished in the development of experimental contact-mode and dynamic-mode atomic force microscopy (AFM) methods designed to measure surface material properties. However, current methods are based on one-dimensional (1D) descriptions of the tip-sample interaction forces, thus neglecting the intricacies involved in the material behavior of complex samples (such as soft viscoelastic materials) as well as the differences in material response between the surface and the bulk. In order to begin to address this gap, a computational study is presented where the sample is simulated using an enhanced version of a recently introduced model that treats the surface as a collection of standard-linear-solid viscoelastic elements. The enhanced model introduces in-plane surface elastic forces that can be approximately related to a two-dimensional (2D) Young's modulus. Relevant cases are discussed for single-and multifrequency intermittent-contact AFM imaging, with focus on the calculated surface indentation profiles and tip-sample interaction force curves, as well as their implications with regards to experimental interpretation. A variety of phenomena are examined in detail, which highlight the need for further development of more physically accurate sample models that are specifically designed for AFM simulation. As a result, a multifrequency AFM simulation tool based on the above sample model is provided as supporting information.

36 MATERIALS SCIENCE↗
DOE OSTI2024

VALIDATION, VERIFICATION, AND CALIBRATION THROUGH A CAUSAL LENS

This paper presents an alternative method based on causal inference to perform validation, verification, and calibration of simulation models. While classical validation and verification approaches focus on the identification of the associations between data elements using statistical and machine learning methods, the novel methods in this paper focus instead on the identification of causal relationships between data elements. Statistical and machine learning-based approaches are strictly data-driven, meaning that they provide quantitative comparison measures between datasets without explicitly considering the hypotheses behind them. This can lead to the erroneous conclusion that, if two data sets are close enough, then the models that generated them are similar. In addition, when experimental and simulated data differ to an extent that fails to meet the acceptance criteria, calibration techniques are used to tweak simulation model parameters to reduce the gap between the two types of data. This produces the false expectation that a simulation model will match reality. The methods presented in this paper move away from these strictly data-driven methods for validation and calibration toward more robust, model-driven methods based on causal inference. Causal inference aims to identify the possible mechanisms that might have generated data. Thus, this analysis targets the prediction of the effects when one (or more) of the identified mechanisms are altered. There are many approaches to identify, quantify and illustrate causal relationships. For the scope of this paper, directed graphs are employed as causal models. If the directed graph lacks cycles it is known as a directed acyclic graph (DAG). A node in such a graph represents an observed data element while a directed edge connecting two nodes represents a causal relationship between two variables. The developed causal methods are designed to extract causal models from simulation models and from experimental data. Causal models capture the causal relationships between data elements (e.g., simulated and experimental data). In this context, validation and verification are performed by comparing causal models. The proposed approach does not only inform system analysts on how a simulation model matches real-world data, but also identifies elements of the simulation model that should be revised when discrepancies between simulation and experimental data are observed. Through these causal methods, analysts have a means to identify the portion of the model equation(s) that are behind an edge connecting two variables. Hence, once the structural differences between causal models have been determined, model calibration can occur by changing only those model parameters that impact the identified causal relationships.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

An introduction to Spent Nuclear Fuel decay heat for Light Water Reactors: a review from the NEA WPNCS

This paper summarized the efforts performed to understand decay heat estimation from existing spent nuclear fuel (SNF), under the auspices of the Working Party on Nuclear Criticality Safety (WPNCS) of the OECD Nuclear Energy Agency. Needs for precise estimations are related to safety, cost, and optimization of SNF handling, storage, and repository. The physical origins of decay heat (a more correct denomination would be decay power) are then introduced, to identify its main contributors (fission products and actinides) and time-dependent evolution. Due to limited absolute prediction capabilities, experimental information is crucial; measurement facilities and methods are then presented, highlighting both their relevance and our need for maintaining the unique current full-scale facility and developing new ones. The third part of this report is dedicated to the computational aspect of the decay heat estimation: calculation methods, codes, and validation. Different approaches and implementations currently exist for these three aspects, directly impacting our capabilities to predict decay heat and to inform decision-makers. Finally, recommendations from the expert community are proposed, potentially guiding future experimental and computational developments. One of the most important outcomes of this work is the consensus among participants on the need to reduce biases and uncertainties for the estimated SNF decay heat. If it is agreed that uncertainties (being one standard deviation) are on average small (less than a few percent), they still substantially impact various applications when one needs to consider up to three standard deviations, thus covering more than 95% of cases. The second main finding is the need of new decay heat measurements and validation for cases corresponding to more modern fuel characteristics: higher initial enrichment, higher average burnup, as well as shorter and longer cooling time. Similar needs exist for fuel types without public experimental data, such as MOX, VVER, or CANDU fuels. A third outcome is related to SNF assemblies for which no direct validation can be performed, representing the vast majority of cases (due to the large number of SNF assemblies currently stored, or too short or too long cooling periods of interest). A few solutions are possible, depending on the application. For the final repository, systematic measurements of quantities related to decay heat can be performed, such as neutron or gamma emission. This would provide indications of the SNF decay heat at the time of encapsulation. For other applications (short- or long-term cooling), the community would benefit from applying consistent and accepted recommendations on calculation methods, for both decay heat and uncertainties. This would improve the understanding of the results and make comparisons easier.

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

Two-temperature scales in the triangular-lattice Heisenberg antiferromagnet

The anomalous thermodynamic properties of the paradigmatic frustrated spin-1/2 triangular-lattice Heisenberg antiferromagnet (TLH) has remained an open topic of research over decades, both experimentally and theoretically. We further the theoretical understanding based on the recently developed, powerful exponential tensor renormalization group method on cylinders and stripes in a quasi-one-dimensional (1D) setup, as well as a tensor product operator approach directly in 2D. The observed thermal properties of the TLH are in excellent agreement with two recent experimental measurements on the virtually ideal TLH material ${\mathrm{Ba}}_{8}{\mathrm{CoNb}}_{6}{\mathrm{O}}_{24}$. Remarkably, our numerical simulations reveal two crossover temperature scales, at ${T}_{l}/J{\sim}0.20$ and ${T}_{h}/J{\sim}0.55$, with $J$ the Heisenberg exchange coupling, which are also confirmed by a more careful inspection of the experimental data. We propose that in the intermediate regime between the low-temperature scale ${T}_{l}$ and the higher one ${T}_{h}$, the "rotonlike" excitations are activated with a strong chiral component and a large contribution to thermal entropies. Bearing remarkable resemblance to the renowned roton thermodynamics in liquid helium, these gapped excitations suppress the incipient ${120}^{{\circ}}$ order that emerges for temperatures below ${T}_{l}$.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Modeling Induction Stirring and Particle Tracking in Molten Uranium

Two independent numerical models have been developed to simulate the behavior of carbon impurities in molten uranium metal. Informed by experimental parameters, one model was created using the commercial software Star-CCM+ and compared with another developed using open-source codes, including OpenFOAM, Finite Element Method Magnetics (FEMM) and a First Passage Kinetic Monte Carlo (FPKMC) approach. The target experimental system features a 404g uranium metal charge containing an average carbon concentration of 139 ppm which was melted in a vacuum induction furnace at 1400° C then resolidified. The microstructures of the uranium and its impurities before and after melting have been characterized and reported separately. Prior to simulating the uranium-carbon system described, the numerical models were validated using a previously published nonradioactive experimental system to ensure agreement with expected output values. Focus has been placed on modeling velocity fields under induction stirring and impurity particle trajectories.

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

Corrosion Testing Of Additively Manufactured Stainless Steel 316H In Molten Salt Environments

The development of a new ASTM standard for evaluating the corrosion resistance of additive manufactured (AM) stainless steel (SS) 316H in chloride molten salts is critical for the use of these materials in extreme environments such as molten salt reactors (MSRs). This report pertains to a work package of the Advaned Materials and Manufacturing Technologies (AMMT) developing a systematic methodology to link changes in AM fabrication parameters, namely surface finishing, porosity, microstructure, and chemical heterogeneity, to corrosion performance in NaCl-MgCl2 salt, a proposed secondary coolant for MSRs. During Fiscal Year 2024, Idaho National Laboratory investigators in the AMMT program, utilized SS316H bars, fabricated with laser bed powder fusion at Los Alamos National Laboratory, to establish and optimize the workflow for evaluating these process-to-performance relationships. Standard practices for specimen preparation were established using these specimens, with particular focus on descaling and sectioning methods that align with ASTM guidelines. A comprehensive experimental design for static corrosion testing was developed, with pre- and post-exposure analysis utilizing optical microscopy and scanning electron microscopy. So far standard descaling techniques were optimized, one static corrosion test was conducted on the LANL AM SS316H specimens, and pre- and post-corrosion practices were established. In addition, the work package yielded a review paper on corrosion testing gaps for AM materials in nuclear applications and submitted a proposal for a rapid-turnaround experiment to the Nuclear Science User Facilities Program to investigate the combined effects of proton irradiation and corrosion on AM SS316H. This work package establishes a foundation for evaluating processing-to-performance relationships for AM SS316H in harsh conditions, contributing to the safe and efficient design of components for next-generation nuclear reactors. The creation of a standardized methodology and the generation of relevant publications and future research pathways represent significant strides towards integrating AM materials into critical applications where corrosion resistance is paramount.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Testing to Evaluate Processes Expected to Occur during MSR Salt Spill Accidents

Obtaining a license for a new nuclear reactor requires the identification and assessment of the potential consequences of specified accident scenarios, which are achieved using accident progression models. Those models need to be parameterized and validated using experimental data, but existing experimental data addressing processes relevant to molten salt reactor accidents are sparse. Specifically, experimental data that quantify the sensitives of important processes to the initial conditions of the spill, the ambient environment, and the containment features are needed to parameterize individual process models. Integrated experiments that simulate accident scenarios are also needed to provide data for model validation, but these experiments will require the use of proven methods to quantify the processes under evaluation. The overarching objectives of this work are to develop the methods for simulating the targeted processes, to determine the effectiveness of the methods in producing the data required for model development, to generate data that can be used to parameterize individual process models, and to provide key insights into the behavior of spilled molten salt that should be considered in models. Experimental methods were designed to quantify aspects of individual processes expected to occur during or after a molten salt spill accident that will affect the fate of spilled molten salt and the radionuclides within. These processes include 1) molten salt spreading and heat transfer, 2) molten salt flowing and freezing in tubing, 3) stainless steel corrosion kinetics in molten salt, and 4) molten salt splashing and aerosol generation. The initial tests described in this report were conducted using eutectic FLiNaK to demonstrate the test methods, the data that are generated, and the analyses of the data to derive values needed for modeling. The primary variables that were tested include initial salt temperature and the presence of volatile surrogate fission products (e.g., cesium and iodine). The developed methods are shown to be effective in quantifying the desired processes and can be applied to study more complex salt compositions of interest to molten salt reactor developers, a wide range of environmental conditions of interest to modelers, and additional variables relevant to salt spill accidents. The developed methods and insights gained from laboratory tests can also be incorporated in future large-scale integrated tests used to simulate molten salt spill accidents.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Electronic Structure Theory and Novel Materials

This grant supported research on electronic structure and materials theory, with focus on three main issues: (i) novel techniques to deal with correlation in the electronic ground-state, (ii) topological materials, (iii) the phase diagram of lattice spin models. Regarding (i), we applied to the homogeneous electron liquid an approach that we previously developed in the context of molecular systems. In this scheme the electronic occupation probabilities and the natural spin orbitals are used to construct an approximate two-body density matrix for the electronic ground-state. Regarding (ii) we used standard electronic structure methods based on density functional theory to model topological materials and interpret experimental observations. Finally, regarding (iii) we further developed a numerical approach to compute the renormalized couplings within real space renormalization group theory in the context of lattice spin models. The main findings were the following. (i) We found that with our approximate two-body density matrix, which works well for small molecules, is not sufficiently accurate for condensed phase systems. Missing a systematic way of improving on the adopted approximations, we decided not to pursue this approach. (ii) We performed two studies. In one, we investigated the influence of Te defects on the topological properties of a WTe2 monolayer, finding that while Te vacancies, even in modest concentration, destroy the topological character, Te adatoms do not, consistent with a recent experiment. In another study, we predicted Weyl semimetal character and strong anomalous Hall effect in the Heusler compensated ferrimagnet Ti2MnAl. (iii) We developed a new Monte Carlo method to do real space renormalization group calculations for lattice spin models. We subsequently extended the scheme to deal with lattice spin models in presence of quenched disorder, finding that the approach can distinguish systems with finite and strong disorder. In the finite disorder case, the method allows one to find with good approximation the critical coupling distribution and the critical exponents.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Image registration for in situ X-ray nano-imaging of a composite battery cathode with deformation

The structural and chemical evolution of battery electrodes at the nanoscale plays an important role in affecting the cell performance. Nano-resolution X-ray microscopy has been demonstrated as a powerful technique for characterizing the evolution of battery electrodes under operating conditions with sensitivity to their morphology, compositional distribution and redox heterogeneity. In real-world batteries, the electrode could deform upon battery operation, causing challenges for the image registration which is necessary for several experimental modalities, e.g. XANES imaging. To address this challenge, this work develops a deep-learning-based method for automatic particle identification and tracking. This approach was not only able to facilitate image registration with good robustness but also allowed quantification of the degree of sample deformation. The effectiveness of the method was first demonstrated using synthetic datasets with known ground truth. The method was then applied to an experimental dataset collected on an operating lithium battery cell, revealing a high degree of intra- and interparticle chemical complexity in operating batteries.

25 ENERGY STORAGE↗
DOE OSTI2023

Combining data and theory for derivable scientific discovery with AI-Descartes

Abstract Scientists aim to discover meaningful formulae that accurately describe experimental data. Mathematical models of natural phenomena can be manually created from domain knowledge and fitted to data, or, in contrast, created automatically from large datasets with machine-learning algorithms. The problem of incorporating prior knowledge expressed as constraints on the functional form of a learned model has been studied before, while finding models that are consistent with prior knowledge expressed via general logical axioms is an open problem. We develop a method to enable principled derivations of models of natural phenomena from axiomatic knowledge and experimental data by combining logical reasoning with symbolic regression. We demonstrate these concepts for Kepler’s third law of planetary motion, Einstein’s relativistic time-dilation law, and Langmuir’s theory of adsorption. We show we can discover governing laws from few data points when logical reasoning is used to distinguish between candidate formulae having similar error on the data.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗