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At least 289 records · Page 16

GPLaSDI: Gaussian Process Latent Space Dynamics Identification

GPLaSDI is a software that introduces GPLaSDI, a novel LaSDI-based framework that relies on Gaussian process (GP) for latent space ODE interpolations. Using GPs offers two significant advantages. First, it enables the quantification of uncertainty over the reduced order model (ROM) predictions. Second, leveraging this prediction uncertainty allows for efficient adaptive training through a greedy selection of additional training data points. This approach does not require prior knowledge of the underlying PDEs. Consequently, GPLaSDI is inherently non-intrusive and can be applied to problems without a known PDE or its residual. We demonstrate the effectiveness of our approach on the Burgers equation, Vlasov equation for plasma physics, and a rising thermal bubble problem. Our proposed method achieves between 200 and 100,000 times speed-up, with up to 7% relative error.

Choi, Youngsoo↗

Systematic analysis of melt pool dynamics in laser processing of mixed powder feedstocks

Functionally graded materials (FGMs) fabricated via additive manufacturing of blended powders offer the potential to spatially tailor properties for new technologies, such as fusion first-wall systems, turbine blades, and spacecraft. However, processing these materials is difficult due to the multiplicity of processing parameters to optimize, all of which must be changed as substrate material, powder feedstock compositions, and melt pool dynamics evolve. Here, this work systematically evaluates the qualitative and quantitative effects of these variables on the melt pool size, shape, composition, and particle distribution in an exemplar Ti-Ta system, and connects the experimental results to Marangoni flow behavior and phenomena observed in other systems. Increasing laser power linearly increases melt pool size and layer thickness, driving engineering considerations such as part/geometrical tolerances. Decreasing laser velocity changes the melt pool shape from lenticular to convex and reduces chemical homogeneity due to extreme thermal and compositional gradients between the melt pool center and boundaries. Thermophysical property differences between the powder feedstock and substrate material, as well as the directionality of the gradient, affect dilution and melt pool dynamics, which in turn affect the melt pool boundary characteristics, shape, and uniformity. Mixed powder feedstocks of intermediate compositions do not behave according to linear interpolations between single-material endpoints, instead building taller and wider melt pools. As such, it is recommended to quantify process maps for at least one intermediate composition in the FGM or multi-material system of interest to ensure optimized processing parameters, predictable melt pool sizes and shapes, and compositional and spatial precision.

Dissimilar↗

Antarctic permafrost processes and antiphase dynamics of cold-based glaciers in the McMurdo Dry Valleys inferred from 10 Be and 26 Al cosmogenic nuclides

Abstract. Soil and sediment mixing and associated permafrost processes are not widely studied or understood in the McMurdo Dry Valleys of Antarctica. In this study, we investigate the stability and depositional history of near-surface permafrost sediments to ∼ 3 m depth in the Pearse and lower Wright valleys using measured cosmogenic 10Be and 26Al depth profiles. In Pearse Valley, we estimate a minimum depositional age of ∼ 74 ka for the active layer and paleoactive-layer sediments (< 0.65 m). Combined depth profile modelling of 10Be and 26Al gives a depositional age for near-surface (< 1.65 m) permafrost in Pearse Valley of 180 +20/-40 ka, implying that the deposition of permafrost sediments predates MIS 5 advances of Taylor Glacier. Deeper permafrost sediments (> 2.09 m) in Pearse Valley are thus inferred to have a depositional age of > 180 ka. At a coastal, lower-elevation site in neighbouring lower Wright Valley, 10Be and 26Al depth profiles from a second permafrost core exhibit near-constant concentrations with depth and indicate the sediments are either vertically mixed after deposition or sufficiently young so that post-depositional nuclide production is negligible relative to inheritance. 26Al/10Be concentration ratios for both depth profiles range between 4.0 and 5.2 and are all lower than the nominal surface production rate ratio of 6.75, indicating that prior to deposition, these sediments experienced complex, yet similar, exposure–burial histories. Assuming a single-cycle exposure–burial scenario, the observed 26Al/10Be ratios are equivalent to a total minimum exposure–burial history of ∼ 1.2 Myr. In proximity to the depth profile core site, we measured cosmogenic 10Be and 26Al in three granite cobbles from thin, patchy drift (Taylor 2 Drift) in Pearse Valley to constrain the timing of retreat of Taylor Glacier. Assuming simple continuous exposure, our minimum, zero-erosion exposure ages suggest Taylor Glacier partially retreated from Pearse Valley no later than 65–74 ka. The timing of retreat after 65 ka and until the Last Glacial Maximum (LGM) when Taylor Glacier was at a minimum position remains unresolved. The surface cobble ages and permafrost processes reveal Taylor Glacier advances during MIS 5 were non-erosive or mildly erosive, preserving the underlying permafrost sediments and peppering boulders and cobbles upon an older, relict surface. Our results are consistent with U/Th ages from central Taylor Valley and suggest changes in moisture delivery over Taylor Dome during MIS 5e, 5c, and 5a appear to be associated with the extent of the Ross Ice Shelf and sea ice in the Ross Sea. These data provide further evidence of antiphase behaviour through retreat of a peripheral lobe of Taylor Glacier in Pearse Valley, a region that was glaciated during MIS 5. We suggest a causal relationship of cold-based glacier advance and retreat that is controlled by an increase in moisture availability during retreat of sea ice and perhaps the Ross Ice Shelf, as well as, conversely, a decrease during times of sea ice and Ross Ice Shelf expansion in the Ross Sea.

58 GEOSCIENCES↗

Vibrational processing of a dynamic structural flight system: A multichannel spectral estimation approach

Dynamic testing of large flight vehicles (rockets) is not only complex, but also can be very costly. These flights are infrequent and can lead to disastrous effects if something were to fail during the flight. The development of sensors coupled to internal components offers a great challenge in reducing their size, yet still maintaining their precision. Sounding rockets provide both a viable and convenient alternative to the more costly vehicular flights. Some of the major objectives are to test various types of sensors for monitoring components of high interest as well as investigating real-time processing techniques. Signal processing presents an extreme challenge in this noisy multichannel environment. The estimation and tracking of modal frequencies from vibrating structures is an important set of features that can provide information about the components under test; therefore, high resolution multichannel spectral processing is required. Finally, the application of both single channel and multichannel techniques capable of producing reliable modal frequency estimates of a vibrating structure from uncertain accelerometer measurements is discussed.

42 ENGINEERING↗

Controlling Structural, Electronic, and Energy Flow Dynamics of Catalytic Processes through Tailored Nanostructures

MoS 2 (molybdenum disulfide) is a highly-versatile catalyst material for support of numerous reactions from hydrodesulfurization and denitrogenation to the focus of this renewal proposal: hydrogenation of CO/CO 2 towards (higher) alcohols. At the same time, MoS 2 is a non-toxic, environmentally-benign and rather inert material- which under ambient conditions for some time has served as a lubricant and, more recently, as next-generation electronic material. The apparent contrast between inertness and stability in ambient, and catalytic activity under reactive conditions is puzzling and calls for a synergistic theoretical and experimental investigation with the long-term objective of enabling the rational design of MoS 2 -based catalysts for alcohol-formation reactions by providing a microscopic understanding of the environmental factors that determines site activity and selectivity. Our research project seeks answers to the questions (a) what conformation does MoS 2 adopt under reaction conditions (as opposed to that under ultrahigh vacuum and low temperatures)?; (b) what reaction pathways exist on such a material?; (c) how can the local environment of the active sites be manipulated so as to make MoS 2 an efficient catalyst for production of higher alcohol from syngas? In particular, research strategies will explore how the basal plane composed of sulfur atoms can be activated so as to exhibit a reactivity of its own, by addressing three research targets and building on extensive preliminary and enabling work: (1) vacancies and vacancy aggregates on the basal plane; (2) non-local catalyst transformation through alkali doping, hydrogenation and phase transition; (3) fabrication of a metal-nanoparticle-activated MoS 2 system, in which particle anchoring, reactive sites and pathways as well as selectivity are controlled by design, as an example of predictive development of a catalyst material,. All strategies are directed to improve the efficacy of the key reactive sites and selectivity of chemical pathways by design, to replace the inefficient methodology of trial and error in catalyst development. This research project represents a synergistic combination of computational guidance, foundational surface-science-based experiments and validation under reactive conditions that aims at transformative new insights into the working of MoS 2 -based hydrogenation-catalysts, a topic squarely at the center of the interest of DOE BES. Guided and led by Talat Rahman, a computational physicist, this project will apply density functional theory to understand structure, reaction pathways and chemical potentials associated with MoS 2 -based CO/CO 2 hydrogenation, augmented by kinetic Monte Carlo methods for reaction rates and prefactors as well as ab-initio molecular dynamics for evaluation of thermal stability. Complementary experimental input and validation will originate from co-PI Ludwig Bartels, a physical chemist and materials scientist, whose group focuses on local imaging and preparation of MoS 2 materials, from co-PI Peter Dowben, an experimental physicist, whose group is expert in the spectroscopy of occupied and unoccupied electronic states, and from senior collaborator Michael White of Brookhaven National Laboratory, whose group generates high-resolution electronic and activity information on size-selected well-defined metal chalcogenide clusters. This collaborative effort will enable a comprehensive understanding of the correlation of structural integrity and catalytic activity of MoS 2 in forms ranging from extended films to individual particles with known geometries and binding sites. Alcohol formation from syngas is a rapidly emerging application that has great potential through facile, economic, and decentralized biomass gasification. CO 2 activation is one of the most pressing concerns of our time: increasing CO 2 levels in the atmosphere change the climate and expose the globe to environmental transformations with the potential for enormous economic and societal impact. We will investigate CO/CO 2 hydrogenation via an interdisciplinary research collaboration with established synergy – one that, in accordance with the mission of the DOE, involves accredited Hispanic-Serving Institutions and that, through student exchange with international collaborators and National Labs, will directly benefit a broad spectrum of communities and generate human resources in sciences essential to their future.

2D materials↗

Degree-preserving graph dynamics: a versatile process to construct random networks

Real-world networks evolve over time via the addition or removal of vertices and edges. In current network evolution models, vertex degree varies or grows arbitrarily. A recently introduced degree-preserving network growth (DPG) family of models preserves vertex degree, resulting in structures significantly different from and more diverse than previous models. Despite its degree preserving property, the DPG model is able to replicate the output of several well-known real-world network growth models. Simulations showed that many real-world networks can also be constructed from small seed graphs via the DPG process. Here, we start the development of a rigorous mathematical theory underlying the DPG family of network growth models. We prove that the degree sequence of the output of some of the well-known, real-world network growth models can be reconstructed via the DPG process, using proper parametrization. We also show that the general problem of deciding whether a simple graph can be obtained via the DPG process from a small seed (DPG feasibility) is, however, NP-complete. In conclusion, it is an intriguing open problem to uncover whether there is a structural reason behind the DPG-constructability of real-world networks.

97 MATHEMATICS AND COMPUTING↗

Dynamic and transient processes in warm dense matter

In this paper, we discuss some of the key challenges in the study of time-dependent processes and non-equilibrium behaviour in warm dense matter. We outline some of the basic physics concepts that have underpinned the definition of warm dense matter as a subject area in its own right and then cover, in a selective, non-comprehensive manner, some of the current challenges, pointing along the way to topics covered by the papers presented in this volume.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Dynamic microbial assembly processes correspond to soil fertility in sustainable paddy agroecosystems

1. Microorganisms underpin the sustainability of agroecosystems, but we have a poor understanding of how the assembly processes that govern microbial community structure interact through time to maintain soil fertility. 2. Ancient rice paddies have a history of cultivation spanning hundreds or thousands of years and provide an ideal opportunity to explore relationships between community assembly processes and long-term agroecosystem sustainability. We used statistical null models to evaluate temporal patterns of bacterial community assembly processes across rice cultivation years and their associations with increases in soil fertility in paddy agroecosystems. 3. We found that stochasticity was a persistent force structuring paddy soil microbial communities, putatively due to frequent flooding that facilities dispersal. However, determinism gradually increased over centuries of agriculture and corresponded to increases in soil fertility. Accordingly, multifunctionality, calculated using enzymes catalyzing key soil functions in carbon, nitrogen, phosphorous and sulfur cycling significantly increased along rice cultivation years. We therefore propose that balanced assembly processes preserve a diverse array of traits that can dominate under various circumstances (stochasticity) while allowing for traits relevant to soil fertility to be selected for by soil fertility (determinism), thus supporting multifunctionality that underlies sustainable agroecosystems. 4. In total, our results highlight that knowledge on temporal microbial assembly processes, community composition, and ecological function in context of soil fertility is key to understanding ecological mechanisms maintaining agroecosystems sustainability.

Liu, Wenjing↗

Advanced Process Control and Dynamic Optimization of Reversible Solid Oxide Cell Systems for Performance and Long-Term Health

This presentation was delivered at the 2024 Hydrogen Annual Merit Review Meeting. It focuses on three aspects of projects focusing on solid oxide cell systems- advanced control including nonlinear model predictive control and traditional control, dynamic optimization with due consideration of chemical degradation over the cell lifetime, dynamic optimization considering physical degradation.

Allan, Douglas↗

Compositional Variation Tests on DuraMelter 100 with LAW Sub-Envelope C1 Feed (LAWC22) Glass in Support of the LAW Pilot Melter (Final Report)

The Vitreous State Laboratory at The Catholic University of America (VSL) is developing and testing glass formulations for RPP-WTP waste envelopes to provide data to meet the RPP-WTP contract requirements and to support system design activities. That work is based upon small-scale batch melts (“crucible melts”) using waste envelope simulants. Selected formulations have also been tested in small-scale continuously-fed joule-heated melters (DM10 and DM100 systems) and, ultimately, in the LAW Pilot Melter. Such melter tests provide information on key process factors such as feed processing behavior, dynamic effects during processing, sulfate incorporation, processing rates, off-gas amounts and compositions, foaming control, etc., that cannot be reliably obtained from crucible melts. This sequential scale-up approach in the vitrification testing program ensures that maximum benefit is obtained from the more costly pilot-scale tests and that the most effective use is made of that resource. The principal objective of the work described in this report was to collect the necessary small-scale melter test data with a LAW Sub-Envelope C1 waste simulant in order to support the next series of tests with the same melter feed on the LAW Pilot Melter. This work was conducted under a corresponding Test Specification and Test Plan.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Understanding Adsorption and Reactions at Aqueous Oxide Interfaces with Neural Network Potential Molecular Dynamics

Chemical processes at metal oxide−water interfaces are of central importance in geochemistry, biology, and energy technologies. A better understanding of these processes would allow us to make a significant step toward optimizing and controlling them, which could in turn lead to broader impacts. Computational modeling is indispensable to accomplishing this task because complexity and disorder often make it difficult to extract atomistic information from experiments. Balancing computational cost and accuracy, simulation schemes based on efficient machine learning representations of the potential energy surface (PES) predicted by ab initio calculations have become increasingly popular over the past decade. In particular, several studies have demonstrated the ability of machine learning models to accurately reproduce the complex ab initio PESs of aqueous oxide interfaces, allowing simulations of systems and processes that are not accessible with ab initio methods. In this Account, we review our recent efforts to understand adsorption processes and reactions at aqueous oxide interfaces using deep potential molecular dynamics (DPMD), a simulation scheme employing deep neural networks (DNNs), which has proven to be quite successful in accurately describing many different systems in the condensed phase. After summarizing the DPMD methodology, we first review our work on the acid−base chemistry of oxide surfaces in contact with water, a fundamental characteristic that controls proton transfer and surface charge at the interface. We focus on the aqueous interface of rutile IrO 2 , an oxide material thus far considered the best catalyst for the oxygen evolution reaction (OER). We show that this interface is characterized by a large fraction of dissociated water and a strong Brønsted acidity of the surface sites, in good agreement with the experimentally measured value of the point of zero proton charge. In our second example, we investigate how the adsorption of organic species from ambient air or water affects the structure and wettability of the aqueous interfaces of TiO 2 , a prototypical photocatalytic material. This is a question that is relevant to understanding the UV-induced hydrophilicity of TiO 2 surfaces, a property at the basis of self-cleaning windows and related applications. Specifically focusing on formic and acetic acids, the two most common atmospheric organic acids, our simulations reveal that these acids control the wettability of TiO 2 largely through acid−base chemistry at the interface rather than chemisorption on the oxide surface, a finding that could help improve the design of self-cleaning surfaces and photocatalytic devices. Finally, we review our recent study of methanol at TiO 2 −water interfaces, a system whose interest is largely motivated by the role of methanol in enhancing photocatalytic hydrogen evolution on TiO 2 . Our simulations provide mechanistic insights into the coupled roles of the organic adsorbate and water at the TiO 2 interface, with implications for how methanol enhances the activity of H 2 evolution.

adsorption↗

The impact of r -process heating on the dynamics of neutron star merger accretion disc winds and their electromagnetic radiation

Neutron star merger accretion discs can launch neutron-rich winds of >10 -2 M⊙. This ejecta is a prime site for r-process nucleosynthesis, which will produce a range of radioactive heavy nuclei. The decay of these nuclei releases enough energy to accelerate portions of the wind by ~0.1c. Here, we investigate the effect of r-process heating on the dynamical evolution of disc winds. We extract the wind from a 3D general relativistic magnetohydrodynamic simulation of a disc from a post-merger system. This is used to create inner boundary conditions for 2D hydrodynamic simulations that continue the original 3D simulation. We perform two such simulations: one that includes the r-process heating, and another one that does not. We follow the hydrodynamic simulations until the winds reach homology (60 s). Using time-dependent multifrequency multidimensional Monte Carlo radiation transport simulations, we then calculate the kilonova light curves from the winds with and without dynamical r-process heating. We find that the r-process heating can substantially alter the velocity distribution of the wind, shifting the mass-weighted median velocity from 0.06c to 0.12c. The inclusion of the dynamical r-process heating makes the light curve brighter and bluer at $\sim 1\, \mathrm{d}$ post-merger. However, the high-velocity tail of the ejecta distribution and the early ($\lesssim 1\, \mathrm{d}$) light curves are largely unaffected.

79 ASTRONOMY AND ASTROPHYSICS↗

Hybrid magnonics: Physics, circuits, and applications for coherent information processing

Hybrid dynamic systems have recently gained interest with respect to both fundamental physics and device applications, particularly with their potential for coherent information processing. In this work, we will focus on the recent rapid developments of magnon-based hybrid systems, which seek to combine magnonic excitations with diverse excitations for transformative applications in devices, circuits, and information processing. Key to their promising potentials is that magnons are highly tunable excitations and can be easily engineered to couple with various dynamic media and platforms. The capability of reaching strong coupling with many different excitations has positioned magnons well for studying solid-state coherent dynamics and exploiting unique functionality. In addition, with their gigahertz frequency bandwidth and the ease of fabrication and miniaturization, magnonic devices and systems can be conveniently integrated into microwave circuits for mimicking a broad range of device concepts that have been applied in microwave electronics, photonics, and quantum information. We will discuss a few potential directions for advancing magnon hybrid systems, including on-chip geometry, novel coherent magnonic functionality, and coherent transduction between different platforms. As a future outlook, we will discuss the opportunities and challenges of magnonic hybrid systems for their applications in quantum information and magnonic logic.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗