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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 415 records · Page 23

A theoretical/computational framework to measure SiO2 and MgO viscosity at high pressure

The convection of the mantle of Earth and super-Earths is important for many terrestrial phenomena, from plate tectonics to outgassing. Rheological properties, such as viscosity, regulate the transport of thermal energy and mass. However, the viscosity of mantle-relevant materials, such as MgO, at relevant pressures (>120 GPa) are not well constrained. The objective of this work was to develop a computational platform to simulate novel experiments aiming to measure the viscosity of MgO at high pressures. Experiments performed by our collaborators at Johns Hopkins University and Lawrence Livermore National Laboratory use the OMEGA EP laser facility to shock a corrugated MgO interface to 170 GPa, with resulting velocity evolution governed by the viscous Richtmyer-Meshkov instability. We used an in-house hydrocode to simulate this process and thus provide a bound on viscosity by comparing our simulations results to these experiments, as well as to examine the physical processes at play. We simulated the experiments with different values of MgO viscosity (from inviscid to 10,000 Pa∙s) while taking into account the unsteady laser pulse, the material's equation of state, and the rate-dependent constitutive relation for MgO, and the materials' equations of state. Our results suggest that MgO at these conditions has a viscosity within an order of magnitude of 5000 Pa∙s.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Particle collisionality in scaled kinetic plasma simulations

Kinetic plasma processes, such as magnetic reconnection, collisionless shocks, and turbulence, are fundamental to the dynamics of astrophysical and laboratory plasmas. Simulating these processes often requires particle-in-cell (PIC) methods, but the computational cost of fully kinetic simulations can necessitate the use of artificial parameters, such as a reduced speed of light and ion-to-electron mass ratio, to decrease expense. While these approximations can preserve overall dynamics under specific conditions, they introduce nontrivial impacts on particle collisionality that are not yet well understood. In this work, we develop a method to scale particle collisionality in simulations employing an artificial speed of light and/or an artificial ion-to-electron mass ratio. By introducing species-dependent scaling factors, we independently adjust inter- and intra-species collision rates to better replicate the collisional properties of the physical system. Our approach maintains the fidelity of electron and ion transport properties while preserving critical relaxation rates, such as energy exchange timescales, within the limits of weakly collisional plasma theory. Furthermore, we demonstrate the accuracy of this scaling method through benchmarking tests against theoretical relaxation rates and connecting to fluid theory, highlighting its ability to retain key transport properties. Existing collisional PIC implementations can be easily modified to include this scaling, which will enable deeper insights into the behavior of marginally collisional plasmas across various contexts.

Totorica, S. R. [Princeton Univ., NJ (United State↗

Ferroelectric molecular field-switch based on double proton transfer process: Static and dynamical simulations

In this work, we present a reversible ferroelectric molecular switch controlled by an external electric field. The studied (2Z)-1-(6-((Z)-2-hydroxy-2-phenylvinyl)pyridin-3-yl)-2-(pyridin-2(1H) -ylidene)ethanone (DSA) molecule is polarized by two uniaxial intramolecular hydrogen bonds. Two protons can be transferred along hydrogen bonds upon an electric field applied along the main molecular axis. The process results in reversion of the dipole moment of the system. Static ab initio and on-the-fly dynamical simulations of the DSA molecule placed in an external electric field give insight into the mechanism of the double proton transfer (DPT) in the system and allow for estimation of the time scale of this process. The results indicate that with increasing strength of the electric field, the step-wise mechanism of DPT changes into the downhill barrierless process in which the synchronous and asynchronous DPTs compete with each other.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Effect of time and spatial domains on monolayer 2D material interface thermal conductance measurement using ns ET-Raman

Raman-based approaches to characterizing thermal properties of nanoscale and microscale materials have proven to be powerful experimental methods. Here, this work explores the potential of energy-transport state-resolved Raman (ET-Raman) for the precise determination of interfacial thermal conductance (G) between monolayer 2D materials and their substrates. ET-Raman employs a continuous wave laser and nanosecond (ns) pulsed laser to induce both steady state and transient heating while simultaneously collecting 2D material temperature information from the Raman signal. A 3D numerical model built using the finite volume method simulates the two differentiated thermal transport processes. The simulated temperature rises are compared with experimental Raman temperature information to extract G. In this study, we investigate the temporal effects of the pulse frequency and pulse width of the ns laser on precise characterization of G. By running multiple simulations for a range of pulsed laser frequencies and pulse widths, we determine that ET-Raman is most sensitive to precise interfacial thermal conductance measurements with short pulse widths (~below 20 ns) and with pulsing frequencies that ensure sufficient cooling time between consecutive pulses (~below 500 kHz). We also conclude that substrate thickness and laser spot size play critical roles in heat distribution and subsequent sensitivity to meaningful G measurements. As both laser spot size and SiO 2 substrate thickness decrease, detection of interfacial thermal transport becomes more difficult. These results offer essential guidance in the design of future Raman-based approaches to thermal measurements using pulsed lasers.

2D materials↗

Adaptive ensemble simulations of biomolecules

Recent advances in both theory and computational power have created opportunities to simulate biomolecular processes more efficiently using adaptive ensemble simulations. Ensemble simulations are now widely used to compute a number of individual simulation trajectories and analyze statistics across them. Adaptive ensemble simulations offer a further level of sophistication and flexibility by enabling highlevel algorithms to control simulations-based on intermediate results. We review some of the adaptive ensemble algorithms and software infrastructure currently in use and outline where the complexities of implementing adaptive simulation have limited algorithmic innovation to date. In conclusion, we describe an adaptive ensemble API to overcome some of these barriers and more flexibly and simply express adaptive simulation algorithms to help realize the power of this type of simulation.

97 MATHEMATICS AND COMPUTING↗

High-Accuracy Simulations to Model Pyrometallurgical Processes in a Secondary Lead Reverberatory Furnace

The US manufacturing industry produces about 1.3 million tons of refined lead each year using secondary sources consisting mainly of lead batteries. ORNL is partnering with Gopher resource, the second largest lead recycling company in the United States, and GTI, to develop a high-fidelity CFD model of a directly fired, reverberatory-style, secondary lead furnace. These High Performance Computing (HPC) simulations are aimed to use first principles modeling for combustion and melting processes of the secondary lead feed while accounting for complex interphase interactions between the gas, solid charge (lead) material, slag, and metal phases. Through validation against operating plant data, this effort will enable significant improvements in design, operational parameters, and energy efficiency, thus improving productivity and refractory lifetime of secondary lead melting furnaces. Estimated savings/reduction of, at least, 1 trillion BTU, 1 million ton/year of greenhouse gas emissions, and $\$50$ million/year to the US lead industry can be expected. ORNL resources and expertise in high-performance computing and multicomponent, multiphase flows were utilized to realize this goal while advancing the understanding of the smelting and melting processes occurring within the furnace.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Assessment of Physical Security Modeling and Simulation in the Vulnerability Assessment Process

This report provides a comprehensive assessment of physical security modeling and simulation tools available for use in the vulnerability assessment (VA) process for nuclear facilities. It outlines the historical evolution of VA methodologies, emphasizing the transition from traditional layer-based approaches to a more holistic framework that integrates detection probabilities directly into combat simulations. The document details the critical components of the VA process, including the characterization of targets, threats, and protective measures, as well as the development of adversary scenarios that reflect both insider and outsider threats. It highlights the importance of performance assurance programs, emphasizing the need for continuous evaluation and testing of security systems to ensure their effectiveness against evolving threats. Additionally, the report discusses the significance of utilizing accredited modeling and simulation tools in accredited areas to accurately represent adversary actions and the corresponding responses of protective forces. By establishing a systematic approach to VA, this document aims to enhance the overall security posture of nuclear facilities, ensuring compliance with regulatory standards while effectively mitigating risks associated with potential adversarial actions.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

A conservative scheme of drift kinetic electrons for gyrokinetic simulation of kinetic-MHD processes in toroidal plasmas

A conservative scheme of drift kinetic electrons for gyrokinetic simulations of kinetic-magnetohydrodynamic processes in toroidal plasmas has been formulated and verified. Both vector potential and electron perturbed distribution function are decomposed into adiabatic part with analytic solution and non-adiabatic part solved numerically. The adiabatic parallel electric field is solved directly from the electron adiabatic response, resulting in a high degree of accuracy. Here, the consistency between electrostatic potential and parallel vector potential is enforced by using the electron continuity equation. Since particles are only used to calculate the non-adiabatic response, which is used to calculate the non-adiabatic vector potential through Ohm's law, the conservative scheme minimizes the electron particle noise and mitigates the cancellation problem. Linear dispersion relations of the kinetic Alfvén wave and the collisionless tearing mode in cylindrical geometry have been verified in gyrokinetic toroidal code simulations, which show that the perpendicular grid size can be larger than the electron collisionless skin depth when the mode wavelength is longer than the electron skin depth.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Solving inverse problems in stochastic models using deep neural networks and adversarial training

Inverse problems associated with stochastic models constitute a significant portion of scientific and engineering applications. In such cases the unknown quantities are distributions. The applicability of traditional methods is limited because of their demanding assumptions or prohibitive computational consumption; for example, maximum likelihood methods require closed-form density functions, and Markov Chain Monte Carlo needs a large number of simulations. We propose a new method that estimates the unknown distribution by matching the statistical properties between observed and simulated random processes. We leverage the expressive power of neural networks to approximate the unknown distribution and use a discriminative neural network for computing the statistical discrepancies between the observed and simulated random processes. Here we demonstrated numerically that the proposed methods can estimate both the model parameters and learn complicated unknown distributions.

42 ENGINEERING↗

Biochemical process of low level radioactive liquid simulation waste containing detergent

Research of biochemical process of low level radioactive liquid waste containing detergent has been done. Thse organic liquid wastes are generated in nuclear facilities such as from laundry. The wastes that are cotegorized as hazard and poison materials are also radioactive. It must be treated properly by detoxification of the hazard and decontamination of the radionuclides to ensure that the disposal of the waste meets the requirement of standard quality of water. This research was intended to determine decontamination factor and separation efficiensies, its kinetics law, and to produce a supernatant that ensured the environmental quality standard. The radioactive element in the waste was thorium with activity of 5.10{sup −5} Ci/m{sup 3}. The radioactive liquid waste which were generated in simulation plant contains detergents that was further processed by aerobic biochemical process using SGB 103 bacteria in a batch reactor equipped with aerators. Two different concentration of samples were processed and analyzed for 212 hours and 183 hours respectively at a room temperature. The product of this process is a liquid phase called as supernatant and solid phase material called sludge. The chemical oxygen demand (COD), biological oxygen demand (BOD), suspended solid (SS), and its alpha activity were analyzed. The results show that the decontamination factor and the separation efficiency of the lower concentration samples are higher compared to the samples with high concentration. Regarding the decontamination factor, the result for 212 hours processing of waste with detergent concentration of 1.496 g/L was 3.496 times, whereas at the detergent concentration of 0.748 g/L was 15.305 times for 183 hours processing. In case of the separation efficiency, the results for both samples were 71.396% and 93.465% respectively. The Bacterial growth kinetics equation follow Monod’s model and the decreasing of COD and BOD were first order with the rate constant of 0.01 hour{sup −1}.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Trident: A Universal Tool for Generating Synthetic Absorption Spectra from Astrophysical Simulations

Hydrodynamical simulations are increasingly able to accurately model physical systems on stellar, galactic, and cosmological scales; however, the utility of these simulations is often limited by our ability to directly compare them with the data sets produced by observers: spectra, photometry, etc. To address this problem, we have created trident, a Python-based open-source tool for post-processing hydrodynamical simulations to produce synthetic absorption spectra and related data. trident can (i) create absorption-line spectra for any trajectory through a simulated data set mimicking both background quasar and down-the-barrel configurations; (ii) reproduce the spectral characteristics of common instruments like the Cosmic Origins Spectrograph; (iii) operate across the ultraviolet, optical, and infrared using customizable absorption-line lists; (iv) trace simulated physical structures directly to spectral features; (v) approximate the presence of ion species absent from the simulation outputs; (vi) generate column density maps for any ion; and (vii) provide support for all major astrophysical hydrodynamical codes. trident was originally developed to aid in the interpretation of observations of the circumgalactic medium and intergalactic medium, but it remains a general tool applicable in other contexts.

79 ASTRONOMY AND ASTROPHYSICS↗

Gold-Tin Solder Wetting Behavior for Package Lid Seals

This study examined the cause of nonwetted regions of the gold (Au) finish on iron-nickel (Fe–Ni) alloy lids that seal ceramic packages using the 80Au-20Sn solder (wt %, abbreviated Au–Sn) and their impact on the final lid-to-ceramic frame solder joint. The Auger electron spectroscopy (AES) surface and depth profile techniques identified surface and through-thickness contaminants in the Au metallization layer. In one case, the AES analysis identified background levels of carbon (C) contamination on the surface; however, the depth profile detected Fe and Ni contaminants that originated from the plating process. The Fe and Ni could impede the completion of wetting and spreading to the edge of the Au metallization. The Au layer of lids not exposed to a Au–Sn solder reflow step had significant surface and through-thickness C contamination. Inorganic contaminants were absent. Subsequent simulated reflow processes removed the C contamination from the Au layer without driving Ni diffusion from the underlying solderable layer. Finally, an Au metallization having negligible C contamination developed elevated C levels after exposure to a simulated reflow process due to C contamination diffusing into it from the underlying Ni layer. However, the second reflow step removed that contamination from the Au layer, thereby allowing the metallization to support the formation of lid-to-ceramic frame Au–Sn joints without risk to their mechanical strength or hermeticity.

36 MATERIALS SCIENCE↗

Expanding the representation of aerosol, cloud, and precipitation processes with graph network-based simulators

We explored a novel framework for simulating the small-scale processes that drive the evolution of aerosol, cloud, and precipitation particles, which are a critical gap in the predictive understanding of weather and climate. Particle-based methods have emerged as an effective tool for modeling aerosol-cloud-precipitation interactions, but existing particle-based models are computationally too expensive to simulate the large domains relevant for the atmosphere or to represent the full suite of relevant processes. The lack of a comprehensive and efficient reference model is a critical bottleneck in our understanding of cloud and precipitation processes and our ability to parameterize these processes for regional- and global-scale simulations. To address this need, we explored an approach to accelerate and expand particle-based models using a new machine learning approach, graph network-based simulators (GNS). Rather than modeling the evolution of the system by numerically integrating continuity equations, the GNS represents dynamics through learned message passing. Our aim was to develop fast and accurate surrogate models for particle-based simulations. We explored applying GNS to simulate cloud droplet transport, growth, and evaporation under turbulent conditions, but we found the GNS over-smoothed the simulations. We then applied the GNS to simulate aerosol dynamics through gas condensation and found the GNS was able to reproduce the benchmark, physics-based simulation with high accuracy.

54 ENVIRONMENTAL SCIENCES↗

PUMA:POWDER UTILIZATION MODELING APPLICATION

SF-25-084 PUMA a high performance modeling framework to simulate powder processing. It provides a scalable tool for manufacturers to simulate powder pre- and post-processing. The tool can predict the distortion, residual stress, and (for reactive processes) reaction completion fraction of complex parts after curing/debinding, sintering, and infiltration processes. These predictions are key metrics industry uses to optimize these processes to produce dense, defect-free, stable components.

HU, TIANCHEN (GARY)↗

wmpy-power: A Python package for process-based regional hydropower simulation

Hydropower is an important source of renewable energy in many parts of the world. The generation potential for a hydropower facility can vary greatly due to fluctuations in precipitation and snowmelt patterns impacting streamflow and reservoir storage. Human activities such as irrigation, manufacturing, and hydration can also influence water availability at nearby and downstream facilities. wmpy-power--the hydropower model described in this work--is process-based, leveraging explicit reservoir storage and release data to address impacts on hydropower from climate change and human adaptive behaviors to inform long-term planning and resource-adequacy considerations.

13 HYDRO ENERGY↗

Influence of landscape heterogeneity on water available to tropical forests in an Amazonian catchment and implications for modeling drought response: Water Available to Tropical Forest

The Amazon basin experienced periodic droughts in the past, and climate models projected more intense and frequent droughts in the future. How tropical forests respond to drought may depend on water availability, which is modulated by landscape heterogeneity. Using the one-dimensional ACME Land Model (ALM) and the three-dimensional ParFlow variably saturated flow model, a series of numerical experiments were performed for the Asu catchment in central Amazon to elucidate processes that influence water available for plant use and provide insights for improving Earth system models. Results from ParFlow show that topography has a dominant influence on groundwater table and runoff through lateral flow. Without any representations of lateral processes, ALM simulates very different seasonal variations in groundwater table and runoff compared to ParFlow even if it is able to reproduce the long-term spatial average groundwater table of ParFlow through simple parameter calibration. In the ParFlow simulations, the groundwater table is evidently deeper and the soil saturation is lower in the plateau compared to the valley. However, even in the plateau during the dry season in the drought year of 2005, plant transpiration is not water stressed in the ParFlow simulations as the soil saturation is still sufficient to maintain a soil matric potential for the stomata to be fully open. This finding is insensitive to uncertainty in atmospheric forcing and soil parameters, but the empirical wilting formulation used in the models is an important factor that should be addressed using observations and modeling of coupled plant hydraulics-soil hydrology processes in future studies.

Fang, Yilin↗