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At least 199 records · Page 11

Advancing the science of explosive fragmentation and afterburn fireballs though experiments and simulations at the benchtop scale

Detonation of explosive devices produces extremely hazardous fragments and hot, luminous fireballs. Prior experimental investigations of these post-detonation environments have primarily considered devices containing hundreds of grams of explosives. While relevant to many applications, such large- scale testing also significantly restricts experimental diagnostics and provides limited data for model validation. As an alternative, the current work proposes experiments and simulations of the fragmentation and fireballs from commercial detonators with less than a gram of high explosive. As demonstrated here, reduced experimental hazards and increased optical access significantly expand the viability of advanced imaging and laser diagnostics. Notable developments include the first known validation of MHz-rate optical fragment tracking and the first ever Coherent Anti-Stokes Raman Scattering (CARS) measures of post-detonation fireball temperatures. While certainly not replacing the need for full-scale verification testing, this work demonstrates new opportunities to accelerate developments of diagnostics and predictive models of post-detonation environments.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Diagnostics for Linac Optimization With Machine Learning

The Fermilab Linac delivers 400 MeV H- beam to the rest of the accelerator chain. Providing stable intensity, energy, and emittance is key since it directly affects downstream machines. To counter fluctuations of Linac output due to various effects to be described below we are working on implementing dynamic longitudinal parameter optimization based on Machine Learning (ML). As inputs for the ML model, signals from beam diagnostics have to be well understood and reliable. In this paper we discuss the status and plans for ML-based optimization as well as preliminary results of diagnostics studies.

43 PARTICLE ACCELERATORS↗

AMPPED LDRD: Advanced Models of the Physics & Phenomena of Electrical Discharge.

This Laboratory Directed Research and Development (LDRD) project aimed at addressing an unmet need for physics-based models that enable prediction of electrical breakdown in the presence of high voltage gradients and real-world environments. This project focused on understanding coupled plasma-surface feedback phenomena critical to electrical discharge processes and design of breakdown voltages, breakdown times, and breakdown paths. New secondary electron emission and coupled plasma-surface measurement methods and models were developed. Highly reproducible discharge experiments were developed to provide current-voltage data as a function of time, and methods were developed to condition electrodes for predictable discharge. To assess plasma-surface feedback mechanisms, new surface physics capabilities, including measurement systems for local and global photoemission yield and ion-induced secondary electron emission yield were developed. Discharge models were developed to incorporate these yields for predicting discharge behavior to understand influence of surface physics on discharge current and time evolution, and methods to accelerate these simulations were demonstrated. A key finding was that the initiation process of a non-vacuum discharge appears highly dependent on photoemission at the cathode. Advanced diagnostics were developed, including spatial electrical field imaging, spectroscopy of plasmas, and high-speed imaging of discharge event s in metal and dielectric environments. These diagnostics and improved electrical models are a step toward enabling quantitative design margins, assurance of safety architectures, and implementation of novel materials and technologies for wide ranging energy and electronics applications.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Empirical Modeling of Direct Expansion (DX) Cooling System for Multiple Research Use Cases

This study provides a general procedure to generate a direct expansion (DX) cooling coil system for a roof top unit (RTU), which is a typical heating ventilation and air-conditioning (HVAC) system for commercial buildings in the United States. Experimental data from a full-scale unoccupied 2-story commercial building is used for the HVAC modeling. The regression for identifying the model coefficients was carried out with multiple stages, and the results were validated with measured data. The model’s applicability was evaluated with multiple case studies, including a building energy simulation (BES) program validation, model-based predictive control (MPC), and fault diagnostics and detection (FDD).

42 ENGINEERING↗

Large Ensemble Diagnostic Evaluation of Hydrologic Parameter Uncertainty in the Community Land Model Version 5 (CLM5)

Abstract Land surface models such as the Community Land Model version 5 (CLM5) seek to enhance understanding of terrestrial hydrology and aid in the evaluation of anthropogenic and climate change impacts. However, the effects of parametric uncertainty on CLM5 hydrologic predictions across regions, timescales, and flow regimes have yet to be explored in detail. The common use of the default hydrologic model parameters in CLM5 risks generating streamflow predictions that may lead to incorrect inferences for important dynamics and/or extremes. In this study, we benchmark CLM5 streamflow predictions relative to the commonly employed default hydrologic parameters for 464 headwater basins over the conterminous United States (CONUS). We evaluate baseline CLM5 default parameter performance relative to a large (1,307) Latin Hypercube Sampling‐based diagnostic comparison of streamflow prediction skill using over 20 error measures. We provide a global sensitivity analysis that clarifies the significant spatial variations in parametric controls for CLM5 streamflow predictions across regions, temporal scales, and error metrics of interest. The baseline CLM5 shows relatively moderate to poor streamflow prediction skill in several CONUS regions, especially the arid Southwest and Central U.S. Hydrologic parameter uncertainty strongly affects CLM5 streamflow predictions, but its impacts vary in complex ways across U.S. regions, timescales, and flow regimes. Overall, CLM5's surface runoff and soil water parameters have the largest effects on simulated high flows, while canopy water and evaporation parameters have the most significant effects on the water balance.

54 ENVIRONMENTAL SCIENCES↗

Data-driven model for divertor plasma detachment prediction

We present a fast and accurate data-driven surrogate model for divertor plasma detachment prediction leveraging the latent feature space concept in machine learning research. Our approach involves constructing and training two neural networks: an autoencoder that finds a proper latent space representation (LSR) of plasma state by compressing the multi-modal diagnostic measurements and a forward model using multi-layer perception (MLP) that projects a set of plasma control parameters to its corresponding LSR. By combining the forward model and the decoder network from autoencoder, this new data-driven surrogate model is able to predict a consistent set of diagnostic measurements based on a few plasma control parameters. In order to ensure that the crucial detachment physics is correctly captured, highly efficient 1D UEDGE model is used to generate training and validation data in this study. The benchmark between the data-driven surrogate model and UEDGE simulations shows that our surrogate model is capable of providing accurate detachment prediction (usually within a few per cent relative error margin) but with at least four orders of magnitude speed-up, indicating that performance-wise, it has the potential to facilitate integrated tokamak design and plasma control. Comparing with the widely used two-point model and/or two-point model formatting, the new data-driven model features additional detachment front prediction and can be easily extended to incorporate richer physics. This study demonstrates that the complicated divertor and scrape-off-layer plasma state has a low-dimensional representation in latent space. Understanding plasma dynamics in latent space and utilising this knowledge could open a new path for plasma control in magnetic fusion energy research.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Tensile Property and Lifetime Prediction for Low-Temperature Aged Uranium-Niobium Alloys

Thermal aging models and lifetime predictions for uranium-niobium (U-Nb) alloys were created using an approach similar to those previously employed. Lifetime estimates for generic U-6Nb components were thus updated; the reported value being 800 years. This update represents a small change in lifetime vs. that of the 2012 assessment (540 years). This lifetime estimate emerged from consideration of several model fits specific to the aging datasets and properties chosen. Aging was quantified using quasi-static tensile properties measured on specimens artificially aged for up to 10 years. The major change relative to the most recent 2012 LANL assessment was that a more comprehensive body of U-Nb literature data was mined, in addition to being augmented by the latest LANL and UK AWE data. The tensile data compilation was published separately (LANL report LA-14493, December 2016). Recognizing the chemical banding of industrially produced U-6Nb, models were developed for the mid-range (6 wt.%) and extrema (4 and 8 wt.%) compositions. Lifetime estimates were calculated for all three alloy classes (4, 6, 8 wt.% nominal) and two measures of total tensile elongation (TE) to failure, namely TE-ext. — extensometer method, and TE-NCD — normalized crosshead displacement method. The conservative assumption was made that whichever composition (4, 6, or 8 wt.% Nb) and property (TE-ext or TE-NCD) was the first to cross the ductility failure threshold would limit the lifetime of the entire component. Tensile strength properties did not figure into the lifetime predictions, but could be useful as age-sensitive diagnostics and were also modeled. Of these, only first yield strength is expected to show a change at 40°C aging vs. time = 0 over the ~100-year timespan of engineering interest. Second yield strength evolves more slowly, and ultimate tensile strength slower still. Among all the models, the apparent activation energies for aging were mostly in the narrow 29– 37 kcal/mol range, which is close to that for diffusion of Nb in gamma-uranium. This agreement may be coincidental. The data from recent long-term aging studies substantially improved the model fit quality and robustness of the lifetimes. Appendices document sensitivity studies of the model fits and lifetimes with respect to using more limited datasets. These results highlight the limitations of relying solely on data from scattered literature studies and smaller datasets more generally.

36 MATERIALS SCIENCE↗

The collapse and three-dimensional explosion of three-dimensional massive-star supernova progenitor models

ABSTRACT The explosion outcome and diagnostics of core-collapse supernovae depend sensitively on the nature of the stellar progenitor, but most studies to date have focused exclusively on one-dimensional, spherically symmetric massive star progenitors. We present some of the first core-collapse supernovae simulations of three-dimensional massive star supernovae progenitors, a 12.5- and a 15-M⊙ model, evolved in three dimensions from collapse to bounce through explosion with the radiation-hydrodynamic code fornax. We compare the results using those starting from three-dimensional progenitors to three-dimensional simulations of spherically symmetric, one-dimensional progenitors of the same mass. We find that the models evolved in three dimensions during the final stages of massive star evolution are more prone to explosion. The turbulence arising in these multidimensional initial models serves as seed turbulence that promotes shock revival. Detection of gravitational waves and neutrinos signals could reveal signatures of pre-bounce turbulence.

79 ASTRONOMY AND ASTROPHYSICS↗

Design study of a combined interferometer and polarimeter for a high-field, compact tokamak

This article is the first design study of a combined interferometer and polarimeter on a compact, high-field, high-density, net-energy tokamak. Recent advances in superconducting technology have made possible designs for compact, high magnetic field fusion power plants, such as ARC [Sorbom et al., Fusion Eng. Des. 100, 378 (2015)], and experiments, such as SPARC [Greenwald et al., PSFC Report No. RR-18-2 (2018)]. These new designs create both challenges and opportunities for plasma diagnostics. The diagnostic proposed in this work, called InterPol, takes advantage of unique opportunities provided by high magnetic field and density to measure both line-averaged density and poloidal magnetic field with a single set of CO 2 and quantum cascade lasers. These measurements will be used for fast density feedback control, constraint of density and safety factor profiles, and density fluctuation measurements. Synthetic diagnostic testing using a model machine geometry, called MQ1 (Mission Q ≥ 1), and profiles simulated with Tokamak Simulation Code indicate that InterPol will be able to measure steady state density and poloidal magnetic field, as well as fluctuations caused by toroidal Alfven eigenmodes and other phenomena on a high-field compact tokamak.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Reconstruction and interpretation of ionization asymmetry in magnetic confinement via synthetic diagnostics

Abstract Strong poloidal refueling asymmetry in the DIII-D tokamak is inferred from line radiation measurements. Synthetic diagnostics in neutral transport modeling coupled to gyrokinetic simulations illuminate implications for the plasma flow profile in the scrape-off layer of single-null beam-driven discharges. Recycling occurs primarily either on the inner or outer divertor legs, depending on the toroidal magnetic field direction. By reversing the toroidal magnetic field, the observed line radiation asymmetry is nearly eliminated or reversed. It is determined that, while relatively simple physics can describe the observed ionization asymmetry, predicting the overall brightness of the hydrogenic Lyman- α signal requires detailed simulation of the plasma and resulting turbulence. To this end, kinetic plasma simulations fully coupled to comprehensive neutral transport calculations—a novel capability—provide first-principles reproduction of Lyman- α observations on DIII-D.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Time-resolved measurements of HO 2 radical in a heated plasma flow reactor

Time-resolved, absolute HO 2 number density in diluted H 2 –O 2 –Ar, CH 4 –O 2 -Ar, and C 2 H 4 –O 2 –Ar mixtures excited by a repetitive ns pulse discharge in a heated plasma flow reactor is measured by Cavity Ringdown Spectroscopy (CRDS). The experimental results are obtained at $\textit{T}$ = 300-600 K and $\textit{P}$ = 130 Torr, both during the discharge pulse burst and in the afterglow. In this work, the HO 2 number density is inferred from the CRDS data using a spectral model exhibiting good agreement with previous measurements of absolute HO 2 absorption cross sections. In the room-temperature H 2 –O 2 mixture, as well as in CH 4 –O 2 and C 2 H 4 –O 2 mixtures over the entire temperature range studied, HO2 is generated only during the discharge burst and decays in the afterglow. However, in the H 2 –O 2 mixture at elevated temperatures, $\textit{T}$ = 400-600 K, HO 2 persists in the afterglow up to 10 ms after the discharge burst, comparable with the flow residence time in the reactor. Comparison with kinetic modeling shows that the sustained reactivity after the source of radicals is turned off is due to a chain propagation / hydrogen oxidation process, which dominates the radical recombination reactions. The kinetic modeling predictions are in good agreement with the relative HO 2 number density measured in all three mixtures, although the model underpredicts the absolute number densities in H 2 –O 2 at $\textit{T}$ = 400-600 K by up to a factor of two. Detection of the sustained low-temperature reactivity in H 2 –O 2 , initiated by the radical generation in the plasma, suggests that the plasma excitation may also affect kinetics of oxidation and reforming of fuels exhibiting low-temperature chemistry below hot ignition point.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Computational modeling and neutron imaging to understand interface shape and solute segregation during the vertical gradient freeze growth of BaBrCl:Eu

In this work we apply continuum models to analyze phase change, heat transfer, fluid flow, solute transport, and segregation in order to understand prior neutron imaging observations of the vertical gradient freeze growth of Eu-doped BaBrCl. The models provide a rigorous framework in which to understand the mechanisms that are responsible for the complicated evolution of interface shape and dopant distribution in the growth experiment. We explain how a transition in the solid/liquid interface shape from concave to convex is driven by changes in radial heat transfer caused by furnace design. We also provide a mechanistic explanation of how dynamic growth conditions and changes of the flow structure in the melt result in complicated segregation patterns in this system. A growth pause caused by controller lock-up is shown to result in a band of solute depletion in accordance with classical theory. However, changing flow patterns during growth result in a non-monotonic axial distribution of solute that cannot be explained by simple application of classical segregation models. We assert that the approach presented here, namely the use of rigorous models in conjunction advanced diagnostics, such as neutron imaging, provides an exciting path forward for process optimization and control, accelerating the incremental advances that have, in the past, typically relied on empiricism, experience, and intuition.

36 MATERIALS SCIENCE↗

Grooved electrodes for high-power-density fuel cells

Proton exchange membrane fuel cells (PEMFCs) are leading candidates to decarbonize the transport sector, but widespread deployment will require improvements in lifetime, fuel economy and cost. Here we present the grooved electrode, an alternative electrode structure that enhances PEMFC performance and durability by coupling high ionomer (ion-conducting binder) content for improved H + transport with grooves for rapid O 2 transport. Grooved electrodes provide up to 50% higher performance than state-of-the-art conventional electrodes under standard operating conditions. Fuel cell diagnostics combined with multiphysics modelling demonstrate that grooved electrodes provide facile O 2 transport despite their high ionomer content, enabling improved reaction rate uniformity. Grooved electrodes also provide improved durability, with less performance loss after carbon corrosion compared with baseline electrodes. Machine learning analysis demonstrates the potential to further optimize grooved structures for next-generation PEMFCs with enhanced performance and durability, enabling smaller and cheaper fuel cell stacks with higher fuel efficiency.

25 ENERGY STORAGE↗

Disentangling multiple gas kinematic drivers in the Perseus galaxy cluster

Galaxy clusters, the Universe’s largest halo structures, are filled with an X-ray-emitting gas with a temperature between 10 million and 100 million degrees. Their evolution is shaped by energetic processes such as feedback from supermassive black holes (SMBHs) and mergers with other cosmic structures. The imprints of these processes on gas kinematics remain largely unknown, restricting our understanding of energy conversion within clusters4. High-resolution spectral mapping with the X-Ray Imaging and Spectroscopy Mission (XRISM) observatory offers a way forward. Here we present XRISM kinematic measurements of the Perseus cluster, radially covering the extent of its cool core. We find direct evidence for at least two dominant drivers of gas motions operating on distinct physical scales: a small-scale driver in the inner approximately 60 kpc, probably associated with the SMBH feedback; and a large-scale driver in the outer core, powered by mergers. This finding suggests that, during the active phase, SMBH feedback drives gas motions, which, if fully dissipated into heat, could have a substantial role in offsetting radiative cooling losses in the Perseus core. Furthermore, our study underscores the necessity of kinematic mapping observations of extended sources to robustly characterize the velocity fields and their role in the evolution of massive halos. It further offers a kinematic diagnostic for SMBH feedback models.

Astronomy and AstroPhysics↗

Runaway electron-induced plasma facing component damagein tokamaks

This Roadmap article addresses the critical and multifaceted challenge of plasma facing component (PFC) damage caused by runaway electrons (REs) in tokamaks, a phenomenon that poses a significant threat to the viability and longevity of future fusion reactors such as ITER and DEMO. The dramatically increased RE production expected in future high-current tokamaks makes it very difficult to avoid or mitigate REs in such devices when a plasma discharge terminates abnormally. Preventing damage from the intense localised heat loads they can cause requires a holistic approach that considers plasma, REs and PFC damage. Despite decades of progress in understanding the physics of REs and the thermomechanical response of PFCs separately, their complex interplay remains poorly understood. This document aims to initiate a coordinated, interdisciplinary approach to bridge this gap by reviewing experimental evidence, advancing diagnostic capabilities, and improving modelling tools across different scales, dimensionalities, and fidelities. Key topics include RE beam formation and transport, damage mechanisms in both brittle and metallic PFCs, and observed effects in major facilities such as JET, DIII-D, WEST and EAST. The Roadmap emphasises the urgency of predictive, high-fidelity modelling validated against well-diagnosed controlled experiments, particularly in the light of recent changes in ITER’s wall material strategy and the growing importance of private sector fusion initiatives. Each section of the Roadmap article is written to provide a concise overview of one area of this multidisciplinary subject, with an assessment of the status, a look at current and future challenges, and a brief summary. The ultimate goal of this initiative is to guide future mitigation strategies and design resilient components that can withstand the intense localised loads imposed by REs, thus ensuring the safe and sustainable operation of the next generation of fusion power plants.

Ratynskaia, Svetlana [KTH Royal Inst. of Technolog↗

Facilitating Machine Learning Collaborations Between Labs, Universities, And Industry

It is clear from numerous recent community reports, papers, and proposals that machine learning is of tremendous interest for particle accelerator applications. The quickly evolving landscape continues to grow in both the breadth and depth of applications including physics modeling, anomaly detection, controls, diagnostics, and analysis. Consequently, laboratories, universities, and companies across the globe have established dedicated machine learning (ML) and data science efforts aiming to make use of these new state-of-the-art tools. The current funding environment in the U.S. is structured in a way that supports specific application spaces rather than larger collaboration on community software. Here, we discuss the existing collaboration bottlenecks and how a shift in the funding environment, and how we develop collaborative tools, can help fuel the next wave of ML advancements for particle accelerators.

Edelen, J.P.↗

Phase Contrast Imaging Diagnostic on DIII-D (1994-2007); Phase Contrast Imaging Diagnostic on DIII-D and Alcator C-Mod (2007-2010); Experimental Study of Waves, Turbulence and Transport, and Model Validation with Phase Contrast Imaging on DIII-D and Alcator C-Mod (2010-2012); Phase Contrast Imaging Diagnostic Upgrade on DIII-D for Measuring High-k Turbulence and Alfven modes (2021-2016); Phase Contrast Imaging Diagnostic Upgrade on DIII-D for Full Multi-Scale Measurements (2016-2020) (Final Report)

This report describes the first twenty-five years of development and use of the Phase Contrast Imaging (PCI) diagnostic for measuring plasma fluctuations on the DIII–D tokamak. One of the key challenges in moving tokamak technology forward to the stage of a nuclear reactor remains understanding how energy and particles are transported across the magnetic field by the action of turbulence and waves, and PCI provides a highly flexible and capable measurement of these fluctuations. The PCI diagnostic uses a laser beam to probe the plasma and optical filtering to produce an amplitude variation on a linear detector array which provides an image of the density waves in the plasma. The PCI covers an exceptional range in frequency and wavelength of the measured fluctuations, allowing observation of plasma-sized magnetohydrodynamic (MHD) modes and ion- and electron-scale turbulence. Modulation of the beam amplitude allows measurement of radio frequency (RF) waves.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Understanding Dynamics and Thermodynamics of ENSO and Its Complexity Simulated by E3SM and Other Climate Models

Despite the seeming success of most state-of-the-art climate models in simulating the El Niño-Southern Oscillation (ENSO), there is strong evidence that models achieve realistic levels of ENSO activity do so often for wrong reasons. This is owing to an often occurred near cancelation of large errors in terms of contributions to ENSO growth rate from coupled dynamic and thermodynamic feedback processes. Climate models remain deficient in simulating the observed ENSO’s spatial and temporal complexity that involves interplays of coupled dynamic and thermodynamic feedbacks, interactions across multiple scales, nonlinear processes in the tropical atmosphere and ocean system, biases in mean sate and physical processes, and influences external to equatorial Pacific coupled ENSO dynamics. Our proposed research aims at advancing predictive and process-level understandings of ENSO simulated in E3SM and other climate models under current and future climate conditions with two main objectives: (i) better understanding the aforementioned broad range interactive processes and sources that control fundamental properties of ENSO in E3SM and CIMP6 outputs as well as in observational (reanalysis) data sets, using a hierarchical of coupled dynamical frameworks consisting of theoretical analysis, intermediate complexity modeling, and coupled dynamic diagnostics; (ii) to use this understanding to explore pathways towards improving E3SM’s capability of simulating ENSO and its complexity. More specifically, we will focus on four main thrusts of research: (1) ENSO’s dynamic and thermodynamic feedbacks; (2) the across-scale interactions of ENSO with annual cycle and MJO/WWB/TIW (Madden Julian Oscillation/Westerly Wind Burst/Tropical Instability Wave) activity; (3) key nonlinear processes of ENSO involving atmospheric convective thresholds, nonlinear ocean dynamic heating, and thermocline outcropping; and (4) the impacts of climate mean-state biases/changes and perturbed physical processes on simulated ENSO and its complexity.

54 ENVIRONMENTAL SCIENCES↗