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DOE OSTI2024

High performance power handling in the absence of an H-mode edge in negative triangularity DIII-D plasmas

Abstract Experiments performed during strongly-shaped high-power diverted negative triangularity (NT) experiments in DIII-D achieved detached divertor conditions and a transient-free edge, showcasing the potential for application of NT to a core-edge integrated reactor-like scenario and providing the first characterization of the parametric dependencies for detachment onset. Detached divertor conditions will be required in future devices to mitigate divertor heat fluxes. Access to dissipative divertor conditions was investigated via an increase in upstream density. Detachment onset at the outer strike point was achieved with H-mode level confinement H 98 − y 2 ∼ 1 and reactor-relevant normalized pressures β N ∼ 2 . Confinement degradation was observed with deeper detachment, associated with the loss of an electron temperature pedestal. Differences in geometry, radial transport, impact of cross field drifts are discussed to explain differences in access to detachment in NT discharges. Higher normalized densities, with respect to equivalent discharges in positive triangularity, were necessary to achieve detachment, partially explained by the shorter parallel connection length to the targets. The effect of cross-field particle drifts ( E × B , B × ∇ B ) on access to detachment was demonstrated by the lower upstream density needed to access detachment with ion B × ∇ B drift directed outside of the active divertor (Greenwald fraction f Gw ∼ 0.9–1.0 vs f Gw ∼ 1.3). The upstream density at detachment onset was observed to increase linearly with plasma current with ion B × ∇ B drift into the divertor, consistent with the observed narrowing of the scrape-off layer heat flux width λ q . Edge fluid simulations capture separatrix densities needed to achieve detachment in NT plasma and their dependence on drift direction. The ability to reproduce detachment dynamics in NT plasma increases the confidence in future design studies for NT divertors.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Validation of prediction capability of operating space for plasma initiation in MAST-U

DYON is a plasma initiation modelling code that solves the differential equation system of the full circuit equations (plasma current, active coil currents and eddy currents in full passive structures) and 0D global energy and particle balance equations (Kim 2022 Nucl. Fusion 62 126012). In order to test the capability of the full electromagnetic plasma initiation model to predict individual discharges in experiments and thus the operating space in the device, a dedicated experimental database was built in MAST-U by scanning the prefilled gas pressure p 0 and the induced loop voltage V loop . In the experimental operating space of p 0 and V loop the lower and the upper limits of p 0 are determined by the plasma breakdown failure and the plasma burn-through failure, respectively. The lower limit of V loop is determined by the plasma burn-through failure. By directly reading the control room data used in each discharge (i.e. currents in the solenoid, poloidal field coils, and toroidal field coils, p 0 , and gas puffing rate), the full electromagnetic DYON consistently predicted the failed breakdown, failed burn-through, and successful plasma initiation discharges in the experimental database, demonstrating its capability to predict the operating space for inductive plasma initiation. The Paschen curve calculated with the effective connection length in MAST-U indicates a much higher p 0 required for plasma breakdown than the experimental data, indicating that individual field line evaluation is necessary to calculate the quantitative requirements for Townsend breakdown. The demonstration in this paper shows that the full electromagnetic DYON could be a useful simulation tool to assess the feasibility of inductive plasma initiation and to optimise operating scenarios in future devices.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2022

Suppression of first-wall interaction in negative triangularity plasmas on TCV

Magnetically confined fusion plasmas with negative triangularity (d) exhibit greater L-mode confinement than with positive d. Recent experiments in the TCV and DIII-D tokamaks have correlated the confinement improvement to a reduction of fluctuations within the plasma core. We report on fluctuation measurements in the scrape-off layer (SOL) for −0.61 < d < +0.64 in limited and diverted ohmic L-mode plasmas; these reveal a strong reduction in SOL fluctuation amplitudes at d < −0.25, and, surprisingly, an almost full suppression of plasma interaction with the main-chamber first-wall, which could have important implications for the prospects of using negative d plasmas as a reactor solution. An exploration of several physical mechanisms suggests that a reduced connection length—intrinsic to negative d plasmas—plays a critical role in the origin of this phenomenon.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Entanglement Capacity Estimates and Throughput Measurements of Quantum Channels

The throughput is an important performance metric of entangled qubit distribution quantum networks, and may be characterized by the number of distributed entangled qubit pairs per second (ebps). It is measured over physical quantum network connections using specialized instruments, including photonic entanglement sources and single photon detectors. Extensive theory has been developed to estimate the entangled qubit capacity of quantum channels using abstractions of physical connections. These two quantities both characterize the throughput performance but in different ways, and typically have been hard to relate to each other in concrete terms, in part due to the lack of precise measurements with matching analytical models and derivations. We describe measurements on a physical testbed with fiber connections of lengths 0-75 kilometers. We obtain the normalized analytic capacity estimates using the transmissivity approximations derived using single photon coincidence measurements, and convert them to bounds on throughput (measured in ebps) using a multiplier derived from co-located detector measurements. The results indicate consistent throughput measurements upper-bounded by their analytical capacity estimates across all connections. We show that previous capacity estimates using light measurements are below ebps measurements for some connections, due to the inclusion of non-representative decrease of light levels outside C-band with distance.

Rao, Nageswara↗

DOE OSTI2026

The Role of Land‐Atmosphere Feedbacks in Midlatitude Wintertime Surface Temperature Variability

Accurately representing synoptic near-surface temperature variability is crucial to predict weather extremes, yet models remain biased. Existing studies primarily attribute wintertime midlatitude near-surface temperature variability to tropospheric large-scale advection, assuming minimal land influence. However, nudging the model's circulation toward observations yields little improvement in wintertime temperature variance over Northern Hemisphere land, suggesting that land-atmosphere interactions also warrant attention. We introduce a new scaling framework for temperature variance that incorporates local land-atmosphere feedbacks. Comparing our framework to the mixing length approach—which links temperature variance to the meridional temperature gradient and air parcel displacement (mixing length)—shows that land-atmosphere feedbacks are inherently embedded in the mixing length, a connection previously overlooked. Roles of land–atmosphere feedbacks are evaluated via model experiments with perturbed circulation, land, or both. We find that longwave radiative damping dominates temperature variance responses over meridional temperature gradient when both land and circulation are perturbed.

atmosheric science↗

DOE OSTI2024

DLSIA: Deep Learning for Scientific Image Analysis

DLSIA (Deep Learning for Scientific Image Analysis) is a Python-based machine learning library that empowers scientists and researchers across diverse scientific domains with a range of customizable convolutional neural network (CNN) architectures for a wide variety of tasks in image analysis to be used in downstream data processing. DLSIA features easy-to-use architectures, such as autoencoders, tunable U-Nets and parameter-lean mixed-scale dense networks (MSDNets). Additionally, this article introduces sparse mixed-scale networks (SMSNets), generated using random graphs, sparse connections and dilated convolutions connecting different length scales. For verification, several DLSIA-instantiated networks and training scripts are employed in multiple applications, including inpainting for X-ray scattering data using U-Nets and MSDNets, segmenting 3D fibers in X-ray tomographic reconstructions of concrete using an ensemble of SMSNets, and leveraging autoencoder latent spaces for data compression and clustering. As experimental data continue to grow in scale and complexity, DLSIA provides accessible CNN construction and abstracts CNN complexities, allowing scientists to tailor their machine learning approaches, accelerate discoveries, foster interdisciplinary collaboration and advance research in scientific image analysis.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

A Hydrokinetic Energy Conversion System using Underwater LLC-type Resonant Converter

The hydrokinetic energy of river and ocean currents is a valuable renewable energy resource. Conventional systems for harvesting hydrokinetic energy usually have bulky passive components, lengthy cables connecting the underwater turbine/generator with onshore power converters, and limited control over power generation. This paper presents a new hydrokinetic energy harvesting system using an LLC-type resonant converter that is placed underwater in close proximity to the generator. By using SiC devices and the soft switching characteristic of LLC resonant converter, the converter operates in 10s of kHz, significantly reducing the passive components. In addition, the LLC converter provides flexible power regulation of the system. Furthermore, the underwater placement of the power converter takes advantage of the cooling provided by the water and simplifies the system by reducing its connecting cable length.

Dai, Hang↗

DOE OSTI2023

Throughput Measurements and Capacity Estimates for Quantum Connections

The throughput of conventional and quantum network connections is an important performance metric, which is typically specified by bits per second (bps) and entangled quntum bits per second (ebps), respectively. It is measured over practical quantum network connections using specialized methods, and estimated using analytical bounds for which extensive theory has been developed. For practical connections, however, these two quantities have often been hard to correlate due to the lack of measurements and estimates derived under well-characterized common conditions. They both differ significantly from the conventional network throughput of TCP which employs buffers and loss recovery mechanisms. We describe a conventional-quantum testbed that enables the comparison of these two quantities both qualitatively and quantitatively. The bps and ebps throughput is measured over fiber connections of lengths over 75 kilometers, which show that the former decreases significantly slower with distance than the latter and in a qualitatively different way. The analytic capacity estimates of ebps are derived using approximations based on light intensity measurements, and they decrease more rapidly with distance than the measured ebps throughput. These results provide qualitative insights into the conventional transport mechanisms based on buffers, and the conditions used in deriving the analytical ebps capacity estimates.

Rao, Nageswara↗

DOE OSTI2025

Dual-Comb Spectroscopy to Tethered Balloon System (DCS to TBS) Field Campaign Report

There is a critical need for the ability to detect, quantify, and attribute sources and sinks of greenhouse gases (GHGs) with high temporal and spatial resolution. Current methods are typically based on continuously operating near-surface point sensors or intermittent aerial/satellite observations. Dual optical frequency comb spectroscopy (“dual-comb spectroscopy”; DCS) is a laser-based technique that can bridge this sensing gap by providing high-precision, high-accuracy, and high-temporal-resolution detection and quantification of trace gases over kilometer-length scales, connecting local and regional observations. A single DCS system can also provide spatial resolution for source/sink attribution with the addition of a few minor optical elements, enabling cross-validation of other observations (e.g., Total Carbon Column Observing Network [TCCON], Orbiting Carbon Observatory [OCO-2/3], Greenhouse Gases Observing Satellite [GOSAT-1/2][).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Dynamic Queue Prediction at Signalized Intersections with Fusing Sensory Information and Connected Vehicles

Queue length is one of the most essential metrics for indicating traffic conditions at signalized intersections. Most existing studies mainly focus on queue length estimation in a retrieving way which cannot effectively predict the future state of vehicle in queue. This paper proposes an innovative dynamic queue prediction model in a vehicle-infrastructure cooperative way. The proposed dynamic queue predictor can customize the queue prediction using the trajectories of preceding vehicles from radar detection with varying information from loop detectors and connected vehicles (CVs). The dynamic queue prediction accuracy can be further improved with at least one present CV in the same cycle. With the accurate dynamic queue prediction, we present a case study of Queue-Aware Eco-Approach and Departure (QEAD) to provide an online optimal vehicle trajectory considering both the signal status and preceding vehicle's future status in queue. The proposed framework and algorithms are of pragmatic significance and one of its advanced features is the ability to work under low penetration rate of CVs. The test using Next Generation SIMulation (NGSIM) dataset and a case study in VISSIM microscopic simulation show promising results.

Ye, Fei↗

DOE OSTI2020

Hydrothermally carbonized biomass formed via reactive twin-screw extrusion

A biomass-derived thermosetting polymer material being a product of processing a biomass feed material via a twin screw extruder having a length extending between an inlet and an outlet. Hot water from a water heater is injected into at least one inlet along the length of the twin screw extruder, the at least one inlet generally corresponding with a pressure boundary within the twin screw extruder. A pressure-sustaining valve is connected between the length of the twin screw extruder and the outlet, with the valve being adjusted to produce the biomass-derived thermosetting polymer material.

09 BIOMASS FUELS↗

DOE OSTI2020

Connecting Hindered Transport in Porous Media across Length Scales: From Single-Pore to Macroscopic

Hindered mass transport is widely observed in various porous media, including filtration membranes and porous rocks. However, there is no universal model capable of predicting transport in porous media due to the heterogeneity of porous structures and the complexity of the underlying microscopic mechanisms, including electrostatic and hydrodynamic effects. Here, we used a highly ordered porous medium (i.e. a silica inverse opal film) as a model system to directly explore the effects of geometric parameters (i.e. pore size, pore throat size and tracer particle size) and microscopic interaction parameters (e.g. controlled by ionic strength) on nanoparticle transport in porous environments using three-dimensional single-particle tracking. We found a linear scaling relation between the macroscopic diffusion coefficient and microscopic diffusion behaviors and a combination of parameters associated with microscopic features and phenomena, including both geometric effects and particle-level interactions. The proportionality coefficient relating micro and macro behaviors was complex and related to the connectivity of the matrix and pore-size variation, which could lead to tortuous diffusion pathways, hindering macroscopic transport. Furthermore, these findings provide important insights into nanoparticles and macromolecules transport in various porous media.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Collapse of the waiting time effect in a spin glass

Waiting time measurements are reported here for a bulk polycrystalline sample of the spin glass Cu 0.95 Mn 0.05 . We observe a suppression of aging as the glass temperature is approached from below. These results are interpreted in terms of a spin-glass correlation length approaching and reaching crystallite sizes. They provide a direct experimental connection between the correlation length scale and relaxation times in the spin-glass state. In particular, these measurements track the value of the dynamic critical exponent as the system transitions from the critical temperature regime to its low-temperature, quasistatic nonequilibrium phase.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2020

Renormalization and scale evolution of the soft-quark soft function

Soft functions defined in terms of matrix elements of soft fields dressed by Wilson lines are central components of factorization theorems for cross sections and decay rates in collider and heavy-quark physics. While in many cases the relevant soft functions are defined in terms of gluon operators, at subleading order in power counting soft functions containing quark fields appear. We present a detailed discussion of the properties of the soft-quark soft function consisting of a quark propagator dressed by two finite-length Wilson lines connecting at one point. This function enters in the factorization theorem for the Higgs-boson decay amplitude of the h → γγ process mediated by light-quark loops. We perform the renormalization of this soft function at one-loop order, present a conjecture for its two-loop anomalous dimension and discuss solutions to its renormalization-group evolution equation in momentum space, in Laplace space and in the “diagonal space”, where the evolution is strictly local in the momentum variable.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

Quantifying the effect of hydride microstructure on zirconium alloys embrittlement using image analysis

Since hydride microstructure can significantly influence Zr alloy nuclear fuel cladding’s ductility, a new metric has been developed to quantify hydride microstructure in 2D micrographs and relate it to crack propagation. As cladding failure usually results from a hoop stress, this new metric, called the Radial Hydride Continuous Path (RHCP), is based on quantifying the continuity of brittle hydride particles along the radial direction of the cladding tube. Compared to previous metrics, this approach more closely relates to the propensity of a crack to propagate radially through the cladding tube thickness. The RHCP takes into account hydride length, orientation, and connectivity to choose the optimal path for crack propagation through the cladding thickness. The RHCP can therefore be more closely linked to hydride embrittlement of the Zr alloy material, thus creating a relationship between material structure, properties, and performance. The new definition, along with previously proposed metrics such as the Radial Hydride Fraction (RHF), the Hydride Continuity Coefficient (HCC), and the Radial Hydride Continuity Factor (RHCF), have been implemented and automated in MATLAB. These codes are made available with this publication as supplementary materials. These metrics were verified by comparing their predictions of hydride morphology against expected values in simple cases, and the implementation of the new metric was validated by comparing its predictions with manual measurements of hydride microstructure performed on ImageJ. The RHCP was also validated against experimental measurements of fracture behavior and it was shown to correlate with cladding failure better than previous metrics. The information provided by these metrics will help accurately assess cladding integrity during operation, transportation, and storage.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Self-Assembled Thermoresponsive Molecular Brushes as Nanoreactors for Asymmetric Aldol Addition in Water

The manipulation and tunability of self-assembled block copolymers through external stimuli presents an attractive strategy to develop smart polymer-based nanoreactors as supports for non-orthogonal tandem catalysis. We report on thermoresponsive core-shell micelles based on poly[norbornene-poly(2-methyl-2-oxazoline-block-2-propyl-2-oxazoline)]-graft-poly[norbornene L-proline] (P[NB-P(MeOx-b-PropOx)]-graft-P[NB-L-proline]) as catalyst supports for L-proline. These molecular brushes exhibit large differences in lower critical solution temperature behavior and nanostructure size in water depending on the chain-lengths and proline connectivity. L-Proline-mediated aldol reactions expose the efficiency by which the molecular brushes self-assemble into micelles. Molecular brushes with an extended backbone show higher activity and selectivity, suggesting better core-shell segregation of the micelles and exclusion of water from the catalytic site. Catalytic efficiencies are not improved above the cloud point temperature, the catalytic be-havior is rather sensitive to conformational changes of the polymer chains.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Poly(ionic liquid)s with Dicationic Pendants as Gas Separation Membranes

Poly(norbornene)s and poly(ionic liquid)s are two different classes of attractive materials, which are known for their structural tunability and thermal stabilities, and have been extensively studied as gas separation membranes. The incorporation of ionic liquids (ILs) into the poly(norbornene) through post-polymerization has resulted in unique materials with synergistic properties. However, direct polymerization of norbornene-containing IL monomers as gas separation membranes are limited. To this end, a series of norbornene-containing imidazolium-based mono- and di-cationic ILs (NBM-mIm and NBM-DILs) with different connectivity and spacer lengths were synthesized and characterized spectroscopically. Subsequently, the poly(NBM-mIm) with bistriflimide [Tf2N−] and poly([NBM-DILs][Tf2N]2) comprising homo-, random-, and block- (co)polymers were synthesized via ring-opening metathesis polymerization using the air-stable Grubbs second-generation catalyst. Block copolymers (BCPs), specifically, [NBM-mIM][Tf2N] and [NBM-ImCnmIm] [Tf2N]2 (n = 4 and 6) were synthesized at two different compositions, which generated high molecular weight polymers with decent solubility relative to homo- and random (co)polymers of [NBM-DILs] [Tf2N]2. The prepared BCPs were efficiently analyzed by a host of analytical tools, including 1H-NMR, GPC, and WAXD. The successfully BCPs were cast into thin membranes ranging from 47 to 125 μm and their gas (CO2, N2, CH4, and H2) permeations were measured at 20 °C using a time-lag apparatus. These membranes displayed modest CO2 permeability in a non-linear fashion with respect to composition and a reverse trend in CO2/N2 permselectivity was observed, as a usual trade-off behavior between permeability and permselectivity.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Multielectrode sensor for concentration and depth measurements in molten salt

A multi electrode sensor that provides in-situ, real time measurements for molten salts and other process fluids such as real-time concentration and salt level measurements for nuclear systems such as molten salt reactors, nuclear reprocessing facilities utilizing molten salts and concentrated solar power systems. The sensor has multiple electrodes with unique lengths which are connected to a potentiostat. Measurements are taken when the electrodes are immersed in the process fluid.

Hoyt, Nathaniel C.↗