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At least 865 records · Page 48

Time-discretization of a plasma-neutral MHD model with a semi-implicit leapfrog algorithm

The semi-implicit leapfrog time-discretization is a workhorse algorithm for initial-value MHD codes to bridge between vastly separated time scales. Inclusion of atomic interactions with neutrals breaks the functional structure of the MHD equations that exploited by the leapfrog. In this work, we address how to best integrate atomic physics into the semi-implicit leapfrog. Following the Crank-Nicolson method, one approach is to time-center the atomic interactions in the linear solver and use a Newton method to include the nonlinear contributions. Alternatively, another family of methods are based on operator-splitting the terms associated with the atomic interactions using a Strang-splitting technique. These methods naturally break equations into constituent ODE and PDE parts and preserve the structure exploited by the semi-implicit leapfrog. We study the accuracy and efficiency of these methods through a battery of 0D and 1D cases and show that a second-order-in-time Douglas-Rachford inspired coupling between the ODE and PDE advances is effective in reducing the time-discretization error to be comparable to that of Crank-Nicolson with Newton iteration of the nonlinear terms. Splitting ODE and PDE parts results in independent matrix solves for each field which reduces the computational cost considerably and provides parallelization over species relative to Crank-Nicolson.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

INSPIRED: Inelastic neutron scattering prediction for instantaneous results and experimental design

Inelastic neutron scattering (INS) has unique advantages in probing how atoms vibrate and how the vibrations propagate and interact. Such dynamic information is crucial in understanding various material properties, from heat capacity, thermal conductivity, phase transitions, and chemical reactions to more exotic quantum behavior. The analysis and interpretation of the INS spectra often start from a model structure of the sample, followed by a series of calculations to obtain the simulated spectra to compare with experiments. The conventional way to perform such calculations usually requires significant time, computing resources, and specialized expertise. Here, we present a new program named INSPIRED (Inelastic Neutron Scattering Prediction for Instantaneous Results and Experimental Design), which enables users to perform rapid INS simulations in several different ways on their personal computers in just a few clicks, with the crystal structure as the only input file. Specifically, the users can choose a pre-trained symmetry-aware neural network (coupled with an autoencoder) to predict the phonon density of states (DOS), 1D S(E) and 2D S(|Q|,E) spectra for any given structure. One can also choose an existing density functional theory (DFT) calculation from a database (containing over 12,000 crystals), and quickly obtain the simulated INS spectra for single crystals and powders. It is also possible to use pre-trained universal machine learning force fields to relax a given crystal structure, calculate the phonon dispersion and DOS, and, subsequently, the INS spectra. All these functions are implemented with a PyQt graphic user interface. Finally, we expect these new tools will benefit broad user communities and significantly improve the efficiency of experiment design, execution, and data analysis for INS.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

GPU-enabled extreme-scale turbulence simulations: Fourier pseudo-spectral algorithms at the exascale using OpenMP offloading

Fourier pseudo-spectral methods for nonlinear partial differential equations are of wide interest in many areas of advanced computational science, including direct numerical simulation of three-dimensional (3-D) turbulence governed by the Navier-Stokes equations in fluid dynamics. This paper presents a new capability for simulating turbulence at a new record resolution up to 35 trillion grid points, on the world's first exascale computer, Frontier, comprising AMD MI250x GPUs with HPE's Slingshot interconnect and operated by the US Department of Energy's Oak Ridge Leadership Computing Facility (OLCF). Key programming strategies designed to take maximum advantage of the machine architecture involve performing almost all computations on the GPU which has the same memory capacity as the CPU, performing all-to-all communication among sets of parallel processes directly on the GPU, and targeting GPUs efficiently using OpenMP offloading for intensive number-crunching including 1-D Fast Fourier Transforms (FFT) performed using AMD ROCm library calls. With 99% of computing power on Frontier being on the GPU, leaving the CPU idle leads to a net performance gain via avoiding the overhead of data movement between host and device except when needed for some I/O purposes. Memory footprint including the size of communication buffers for MPI_ALLTOALL is managed carefully to maximize the largest problem size possible for a given node count. Detailed performance data including separate contributions from different categories of operations to the elapsed wall time per step are reported for five grid resolutions, from 2048 3 on a single node to 32768 3 on 4096 or 8192 nodes out of 9408 on the system. Both 1D and 2D domain decompositions which divide a 3D periodic domain into slabs and pencils respectively are implemented. The present code suite (labeled by the acronym GESTS, GPUs for Extreme Scale Turbulence Simulations) achieves a figure of merit (in grid points per second) exceeding goals set in the Center for Accelerated Application Readiness (CAAR) program for Frontier. The performance attained is highly favorable in both weak scaling and strong scaling, with notable departures only for 2048 3 where communication is entirely intra-node, and for 32768 3 , where a challenge due to small message sizes does arise. Communication performance is addressed further using a lightweight test code that performs all-to-all communication in a manner matching the full turbulence simulation code. Performance at large problem sizes is affected by both small message size due to high node counts as well as dragonfly network topology features on the machine, but is consistent with official expectations of sustained performance on Frontier. Overall, although not perfect, the scalability achieved at the extreme problem size of 32768 3 (and up to 8192 nodes — which corresponds to hardware rated at just under 1 exaflop/sec of theoretical peak computational performance) is arguably better than the scalability observed using prior state-of-the-art algorithms on Frontier's predecessor machine (Summit) at OLCF. New science results for the study of intermittency in turbulence enabled by this code and its extensions are to be reported separately in the near future.

3D fast Fourier transform↗

Advances in understanding vacuum break dynamics in liquid helium-cooled tubes for accelerator beamline applications

Understanding air propagation and condensation following a catastrophic vacuum break in particle accelerator beamlines cooled by liquid helium is essential for ensuring operational safety. This review summarizes experimental and theoretical work conducted in our cryogenics lab to address this issue. Systematic measurements were performed to study nitrogen gas propagation in uniform copper tubes cooled by both normal liquid helium (He I) and superfluid helium (He II). These experiments revealed a nearly exponential deceleration of the gas front, with stronger deceleration observed in He II-cooled tubes. To interpret these results, a one-dimensional (1D) theoretical model was developed, incorporating gas dynamics, heat transfer, and condensation mechanisms. The model successfully reproduced key experimental observations in the uniform tube system. However, recent experiments involving a bulky copper cavity designed to mimic the geometry of a superconducting radiofrequency (SRF) cavity revealed strong anisotropic flow patterns of nitrogen gas within the cavity, highlighting limitations in extrapolating results from simplified tube geometries to real accelerator beamlines. To address these complexities, we outline plans for systematic studies using tubes with multiple bulky cavities and the development of a two-dimensional (2D) model to simulate gas dynamics in these more intricate configurations. As a result, these efforts aim to provide a comprehensive understanding of vacuum breaks in particle accelerators and improve predictive capabilities for their operational safety.

Beamline tube↗

Data on Cu- and Ni-Si-Mn-rich solute clustering in a neutron irradiated austenitic stainless steel

The data presented in this article is supplementary to the research article “Phase instabilities in austenitic steels during particle bombardment at high and low dose rates” (Levine et al.). Needle-shaped samples were prepared with focused ion beam milling from a 304L stainless steel that was irradiated with fast neutrons (E 0.1 MeV) in the BOR-60 reactor at 318 °C to 47.5 dpa. Atom probe tomography (APT) experiments in voltage mode were then conducted on a Cameca LEAP 5000X HR. Atom position, range, and mass spectrum files after reconstruction with Cameca’s IVAS software are included. Cu- and Ni-Si-Mn-rich solute nanoclusters were identified and analyzed using the Open Source Characterization of APT Reconstructions (OSCAR) program. Python code for OSCAR, information on the program’s underlying algorithm, and sample output files are provided. A proximity histogram of a Ni-Si-Mn-rich cluster and a 1D density/solute concentration profile of a Cu-rich cluster are given to demonstrate OSCAR’s analytical functionalities. The provided APT dataset is valuable for benchmarking phase instabilities in neutron-irradiated austenitic stainless steels that occur at high doses. The OSCAR program can be reused to process other APT data sets where solute nanoclustering is of interest.

42 ENGINEERING↗

Structure-guided design of direct-acting antivirals that exploit the gem-dimethyl effect and potently inhibit 3CL proteases of severe acute respiratory syndrome Coronavirus-2 (SARS-CoV-2) and middle east respiratory syndrome coronavirus (MERS-CoV)

The high morbidity and mortality associated with SARS-CoV-2 infection, the etiological agent of COVID-19, has had a major impact on global public health. Significant progress has been made in the development of an array of vaccines and biologics, however, the emergence of SARS-CoV-2 variants and breakthrough infections are an ongoing major concern. Furthermore, there is an existing paucity of small-molecule host and virus-directed therapeutics and prophylactics that can be used to counter the spread of SARS-CoV-2, and any emerging and re-emerging coronaviruses. Here, we describe herein our efforts to address this urgent need by focusing on the structure-guided design of potent broad-spectrum inhibitors of SARS-CoV-2 3C-like protease (3CL pro or Main protease), an enzyme essential for viral replication. The inhibitors exploit the directional effects associated with the presence of a gem-dimethyl group that allow the inhibitors to optimally interact with the S4 subsite of the enzyme. Several compounds were found to potently inhibit SARS-CoV-2 and MERS-CoV 3CL proteases in biochemical and cell-based assays. Specifically, the EC50 values of aldehyde 1c and its corresponding bisulfite adduct 1d against SARS-CoV-2 were found to be 12 and 10 nM, respectively, and their CC50 values were >50 μM. Furthermore, deuteration of these compounds yielded compounds 2c/2d with EC50 values 11 and 12 nM, respectively. Replacement of the aldehyde warhead with a nitrile (CN) or an α-ketoamide warhead or its corresponding bisulfite adduct yielded compounds 1g, 1e and 1f with EC50 values 60, 50 and 70 nM, respectively. High-resolution cocrystal structures have identified the structural determinants associated with the binding of the inhibitors to the active site of the enzyme and, furthermore, have illuminated the mechanism of action of the inhibitors. Overall, the high Safety Index (SI) (SI=CC50/EC50) displayed by these compounds suggests that they are well-suited to conducting further preclinical studies.

3-Chymotrypsin-like protease (3CLpro)↗

The deep-DRT: A deep neural network approach to deconvolve the distribution of relaxation times from multidimensional electrochemical impedance spectroscopy data

Electrochemical impedance spectroscopy (EIS) is an experimental technique ubiquitously used to study electrochemical systems. However, conventional EIS data interpretation through physical and equivalent circuit models is challenging because physical models are problem-specific, and equivalent circuits are often just lumped-element analogs lacking physical meaning. The distribution of relaxation times (DRT) has emerged as a complementary approach to resolve these issues. One drawback of conventional DRT deconvolution is that the EIS data is understood to be (only) a function of frequency (i.e. 1D data) and deconvolved accordingly. This work proposes a novel deconvolution method based on deep neural networks (DNNs), allowing the analysis of multidimensional EIS spectra to bridge data dependency on both frequencies and experimental conditions. Two particularly appealing traits of the deep-DRT method developed in this article are that neither regularization nor specific spacing on the state variables defining the experiment are required. Finally, leveraging DNN to examine complex EIS spectra and their dependence on experimental conditions, this work opens a new research direction in the area of EIS analysis and DRT deconvolution.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Design optimization of an additively manufactured prototype recuperator for supercritical CO 2 power cycles

Supercritical CO 2 (sCO 2 ) power cycles are being developed due to their potential for high efficiency and reduced capital cost. It is necessary that these recuperators operate at high pressures and temperatures, up to 30 MPa and 900 K, with effectiveness values > 95% and pressure drops <1% to achieve high cycle efficiencies. Moreover, it is also necessary to have reasonable cost recuperators to control the capital costs of the sCO 2 power cycles. In this study, a Plate Pin-Fin (PPF) heat exchanger has been proposed as an sCO 2 recuperator. This preliminary recuperator design leverages capabilities enabled by additive manufacturing. Although the PPF design has characteristics similar to those of a plate heat exchanger, small diameter and relatively long fins are used to increase surface area, enhance heat transfer, and provide structural support for the partition plates that separate the fluid streams. Existing correlations for heat transfer and pressure drop were adapted for the PPF heat exchanger. These correlations were implemented in a 1D analytical model and used for the optimization of a 5-kW th high temperature recuperator for an indirect sCO 2 cycle by varying the design parameters to minimize the quantity of material required. A 3D conjugate heat transfer numerical simulations were conducted to validate the heat transfer and pressure loss correlations. A steepest descent method was used to minimize heat exchanger mass for a 5-kW prototype recuperator subject to a maximum specified pressure drop. Additionally, the design analysis indicated that an optimum PPF recuperator would be attained for the minimum allowable pin transverse spacing, minimum pin width, minimum pin height and near maximum cell aspect ratio. Moreover, at a low material requirement of 0.216 kg/kW and a pressure drop, which is almost five times lower than the allowable pressure drop design target, the optimized PPF heat exchanger has the high potential to be an alternative to a printed circuit heat exchanger, which is a conservative design basis for the current state-of-the-art sCO 2 recuperators.

42 ENGINEERING↗

Lithium superoxide-based high rate Li-Air batteries enabled by Di-iridium sulfur bridge active sites

Li-oxygen (Li-O 2 ) batteries can potentially provide much higher energy density than Li-ion batteries; however, the practical application of these batteries is hindered due to several drawbacks such as low current rates and high overpotential for the charging process. Here, in this paper, we report a novel Li-Air battery system that operates under high current rates (up to 1mAcm -2 ) with LiO 2 as the primary discharge product instead of the commonly reported Li 2 O 2 . This LiO 2 based battery at high rates is through a combination of an as-synthesized new one-dimensional (1D) transition metal trichalcogenide mid-entropy alloy of SnIrS 3.6 as a cathode catalyst and an electrolyte blend with a SnI 2 bi-functional additive. It is revealed that SnIrS 3.6 has a microporous structure composed of six- and five-coordinated metal atoms, forming octahedral and triangular bipyramids which has not been observed in other layered chalcogeide materials. DFT calculations reveal that the SnIrS 3.6 structure can result in LiO 2 formation through di-iridium sulfur bridge active sites that results in strong binding of O 2 and LiO 2 preventing disproportionation to Li 2 O 2 and enabling high rates. This finding will open a new perspective in designing advanced LiO 2 -based Li-O 2 batteries for real practices.

25 ENERGY STORAGE↗

Quartz-hosted inclusions and embayments reveal storage, fluxing, and ascent of the Mesa Falls Tuff, Yellowstone

Quartz-hosted glasses from the Mesa Falls Tuff provide a geochemical window into the pre-eruptive magmatic system from one of Yellowstone's largest-volume caldera-forming eruptions. H 2 O and CO 2 concentrations, along with major and trace elements, were measured in both fully enclosed glass inclusions and partially enclosed embayments in the same quartz crystals. Major elements are largely consistent between the inclusions and embayments, except for K 2 O and Na 2 O. Of note, K 2 O is enriched by ~1 wt.% in embayment interiors relative to inclusions. Most trace elements are also enriched in the embayment interiors compared to inclusions from the same crystals. Fractionation trends of trace elements are consistent with ~30-60% crystallization. Quartz-hosted glass inclusions preserve 3.1±0.9 wt.% H 2 O and 493±227 ppm CO 2 whereas embayment interiors have 0.9±0.1 wt.% H 2 O and 399±229 ppm CO 2 . The CO 2 is roughly similar, but the distinct ~2 wt.% discrepancy between inclusion and embayment interior H 2 O contents may have been produced by CO 2 fluxing sourced from underplated Yellowstone basalts. H 2 O gradients within embayments are flat in their interiors and modified by sharp positive gradients near embayment exteriors which were produced by post-eruptive rehydration. CO 2 gradients occur as gently sloping concentration gradients that extend inward 150 to 250 μm from the embayment exterior. Finally, finite-difference 1D and 2D diffusion modeling indicates the distribution of H 2 O and CO 2 in embayments was produced by slow, fluid-saturated decompression that preceded rapid ascent during the caldera-forming eruption.

2D diffusion modeling↗

Topological effects on separation of alkane isomers in metal–organic frameworks

Polymorphism in metal–organic frameworks (MOFs) means that the same chemical building blocks (nodes and linkers) can be used to construct isomeric MOFs with different topological networks. The choice of topology can substantially impact the pore network of the MOF, changing the sizes and shapes of the pores, which has implications for adsorption and separation applications. Here, we look at the influence of topology in 38 polymorphic MOFs on the separation of linear and branched C4–C6 alkane isomers, a separation of great importance to the petrochemical industry. We find that the MOF Cu 2 (1,4-benzenedicarboxylate) in nbo topology (nbo-Cu 2 BDC) has particularly high affinity for linear alkanes due to its small pore size, which excludes the branched isomers. Upon studying this MOF in further detail, we find that it can take either of two conformations: a cubic conformation, which is typical of nbo MOFs, and a unique star conformation that contains 1D triangular and hexagonal channels. The determination of which conformation the MOF will adopt depends on steric effects between the nodes and linkers.

42 ENGINEERING↗

Analysis of fast-ion losses measured in MAST-U via infrared thermography and a Fast Ion Loss Detector

Fast-ion losses need to be monitored to avoid damage to plasma facing components. In existing experimental devices, the scintillator-based fast-ion loss detector (FILD) is the most advanced diagnostic for measuring fast-ion losses. However, FILDs provide only local information about the losses. Infrared (IR) thermography can be used as a complementary tool for more global monitoring of the deposition of fast-ion losses on the wall, at the expense of no velocity-space resolution. IR cameras measure the temperature of the plasma facing components. This measurement, determined by a combined effect of the thermal plasma, radiation, neutrons and fast-ion losses, can be decomposed to infer the fast-ion load on the tokamak wall. In this manuscript, a workflow to estimate fast-ion losses via IR thermography is applied to the MAST-U spherical tokamak, using a 1D approximation to extract the experimental heat flux on the FILD front face from IR data. To numerically estimate the different contributions to this total heat flux, the field-line tracing environment SMITER is used to calculate the thermal plasma contribution, the orbit-following Monte-Carlo code ASCOT to estimate the fast-ion losses, and bolometry measurements for the radiation. To validate the workflow, two discharges, L-mode plasmas with low MHD activity, were executed using on and off-axis beams, respectively. The experimentally and numerically estimated heat flux are of the same order of magnitude for the on-axis heated scenario, with a strong dependence of the estimated fast-ion losses contribution on the fit to the kinetic profiles used as input. This is also true for the off-axis heated scenario, where the total numerically estimated heat flux is 2.1 or 1.3 times higher than the maximum experimentally estimated heat flux, depending on the ASCOT input used.

FILD↗

Weathering of chlorite from grain to watershed: The role and distribution of oxidation reactions in the subsurface

The reaction mechanism of weathering of chlorite, an important rock-forming phyllosilicate, is not well understood in natural settings. Here, in this work we investigated the weathering of Fe-rich chlorite from deep protolith to saprock to soil across a small shale-underlain watershed in the Appalachian Mountains, USA (Shale Hills). We found that oxidation of Fe(II) in chlorite always occurs prior to dissolution of the interlayers of the mineral. The oxidation of pyrite and chlorite commence near the water table across narrow depth intervals under the upper-catchment ridges, but well below the water table across wide depth intervals under the valley. We hypothesize that these patterns can be explained by hydrological and geochemical differences between the ridge and the valley: oxygenated water descends sub-vertically (1D flow) under the ridge, while under the valley, oxygen-depleted water moves upward to the stream and laterally out of the watershed in the subsurface (3D flow). Geochemical and mineralogical characterization indicates that the transformation of Fe-rich chlorite at Shale Hills is initiated by the oxidation of Fe(II). Next, the interlayer hydroxide sheet dissolves to form hydroxy-interlayered vermiculite and then vermiculite. During the transformation, Mg and Fe are released into solution and Fe is reprecipitated as goethite in pore space. Delivery of oxygen to the deep subsurface by infiltration of meteoric water is thought to control the initial transformation of chlorite at Shale Hills. It is possible that weathering of many Fe(II)-rich minerals is initiated by oxidation as mediated by rates of subsurface oxygen delivery.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Evaluation of accuracy and convergence of numerical coupling approaches for poroelasticity benchmark problems

Accurate modeling of subsurface flow and transport processes is vital as the prevalence of subsurface activities such as carbon sequestration, geothermal recovery, and nuclear waste disposal increases. Computational modeling of these problems leverages poroelasticity theory, which describes coupled fluid flow and mechanical deformation. Although fully coupled monolithic schemes are accurate for coupled problems, they can demand significant computational resources for large problems. In this work, a fixed stress scheme is implemented into the Sandia Sierra Multiphysics toolkit. Two implementation methods, along with the fully coupled method, are verified with one-dimensional (1D) Terzaghi, 2D Mandel, and 3D Cryer sphere benchmark problems. The impact of a range of material parameters and convergence tolerances on numerical accuracy and efficiency was evaluated. Overall the fixed stress schemes achieved acceptable numerical accuracy and efficiency compared to the fully coupled scheme. However, the accuracy of the fixed stress scheme tends to decrease with low permeable cases, requiring the finer tolerance to achieve a desired numerical accuracy. For the fully coupled scheme, high numerical accuracy was observed in most of cases except a low permeability case where an order of magnitude finer tolerance was required for accurate results. Finally, a two-layer Terzaghi problem and an injection–production well system were used to demonstrate the applicability of findings from the benchmark problems for more realistic conditions over a range of permeability. Simulation results suggest that the fixed stress scheme provides accurate solutions for all cases considered with the proper adjustment of the tolerance. Furthermore, this work clearly demonstrates the robustness of the fixed stress scheme for coupled poroelastic problems, while a cautious selection of numerical tolerance may be required under certain conditions with low permeable materials.

58 GEOSCIENCES↗

Results from single-shock Marble experiments studying thermonuclear burn in the presence of heterogeneous mix on the National Ignition Facility

The Marble campaign on the National Ignition Facility investigates the effect of heterogeneous mix on thermonuclear burn for comparison to a probability distribution function (PDF) burn model. Marble utilizes plastic capsules filled with deuterated plastic foam and a fill gas containing tritium. As the capsules implode, the deuterium in the foam mixes with the tritium gas, and DT neutrons are produced as the shocks compress and heat the mixture. The yield of DT neutrons is dependent on the uniformity of the mix, with more heterogeneous mix producing fewer neutrons. In Marble, the heterogeneity of the mix is controlled by varying the diameter of voids introduced into the foam. The first NIF Marble campaign has been executed in which the Marble capsules were indirectly driven with a single strong shock using NIF hohlraums. The experiments produce a low-convergence, high-ion-temperature implosion. The ratio of DT to DD neutron yield is largely consistent with uniform atomic mix for fine-pore foam, and increases slightly with void diameter, contrary to 1D simulations using the PDF burn model. Recent 3D high-resolution simulations of similar experiments performed on the Omega Laser Facility suggest an explanation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Development of spatially and temporally resolved electron density measurements for the assessment of radiation hydrodynamics simulations of laboratory X-ray photoionized plasmas

The photoionized plasma gas cell experiment is an established platform we use to make at-parameter (ξ > > 1 ergs cm s –1 ) measurements of plasma properties with application to high-energy astrophysical systems. We model the experiments with 1D radiation hydrodynamics simulations using the HELIOS-CR code to inform our understanding and assist in the interpretation of results. The simulations predict that the bulk of the plasma is in a quasi-uniform and hydrodynamically unperturbed state throughout the duration of the experiment. To evaluate this prediction, we introduced a photonic Doppler velocimetry (PDV) diagnostic to measure spatially and temporally resolved plasma electron density. The initial measurements were successful but had limitations that made model-data comparisons challenging. To address this, we re-designed the gas cell PDV diagnostic and doubled the number of measurement locations to sample across two thirds of the depth of the cell. We also present a comparison of the results from the upgraded PDV diagnostic to the HELIOS-CR simulations for the first time. As a result, the experimental data confirms the prediction of an unperturbed region in the bulk of the plasma but reveals discrepancies in the time evolution and spatial distribution of the simulated electron density.

79 ASTRONOMY AND ASTROPHYSICS↗

2D kinetic-ion simulations of inverted corona fusion targets

Laser-driven “inverted corona” fusion targets have attracted interest as a low-convergence neutron source and platform for studying kinetic physics. The scheme consists of a hollow or gas-filled spherical shell made of deuterated plastic. The shell has one or more laser entrance holes (LEH), resembling a spherical hohlraum. The laser passes through the LEH’s and illuminates the interior surface of the shell, ablating a plasma that travels inward towards the target center. Long ion mean free paths in the converging plasma can lead to significant interpenetration, atomic mix, and other kinetic effects. Here, in this work we report on numerical simulations of inverted corona targets using the kinetic-ion, fluid–electron hybrid particle-in-cell (PIC) approach in 2D RZ geometry. 2D simulations suggest that shape effects do not have a significant impact on plasma evolution and observed yield trends are primarily the result of 1D kinetic mix mechanisms. Simulations are also compared against available experimental data recorded at the OMEGA laser facility. In particular, synthetic x-ray emission images show good qualitative agreement with experimental results, albeit with an apparent timing discrepancy for the two-sided vacuum target. More generally, we demonstrate the potential of hybrid-PIC simulations for full-system modeling and experimental design, including collisional absorption of laser energy, plasma evolution, mix, and fusion burn.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Measurements of the thermal conductivity of reference liquids using a modified transient hot-wire needle probe

Many power generation processes feature some type of working fluid that plays a critical role in the transfer of heat throughout the system. To optimize thermal efficiencies, an accurate characterization of the temperature-dependent thermal conductivity of the fluid is needed. Herein, this study develops a time-domain Modified Transient Hot-wire Needle Probe to overcome phenomena that have impaired traditional measurement techniques when the fluid is both corrosive and at an elevated temperature. First, the physical design of the instrument is presented to demonstrate features that limit interference from corrosion, electrical conduction, and convective and radiative heat transfer. Next, a governing equation for 1D (radial) heat conduction is fully developed using the thermal quadrupoles technique. A finite-element study is performed for validation. A sensitivity analysis is done to assess the time-dependent influence of critical parameters in the governing equation for several samples. Finally, thermal conductivity measurements are presented for seven different liquid substances by fitting the thermal model to experimental data across a range of temperatures. Reference correlations are included for comparison. The sample thermal conductivity and ambient temperature of the experimental conditions range from 0.125–16.5$\frac{W}{m·K}$ and 10–400°C, respectively. The total uncertainty, comprised of both the experimental design and fitting process, of all measurements is quantified.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗