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At least 73 records · Page 4

Eddy Current Flow Meter Measurements and Modeling Validation

The goal of the eddy current flow meter (ECFM) is to monitor velocities and temperatures of conductive liquid metals. The ECFM can also detect voids in two-phase liquid metal flows. Measurement of these flows can greatly improve the accuracy of the empirical formulas used for fluid dynamics near the reactor core and aid in mapping any non-uniformities in fluid flow such as estimates of temperature and phase. While the eventual goal is to develop the ECFM for the liquid sodium surrounding the Versatile Test Reactor (VTR) core, this report focuses on modeling and experimental validation of ECFM for a moving solid test rod and for liquid mercury in the Target Test Facility (TTF) flow loop to better understand and further develop ECFM measurement capabilities by validating model predictions with benchmark experiments. Eventually the models could be used to design and optimize future ECFMs for specific applications such as monitoring flow within the VTR pool.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Model-independent measurement of the matter-radiation equality scale in DESI 2024

The peak of the matter power spectrum, known as the turnover (TO) scale, is determined by the horizon size at the time of matter-radiation equality. This scale can serve as a standard ruler, independent of other features in the matter power spectrum, such as baryon acoustic oscillations (BAO). Here, in this work, we present the first detection of the turnover in the galaxy autopower spectrum, utilizing the distribution of quasars and luminous red galaxies (LRG) measured by the Dark Energy Spectroscopic Instrument (DESI) during its first year of survey operations in a model-independent manner. To avoid confirmation bias, we first analyze the data using data blinding methods designed for the DESI baryon acoustic oscillation, redshift space distortion and scale-dependent bias signals. We measure the angle-averaged dilation distance 𝐷 V ⁡(𝑧 = 1.651) = (38.1 ± 2.5)⁢𝑟 H from the quasars and 𝐷 V ⁡(𝑧 = 0.733) = (21.8 ± 1.0)⁢𝑟 H from the LRG sample in units of the horizon 𝑟 H at the matter-radiation-equality epoch. Combining these two constraints and assuming a flat Λ⁢CDM model with three standard neutrino species, we can translate this into a constraint of Ω m ⁢ℎ 2 = 0.13⁢9$^{+0.036}_{−0.046}$. We can break the Ω m −𝐻 0 degeneracy with low-redshift distance measurements from type-Ia supernova (SN) data from Pantheon+, we obtain a sound-horizon free estimate of the Hubble-Lemaître parameter of 𝐻 0 = 65.2$^{+4.9}_{−6.2}$ km/s/Mpc, consistent with sound-horizon dependent DESI measurements. On the other hand, combining the DESI BAO and TO, we find a truly DESI-only measurement of 𝐻 0 = 74.0$^{+7.2}_{−3.5}$ km/s/Mpc, in line with DESI-only full-shape results where the sound-horizon scale is marginalized out. This discrepancy in 𝐻 0 can be reconciled in a 𝑤 0 ⁢𝑤 𝑎 ⁢ CDM cosmology, where the combination of DESI BAO and TO data yields 𝐻 0 = 66.5 ± 7.2 km/s/Mpc.

cosmological parameters↗

TAP Absorption Coefficients

The data set of aerosol light absorption coefficients were collected by two tricolor absorption photometers (TAP; Brechtel Model 2901) in July and August, 2022 during the TRACER field campaign at the AMF1 site in La Porte, Texas. One of the TAPs at the La Porte site was an RGB model measuring aerosol light absorption at 652, 528, 467 nm, and the other was an UV model measuring absorption at the same red and green wavelengths but at an additional UV wavelength at 365 nm. Since TAP is a filter-based optical instrument using 47-mm glass fiber filters, the output absorption coefficients are corrected for filter loading and scattering effects based on a correction scheme developed in "Comment on ‘Calibration and Intercomparison of Filter-Based Measurements of Visible Light Absorption by Aerosols’" by John A. Ogren 2010. This uploaded dataset contains both the Ogren corrected absorption coefficients (column header with “ Ogren”) and the raw absorption coefficients without the correction scheme (column header with “_ Raw”). During the field campaign, the two TAPs operated side by side with a shared inlet at a flow rate of 2 lpm. In July, no inlet impactors/cyclones were installed; however, beginning in August, a PM2.5 cyclone inlet was installed.

54 ENVIRONMENTAL SCIENCES↗

Measurement and Modeling of Polarized Atmosphere at the South Pole with SPT-3G

We present the detection and characterization of fluctuations in linearly polarized emission from the atmosphere above the South Pole. These measurements make use of data from the SPT-3G receiver on the South Pole Telescope in three frequency bands centered at 95, 150, and 220 GHz. We use the cross-correlation between detectors to produce an unbiased estimate of the power in Stokes I, Q, and U parameters on large angular scales. Our results are consistent with the polarized signal being produced by the combination of Rayleigh scattering of thermal radiation from the ground and thermal emission from a population of horizontally aligned ice crystals with an anisotropic distribution described by Kolmogorov turbulence. The measured spatial scaling, frequency scaling, and elevation dependence of the polarized emission are explained by this model. Polarized atmospheric emission has the potential to significantly impact observations on the large angular scales being targeted by searches for inflationary B-mode CMB polarization. We present the distribution of measured angular power spectrum amplitudes in Stokes Q and I for 4 yr of Austral winter observations, which can be used to simulate the impact of atmospheric polarization and intensity fluctuations at the South Pole on a specified experiment and observation strategy. We present a mitigation strategy that involves both downweighting significantly contaminated observations and subtracting a polarized atmospheric signal from the 150 GHz band maps. In observations with the SPT-3G instrument, the polarized atmospheric signal is a well-understood and subdominant contribution to the measured noise after implementing the mitigation strategies described here.

79 ASTRONOMY AND ASTROPHYSICS↗

Modeling and Measuring the Stress Distribution in Soft Magnetic Cores due to Epoxy Impregnation and Curing

Understanding the effects of viscoelastic relaxation of stresses is critical in electric motor and inductor applications, where the magnetic material is fully or partially comprised of an amorphous phase and impregnated in an epoxy. Magnetic Amorphous Nanocomposites (MANCs) are a class of recently developed high-frequency magnetic materials that exhibit low magnetic hysteresis, high saturation flux density and very low AC magnetic losses. MANCs are formed as long, thin ribbons, a shape factor that minimizes eddy current-induced self-heating. This feature, in addition to their 1 GPa strength, and makes them attractive candidates for high-speed, high-power density, electric motors. MANCs are used in the form of tape-wound cores (TWCs). During the manufacturing process, the cores are impregnated with liquid epoxy between each layer of ribbon. Validated knowledge of the stresses imposed by the manufacturing process and during operation is necessary to understand motor performance limitations with respect to strength. Magnetostriction, the strain imposed by reversal of the magnetic field, also affects performance. When the epoxy cures, it contracts volumetrically by 8%, imposing radial and circumferential stresses that vary along the radial direction. To date, these stresses have received little attention in the literature. Here, we model the stress distribution throughout a TWC due to epoxy curing. Strain gauge measurements reported here indicate substantially lower tangential strain than model values, which is beneficial and which we attribute to viscoelastic relaxation of the epoxy layers. We will incorporate a constitutive model of this viscoelastic relaxation, and conduct more detailed strain measurements to understand how this takes

24 POWER TRANSMISSION AND DISTRIBUTION↗

Measurement and modeling of beam transport in the FODO line of the Spallation Neutron Source Beam Test Facility

Ongoing studies at the Spallation Neutron Source (SNS) Beam Test Facility (BTF) seek to understand and model bunch dynamics in a high-power LINAC front-end. The BTF has recently been upgraded with a reconfiguration from a U-shaped line to a Straight line. We report the current state of model benchmarking, with a focus on RMS beam sizes within the FODO line. The beam measurement is obtained via three camera/screen pairs in the FODO line. This presentation discusses the methodology and results of this measurement.

Thompson, Trent↗

Python Measurement-Informed Modelling Method (PythonMIMM) v1.02

This Python program implements the calculations for electrical energy efficiency and electrical losses in the paper "Energy and power quality measurement for electrical distribution in AC and DC microgrid buildings" (https://www.sciencedirect.com/science/article/abs/pii/S0306261921015658). The inputs are metered voltage, current, or power data of meters located throughout the DC system. In the absence of metered data, the user must input some other information about the building such as the types of power converters or wire lengths. The program will build a loss model of the DC system based on metered data and electrical information. It will also generate an equivalent AC system and determine the losses and efficiency.

Gerber, Daniel [Lawrence Berkeley National Laborat↗

Measurement and Modeling of Electron Temperature in Laboratory Photoionized Plasmas Relevant to Astrophysics

The electron temperature of photoionized plasmas characterizes the thermalization of photoelectrons, impacts the charge-state distribution, emissivity, and opacity through atomic recombination processes, and is needed to perform detailed comparisons with theory predictions. We discuss temperature measurements in laboratory photoionized plasmas and a comparison with model calculations done with several theory approximations and codes. These include a radiation-hydrodynamics simulation and two nonequilibrium heating and ionization models that tracked the evolution of the internal energy of the electrons. Furthermore, for the same physics model and X-ray flux time history, calculations were performed assuming steady-state or time-dependent conditions. The time history of steady-state results correlates with that of the X-ray flux, while that of the time-dependent cases does not, and it is qualitatively and quantitatively different from the steady-state case. Steady-state results significantly overestimated temperature measurements, while time-dependent results produced better approximations, which suggests the importance of transient effects in the experiment and also the need for time-resolved measurements.

Laboratory astrophysics↗

Models and Measurements Quantify Photon Recycling, Charge-Carrier Diffusion and Photon Scattering Contributions to Photoluminescence in InP Nanowire Arrays

Nanowire arrays present many unique advantages for solar-to-chemical energy conversion. One possible advantage is that photon recycling between neighboring nanowires has the potential to increase solar energy conversion efficiencies. Here, in this work, we explore three underlying mechanisms of optical and electronic coupling between neighboring nanowires─incident photon scattering, photon recycling, and charge-carrier transport from the photoexcited nanowire to the neighboring nanowire via the underlying substrate─using single nanowire-level microscopy and spectroscopy measurements. We present a comprehensive analysis of light absorption and emission of a single nanowire at open circuit, and subsequent re-absorption and re-emission by a neighboring nanowire. We developed a novel correlated single nanowire microspectroscopy and widefield imaging methodology to spatially resolve photon communication pathways between neighboring nanowires and selectively image re-emitted and reflected photons. We developed unique multiphysics models to couple wave optics and semiconductor photophysics to especially isolate contributions from photon recycling and electronic transport to photon emission from neighboring nanowires. By systematically varying the morphologies of the nanowires modeled, we identified pathways to maximize photon recycling between neighboring nanowires. We concluded that the measured photoluminescence is more strongly influenced by the diffusion of charge carriers as compared to photon recycling in materials with moderate-to-large charge-carrier mobilities (>10 cm 2 V –1 s –1 ), and that photon recycling dictates photoluminescence intensity only when the charge-carrier mobility is low (<1 cm 2 V –1 s –1 ). The experimental and simulation platforms developed herein for photon management strategies can be leveraged by the semiconductor photocatalysis community to enhance solar-to-chemical conversion efficiencies in semiconductor nanowire arrays.

25 ENERGY STORAGE↗

Laser Measurements and Modeling of Shock Tunnel Freestream Velocity and Multispecies Thermal Nonequilibrium

Coherent anti-Stokes Raman scattering (CARS) and nitric oxide molecular tagging velocimetry (NO-MTV) were used to characterize the freestream in Sandia’s Hypersonic Shock Tunnel (HST) using a burst-mode laser operated at 100 kHz. Experiments were performed at nominal freestream velocities of 3 and 4 km/s using both air and N 2 test gas. The CARS diagnostic provides nonequilibrium characterization of the flow by measuring vibrational and rotational temperatures of N 2 and O 2 , which are compared to NO temperatures from separate laser absorption experiments. Simultaneous, collinear freestream velocities were measured using NO MTV along with pitot pressure measurements. Furthermore, this extensive freestream dataset is compared to nonequilibrium CFD that is capable of modeling species-specific, vibrational temperatures throughout the nozzle expansion. Significant nonequilibrium between vibrational and rotational temperatures was measured at each flow condition. N 2 exhibits the most nonequilibrium, followed by O 2 and NO. The CFD model captures this trend, although it consistently overpredicts N 2 and O 2 vibrational temperatures. At 3 km/s, the modeled NO nonequilibrium is underpredicted, whereas it is overpredicted at 4 km/s. Good agreement is seen between CFD and the velocity and rotational temperature measurements. Experiments with water added to the test gas yielded no discernable difference in vibrational relaxation.

Aerodynamics↗

Gallium-doped zinc oxide: nonlinear reflection and transmission measurements and modeling in the ENZ region

Abstract Strong nonlinear materials have been sought after for decades for applications in telecommunications, sensing, and quantum optics. Gallium-doped zinc oxide is a II–VI transparent conducting oxide that shows promising nonlinearities similar to indium tin oxide and aluminum-doped zinc oxide for the telecommunications band. Here we explore its nonlinearities in the epsilon near zero (ENZ) region and show n 2,eff values on the order of 4.5 × 10 −3 cm 2 GW −1 for IR pumping on 200–300 nm thin films. Measuring nonlinear changes in transmission and reflection with a white light source probe in the near-IR while exciting in the near-IR provides data in both time and wavelength. Three films varying in thickness, optical loss, and ENZ crossover wavelength are numerically modeled and compared to experimental data showing agreement for both dispersion and temporal relaxation. In addition, we discuss optimal excitation and probing wavelengths occur around ENZ for thick films but are red-shifted for thin films where our model provides an additional degree of freedom to explore. Obtaining accurate nonlinear measurements is a difficult and time-consuming task where our method in this paper provides experimental and modeled data to the community for an ENZ material of interest.

Ball, Adam (ORCID:0000000318167813)↗

Measurements and modeling of type-I and type-II ELMs heat flux to the DIII-D divertor

Type-I and type-II edge-localized-modes (ELMs) heat flux profiles measured at the DIII-D divertor feature a peak in the vicinity of the strike-point and a plateau in the scrape-off-layer (SOL), which extends to the first wall. The plateau is present in attached and detached divertors and it is found to originate with plasma bursts upstream in the SOL. The integrated ELM heat flux is distributed at ~65% in the peak and ~35% in this plateau. The parallel loss model, currently used at ITER to predict power loads to the walls, is benchmarked using these results in the primary and secondary divertors with unprecedented constraints using experimental input data for ELM size, radial velocity, energy, electron temperature and density, heat flux footprints and number of filaments. The model can reproduce the experimental near-SOL peak within ~20%, but cannot match the SOL plateau. Employing a two-component approach for the ELM radial velocity, as guided by intermittent data, the full radial heat flux profile can be well matched. The ELM-averaged radial velocity at the separatrix, which explains profile widening, increases from ~0.2 km s –1 in attached to ~0.8 km s –1 in detached scenarios, as the ELM filaments' path becomes electrically disconnected from the sheath at the target. The results presented here indicate filaments fragmentation as a possible mechanism for ELM transport to the far-SOL and provide evidence on the beneficial role of detachment to mitigate ELM flux in the divertor far-SOL. However, these findings imply that wall regions far from the strike points in future machines should be designed to withstand significant heat flux, even for small-ELM regimes.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Use of a controlled experiment and computational models to measure the impact of sequential peer exposures on decision making

It is widely believed that one’s peers influence product adoption behaviors. This relationship has been linked to the number of signals a decision-maker receives in a social network. But it is unclear if these same principles hold when the “pattern” by which it receives these signals vary and when peer influence is directed towards choices which are not optimal. To investigate that, we manipulate social signal exposure in an online controlled experiment using a game with human participants. Each participant in the game decides among choices with differing utilities. We observe the following: (1) even in the presence of monetary risks and previously acquired knowledge of the choices, decision-makers tend to deviate from the obvious optimal decision when their peers make a similar decision which we call the influence decision, (2) when the quantity of social signals vary over time, the forwarding probability of the influence decision and therefore being responsive to social influence does not necessarily correlate proportionally to the absolute quantity of signals. To better understand how these rules of peer influence could be used in modeling applications of real world diffusion and in networked environments, we use our behavioral findings to simulate spreading dynamics in real world case studies. We specifically try to see how cumulative influence plays out in the presence of user uncertainty and measure its outcome on rumor diffusion, which we model as an example of sub-optimal choice diffusion. Together, our simulation results indicate that sequential peer effects from the influence decision overcomes individual uncertainty to guide faster rumor diffusion over time. However, when the rate of diffusion is slow in the beginning, user uncertainty can have a substantial role compared to peer influence in deciding the adoption trajectory of a piece of questionable information.

97 MATHEMATICS AND COMPUTING↗

Atomistic measurement and modeling of intrinsic fracture toughness of two-dimensional materials

Quantifying the intrinsic mechanical properties of two-dimensional (2D) materials is essential to predict the long-term reliability of materials and systems in emerging applications ranging from energy to health to next-generation sensors and electronics. Currently, measurements of fracture toughness and identification of associated atomistic mechanisms remain challenging. Herein, we report an integrated experimental–computational framework in which in-situ high-resolution transmission electron microscopy (HRTEM) measurements of the intrinsic fracture energy of monolayer MoS 2 and MoSe 2 are in good agreement with atomistic model predictions based on an accurately parameterized interatomic potential. Changes in crystalline structures at the crack tip and crack edges, as observed in in-situ HRTEM crack extension tests, are properly predicted. Such a good agreement is the result of including large deformation pathways and phase transitions in the parameterization of the inter-atomic potential. The established framework emerges as a robust approach to determine the predictive capabilities of molecular dynamics models employed in the screening of 2D materials, in the spirit of the materials genome initiative. Moreover, it enables device-level predictions with superior accuracy (e.g., fatigue lifetime predictions of electro- and opto-electronic nanodevices).

Zhang, Xu↗

Ultrafast radiographic imaging and tracking: An overview of instruments, methods, data, and applications

Ultrafast radiographic imaging and tracking (U-RadIT) use state-of-the-art ionizing particle and light sources to experimentally study sub-nanosecond transients or dynamic processes in physics, chemistry, biology, geology, materials science and other fields. These processes are fundamental to modern technologies and applications, such as nuclear fusion energy, advanced manufacturing, communication, and green transportation, which often involve one mole or more atoms and elementary particles, and thus are challenging to compute by using the first principles of quantum physics or other forward models. One of the central problems in U-RadIT is to optimize information yield through, e.g. high-luminosity X-ray and particle sources, efficient imaging and tracking detectors, novel methods to collect data, and large-bandwidth online and offline data processing, regulated by the underlying physics, statistics, and computing power. We review and highlight recent progress in: (a.) Detectors such as high-speed complementary metal-oxide semiconductor (CMOS) cameras, hybrid pixelated array detectors integrated with Timepix4 and other application-specific integrated circuits (ASICs), and digital photon detectors; (b.) U-RadIT modalities such as dynamic phase contrast imaging, dynamic diffractive imaging, and four-dimensional (4D) particle tracking; (c.) U-RadIT data and algorithms such as neural networks and machine learning, and (d.) Applications in ultrafast dynamic material science using XFELs, synchrotrons and laser-driven sources. Hardware-centric approaches to U-RadIT optimization are constrained by detector material properties, low signal-to-noise ratio, high cost and long development cycles of critical hardware components such as ASICs. Interpretation of experimental data, including comparisons with forward models, is frequently hindered by sparse measurements, model and measurement uncertainties, and noise. Alternatively, U-RadIT make increasing use of data science and machine learning algorithms, including experimental implementations of compressed sensing. Machine learning and artificial intelligence approaches, refined by physics and materials information, may also contribute significantly to data interpretation, uncertainty quantification and U-RadIT optimization.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

PickerXL, A Large Deep Learning Model to Measure Arrival Times from Noisy Seismic Signals

Precisely measuring seismic arrival times is a labor-intensive task but is critical for both earthquake monitoring and subsurface imaging. Recently published deep learning models have demonstrated superior performance compared to traditional automatic approaches for picking arrival times. Although existing deep learning models have shown promising results, further advancements are necessary as their performance is not yet satisfactory especially when applied to new regions and station networks. Increasing model size has led to improved performance in other machine learning applications. Here, we aimed to investigate whether enlarging deep learning models can increase performance on accepted benchmarks. We trained three models of varying sizes, small (1X), medium (4X), and large (16X), using globally distributed local and regional earthquake signals and background noise waveforms from a benchmark dataset, Stanford Earthquake Dataset. Our results indicate that the largest model (PickerXL) outperforms both the smaller models and Seisbench implementation of the PhaseNet model, which has the same number of parameters as our small model. The PickerXL model’s enhanced capacity to extract complex patterns from seismograms contributes to its superior arrival picking abilities compared to the smaller model.

Chai, Chengping [Oak Ridge National Laboratory (OR↗