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At least 397 records · Page 22

Statistical inference of anomalous thermal transport with uncertainty quantification for interpretive 2D SOL models

The critical task of inferring anomalous cross-field transport coefficients is addressed in simulations of boundary plasmas with fluid models. A workflow for parameter inference in the UEDGE fluid code is developed using Bayesian optimization with parallelized sampling and integrated uncertainty quantification. In this workflow, transport coefficients are inferred by maximizing their posterior probability distribution, which is generally multidimensional and non-Gaussian. Uncertainty quantification is integrated throughout the optimization within the Bayesian framework that combines diagnostic uncertainties and model limitations. As a concrete example, we infer the anomalous electron thermal diffusivity $\chi_\perp$ from an interpretive 2D model describing electron heat transport in the conduction-limited region with radiative power loss. The workflow is first benchmarked against synthetic data and then tested on H-, L-, and I-mode discharges to match their midplane temperature and divertor heat flux profiles. We demonstrate that the workflow efficiently infers diffusivity and its associated uncertainty, generating 2D profiles that match 1D measurements. Future efforts will focus on incorporating more complicated fluid models and analyzing transport coefficients inferred from a large database of experimental results.

Bayesian optimization↗

Sensor selection and tool wear prediction with data‐driven models for precision machining

Abstract Estimation of tool wear in precision machining is vital in the traditional subtractive machining industry to reduce processing cost, improve manufacturing efficiency and product quality. In this vein, fusion of time and frequency‐domain features of commonly sensed signals can provide an early indication of tool wear and improve its prediction accuracy for prognostics and health management. This paper presents a data‐driven methodology and a complete tool chain for the inference of precision machining tool wear from fused machine measurements, such as cutting force, power, audio and vibration signals, and quantify the usefulness of each measurement. Indicators of tool wear are extracted from time‐domain signal statistics, frequency‐domain analysis, and time‐frequency domain analysis. Correlation coefficients between the extracted features (indicators) and the tool wear are used to select the most informative features. Principal Component Analysis and Partial Least‐Squares are used to reduce the dimensionality of the feature space. Regression models, including linear regression, support vector regression, Decision tree regression, neural network regression and Gaussian process regression, are used to predict the tool wear using data from a Haas milling machine performing spiral boss face milling. The performance of the regression models based on subsets of sensors validates the preliminary estimates about the saliency of the sensors. The experimental results show that the proposed methods can predict the machine tool wear precisely, with readily available sensor measurements. Neural network and Gaussian process regression were able to achieve good estimates of tool wear at different machine operating conditions. The most informative signal in predicting tool wear was shown to be the vibration signal. Time‐frequency domain features were the most informative features among the combination of features of three domains. In addition, using partial least squares components extracted from the original features of signals led to higher prediction accuracy.

Han, Seulki↗

Novel Perovskite Semiconductors for the Detection of Special Nuclear Material

Special nuclear material detection using portable, highly efficient detectors is of paramount importance to national security and environmental monitoring. Current neutron detectors, including gas proportional counters and scintillators, are not suitable for discrete or portable monitoring due to size, weight, and power limitations. For example, 3 He gas proportional detectors have significant drawbacks, including long absorption lengths, high voltage requirements, and dependence on the availability of 3 He. The goal of this project is to synthesize a novel, boron-based perovskite semiconductor crystals to create a more efficient and more portable neutron detector. This innovative material will lead to a significant decrease in power and size requirements with higher operating temperatures than other traditional solid-state detectors. Directly incorporating 10 B eliminates the need for a conversion layer and leads to high neutron absorption coefficients. In this seedling project, we used inverse temperature crystallization with boron precursors to create CH 3 NH 3 PbI 3-x (BF 4 ) x . The crystals were analyzed with X-ray diffraction, but the results were inconclusive. Future work will focus on tailoring the solution growth and selecting appropriate solvents and precursors.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Data-Driven Chance-Constrained Design of Voltage Droop Control for Distribution Networks: Preprint

This paper addresses the design of local control methods for voltage control in distribution networks with high level of distributed energy resources (DERs). The designed control methods adapt the active and reactive power output of distributed energy resources proportional to the deviation of the local measured voltage magnitudes from a reference voltage, which is referred to as droop control. Thus, the design focuses on determining the droop characteristics which satisfy network-wide voltage magnitude constraints. The uncertainty and variability of DERs renders the design of optimal droop controls very challenging. Hence, this paper proposes chance constraints to limit the risk from intermittent DERs, by designing droop control coefficients that guarantee the satisfaction of network operational constraints with a specific probability. In addition, the proposed approach relies entirely on historical data rather than assuming knowledge of the probability distributions that characterize the uncertainty of DERs. The efficacy of the proposed method is demonstrated on a 37-bus distribution feeder.

chance-constrained optimization↗

Turbulent entrainment in finite-length wind farms

In this article, we present an entrainment-based model for predicting the flow and power output of finite-length wind farms. The model is an extension of the three-layer approach of Luzzatto-Fegiz & Caulfield ( Phys. Rev. Fluids , vol. 3, 2018, 093802) for wind farms of infinite length, and assumes dependence of key flow quantities, such as the wind farm bulk velocity, on the streamwise distance from the farm entrance. To assist our analysis and validate the proposed model, we undertake a series of large-eddy simulations with different turbine spacing arrangements and layouts. Comparisons are also made with the top-down model with entrance effects of Meneveau ( J. Turbul. , vol. 13, 2012, N7) and data from the literature. The finite-length entrainment model is shown to be capable of capturing the power drop between contiguous rows of turbines as well as describing the advection and turbulent transport of kinetic energy in both the entrance and fully developed regions. The fully developed regime is approximated only deep in the wind farm, after approximately 15 rows of turbines. Our data suggest that for the cases considered in this study, the empirical coefficients that can be used to describe turbulent entrainment and transfers above the wind farm exhibit little dependence on the farm layout and may be considered constant for modelling purposes. However, the flow field within the wind farm layer can be strongly modulated by the turbine density (spacing) as well as the array layout, and to that extent it can be argued that they are both primary factors determining the wind farm power output.

17 WIND ENERGY↗

Thermal-shock experiments for separate-effects validation of UO 2 fuel fracture models

Because of the important role that fracture plays in the behavior of ceramic UO2 fuel in a nuclear reactor environment, fracture models are a major component of fuel performance codes. As with any aspect of fuel performance, it is crucial to validate these fracture models against experimental data; however, obtaining well-controlled data for conditions representative of a reactor environment is difficult. Quenching is proposed here as a relatively simple approach for using a laboratory environment to achieve conditions that approximate those of a reactor environment. In this paper, an experimental apparatus containing a single instrumented fuel pellet in a sealed section of copper tubing is developed. It is then applied to a series of seven experiments in which the apparatus is first heated to a high temperature (580-680°C) by immersion in a molten salt bath, then quenched in a cold bath (-10-4 °C). Development of these experiments was guided by numerical simulations, and post-test simulations were performed to aid in understanding the experimental behavior and assessing the accuracy of the predictions of fracture initiation and propagation. In addition, similar experiments were performed on solid copper rods to provide temperature-dependent heat transfer coefficients for use in simulations of these experiments. Here, this study demonstrates that quenching is a viable approach for generating thermal gradients representative of those in prototypical light-water reactor conditions at powers of about 5–10 kW/m. Fracture is expected to begin at these power levels, and moderate amounts of radial and axial cracking was observed in these quenching tests.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Comparative Analysis of Direct and Indirect Cooling of Wide-Bandgap Power Modules and Performance Enhancement of Jet Impingement-Based Direct Substrate Cooling

With the development of high-power and high-torque machines, requirements for high-power density electronics are increasing. Thermal management of such systems requires high heat extraction. Conventional air cooling based heat sinks and cold plate based liquid cooling have their own benefits for various applications but has limitations for high power density applications. The current study explores a jet impingement based direct substrate cooling system that was implemented for a SiC based direct bonded Cu substrate for various power losses. Numerical comparison between jet impingement cooling and conventional horizontal/indirect cooling (pin fin heat sink and genetic algorithm-optimized heat sink) showed that the area weighted average of the heat transfer coefficient (HTC) is high for both horizontal cooling designs, and the local HTC is higher for jet impingement. Design iterations were undertaken to resolve the bottleneck of this cooling system. Increasing the number of nozzles helped to cover more area at the direct bonded Cu bottom plate, which drops the chip temperature considerably. With a constant flow rate, increasing the number of nozzles would decrease local jet velocity, which reduces the heat extraction by jet impingement. This issue can be addressed by reducing the diameter of nozzle but doing so results in a high pressure drop where the design constraint is 2 psi. A flared nozzle design is proposed, which has a higher spreading angle of the jet that increases the flow coverage and reduces the pressure drop of the coolant loop.

Barua, Himel↗

Optimal Power Flow Derived Sparse Linear Solver Benchmarks

Due to the changing nature of the power grid, it is increasingly important to be able to solve a high-fidelity optimal power-flow models on large power networks. This high-fidelity problem, called AC Optimal Power Flow (ACOPF), is a nonlinear, nonconvex optimization problem. One of the few reliable ways of solving such a problem is interior point methods. These methods result in sparse linear systems where the coefficient matrix is symmetric, indefinite and nearly always ill-conditioned. As such, they are particularly challenging for sparse linear solvers and represent a considerable computational bottleneck in solving the ACOPF problem. In this paper, we introduce a repository of linear systems captured from ACOPF problems when solved by the open-source optimizer IPOPT. These matrices are meant to be used as a test suite for sparse linear solver development.

97 MATHEMATICS AND COMPUTING↗

Uniformly Ordered Binary Decision Algorithm for Benchmark Experiment Correlations in Whisper Validation

When performing a validation exercise for determining the upper subcritical limit of a nuclear criticality safety application, an analyst should select and perform a statistical analysis on a population of benchmark experiments that are neutronically similar to the application. The size of this population should be sufficiently large such that the statistical analysis has a high degree of confidence that the bias plus bias uncertainty (calculational margin) has been accurately quantified. A complication arises because many benchmark experiments share common components, leading to correlations in their measured effective multiplication factors. Correlations between benchmark experiments within the population reduces its predictive power. This motivates the need for methods that consider benchmark experiment correlations and ensure adequate statistical significance of results. The Whisper code is a statistical analysis pack- age that incorporates nuclear data sensitivity coefficients from MCNP to assess benchmark experiment similarity and then performs an extreme-value analysis to estimate the bias plus bias uncertainty. The original methodology in Whisper does not consider the effect of benchmark experiment correlations when making this estimation, and this summary proposes the uniformly ordered binary decision algorithm to address this shortcoming. The original methodology in Whisper computes similarity coefficients ck for an application compared to all benchmark experiments in its library and develops weighting factors for a selected population proportional to the ck values. The methodology can be interpreted as statistically emulating a validation exercise for a particular application where the weighting factors may be viewed as the likelihood that an analyst would include a particular benchmark experiment within the population. The effective sample size of the population is the expected or mean number of benchmark experiments in the population. The uniformly ordered binary decision algorithm identifies clusters of correlated benchmark experiments within the population and then computes adjusted weighting factors based on the magnitude of the correlation coefficients within the cluster to compute a reduced effective sample size accounting for the lower information content because of correlations. Benchmark experiments within the cluster are ordered randomly with equal probability and probabilistic decisions are made as to whether a benchmark. experiment within the cluster should treated as redundant with a previous one; if two redundant benchmark experiments are included, then the conservative worst case bias plus bias uncertainty is used and the pair is counted as a single benchmark experiment in the population. Results are provided for HEU solutions in a research version of the Whisper software using benchmark experiment correlations provided by DICE, the Database for the International Criticality Safety Benchmark Evaluation Project (ICSBEP). These show that there can be a significant increase in the bias plus bias uncertainty because the effective sample size is reduced, and therefore the algorithm, needing to meet sample size requirements, expands the benchmark experiment population by accepting less similar benchmark experiments that would have otherwise not been included.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Drell-Yan q T resummation of fiducial power corrections at N 3 LL

We consider Drell-Yan production pp → V*X → LX at small q T << Q, where q T and Q are the total transverse momentum and invariant mass of the leptonic final state L. Experimental measurements require fiducial cuts on L, which in general introduce enhanced, linear power corrections in q T /Q. We show that they can be unambiguously predicted from factorization, and resummed to the same order as the leading-power contribution. For the fiducial q T spectrum, they constitute the complete linear power corrections. We thus obtain predictions for the fiducial q T spectrum to N 3 LL and next-to-leading-power in q T /Q. Matching to full NNLO ($α$$^{2}_{s}$), we find that the linear power corrections are indeed the dominant ones, and once included by factorization, the remaining fixed-order corrections become almost negligible below q T ≲ 40 GeV. We also discuss the implications for more complicated observables, and provide predictions for the fiducial Φ* spectrum at N 3 LL+NNLO. We find excellent agreement with ATLAS and CMS measurements of q T and Φ*. We also consider the $p$$^{ℓ}_{T}$ spectrum. We show that it develops leptonic power corrections in q T /(Q – 2$p$$^{ℓ}_{T}$), which diverge near the Jacobian peak $p$$^{ℓ}_{T}$ ~ Q/2 and must be kept to all powers to obtain a meaningful result there. Doing so, we obtain for the first time an analytically resummed result for the $p$$^{ℓ}_{T}$ spectrum around the Jacobian peak at N 3 LL+NNLO. Our method is based on performing a complete tensor decomposition for hadronic and leptonic tensors. We show that in practice this is equivalent to often-used recoil prescriptions, for which our results now provide rigorous, formal justification. Our tensor decomposition yields nine Lorentz-scalar hadronic structure functions, which for Z/γ* → ℓℓ or W → ℓν directly map onto the commonly used angular coefficients, but also holds for arbitrary leptonic final states. In particular, for suitably defined Born-projected leptons it still yields a LO-like angular decomposition even when including QED final-state radiation. Finally, we also discuss the application to q T subtractions. Including the unambiguously predicted fiducial power corrections significantly improves their performance, and in particular makes them applicable near kinematic edges where they otherwise break down due to large leptonic power corrections.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Sensitivity study on the fin effect of thermocouple mounted on the heated surface under film boiling condition

In the reactivity-initiated accident (RIA) scenario, right after the power burst with the occurrence of departure from nucleate boiling (DNB), the cladding temperature quickly reaches its maximum and is maintained in a steady film boiling regime. Then, under limited heat transfer performance of film boiling, the local cooling effect by the thermocouple wire may not be neglected. A computational model is developed to estimate the local cooling effect of the thermocouple wire mounted on the cladding surface under film boiling condition. The model predicts the temperature profile along the cladding surface as physically expected and is verified against the benchmark problem. Sensitivity studies reveal the significant effects of the thickness of vapor film layer and the diameter of thermocouple on the temperature drop near the thermocouple, for they increase the heat transfer area to the liquid water region. The impact of film boiling heat transfer coefficient, however, is not significant, as the primary heat transfer mechanism near the thermocouple is the heat conduction to the wire. Future study will include the contribution of radiative heat transfer between the cladding surface and the vapor film layer, as well as a transient power history which represents an actual RIA scenario.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Experimental and analytical study of the hydrodynamic and single and two-phase convective heat transfer performance of flexible PDMS microchannels with micropillar arrays

Various copper and silicon based thermal management systems are used in the cooling of electronics. However, the rigid nature of these materials along with their high thermal and electrical conductivity pose a difficulty in developing direct contact embedded flexible cooling systems that can offer robust cooling performance. The low density, thermal stability, chemical inertness, and electrical insulation of Polydimethylsiloxane (PDMS) make it an ideal material to develop lightweight direct contact thermal management systems for electronics. Its ease of fabrication with tunable flexibility provides the opportunity to go beyond traditional electronics and develop advanced active and passive thermal management systems for a wide–range of applications in foldable and wearable electronics, liquid cooling garments, microgravity, and electric motors. In this study, a flexible PDMS based microchannel with micropillar arrays, which enhance the thermal performance of the device through capillary-assisted flow, has been developed. The hydrodynamic and convection heat transfer performance of three PDMS wick pillar geometries, ranging from a porosity of 0.8–0.91, are investigated and compared under single-phase and two-phase conditions. Dielectric coolant FC-3283 is employed and permeability measurements are made for mass fluxes ranging from 53 kg/m 2 s to 369 kg/m 2 s. Given its conformability, the device demonstrates a deviation from Darcy’s Law, within the laminar regime, with an increasing permeability with mass flux at the rate of ~0.5–0.8 Darcy/(kg/m 2 s). A semi-analytical model has been developed and reported to quantify the conformability of the device. The heat transfer performance is experimentally evaluated using the same dielectric fluid for mass flux ranging from 105 kg/m 2 s to 420 kg/m 2 s with heat fluxes ranging from 1.5 W/cm 2 to 16 W/cm 2 . Heat transfer coefficients of up to 7000 W/m 2 K are observed, which are comparable to copper and silicon microchannels. The effect of porosity on the single phase thermal performance has been evaluated against the pumping power to provide a basis for thermal management system design. Finally, high-speed imaging is performed to study the two-phase flow characteristics to provide insight into the vapor formation and removal.

42 ENGINEERING↗

Dual-Functional Thermocapacitive Heat Pump with Electrochemical Supercapacitors for Building Thermal Management and Energy Storage

Efficient heating and cooling technologies can help reduce the energy consumption and carbon emissions of buildings. This work explores the use of supercapacitive cells in a multifunctional, liquid-regenerated thermocapacitive heat pump that can provide electrical energy storage in addition to heating and cooling. A proof-of-concept prototype based on eight commercial supercapacitors and using deionized water as a liquid regenerator demonstrated cooling and energy storage capabilities. A peak cooling coefficient of performance (COPc) of 0.27 was achieved at a temperature drop of 0.24 K. The highest measured electrical energy storage density of the cells was 5.93 J cm-3, and the highest cooling power delivered relative to the volume of the cells was 0.58 mW cm-3. This work demonstrates the use of electrochemical energy storage devices in multifunctional equipment for thermal management in buildings.

25 ENERGY STORAGE↗

Correlation Between Microscopic Current Fluctuations Observed at Ultra-Microelectrodes and Macroscopic Bulk Electrolysis Performance in Redox-Active Microemulsions

Microemulsions (μEs) have been proposed as redox flow battery (RFB) electrolytes that maximize ionic conductivity and charge capacity by synergizing two immiscible phases. However, charge transfer during electrolysis in μEs is poorly understood. Here, we show that ultramicroelectrode electrolysis of ferrocene-loaded μEs –20%, 60%, and 90% water - reveals stochastic current fluctuations. These are differentiated in the scanning electrochemical microscopy (SECM) geometry, where power spectral density analysis showed distinct changes in the frequency contributions. SECM in the substrate generation-tip collection mode showed that fluctuations arise under mass-transfer control. Significant differences in the diffusion coefficient of ferrocene species were deducted from SECM approach curves, suggesting phase transfer behavior. Using bulk electrolysis, we calculated the charge accessibility and cycling behavior in the μEs. A decrease in the stochastic behavior of the μEs seems to correlate to a higher accessibility and cycling performance, with the 90% water μE displaying the best reversibility and the 60% the lowest. Altogether, these results suggest that Marangoni-type convection driven by concentration gradients and/or μE restructuring during charge transfer play a role in the electrochemical performance of μEs. This presents opportunities for screening and diagnosing the performance of these emerging RFB electrolytes.

25 ENERGY STORAGE↗

Thermo-optic properties of silicon-rich silicon nitride for on-chip applications

We demonstrate the thermo-optic properties of silicon-rich silicon nitride (SRN) films deposited using plasma-enhanced chemical vapor deposition (PECVD). Shifts in the spectral response of Mach-Zehnder interferometers (MZIs) as a function of temperature were used to characterize the thermo-optic coefficients of silicon nitride films with varying silicon contents. A clear relation is demonstrated between the silicon content and the exhibited thermo-optic coefficient in silicon nitride films, with the highest achievable coefficient being as high as (1.65±0.08) ×10 −4 K -1 . Furthermore, we realize an SRN multi-mode interferometer (MMI) based thermo-optic switch with over 20 dB extinction ratio and total power consumption for two-port switching of 50 mW.

Nejadriahi, Hani↗

Measurement of the Full Shape of the Thermal Sunyaev–Zel’dovich Power Spectrum from the South Pole Telescope and Herschel–SPIRE Observations

We present a measurement of the full shape of the power spectrum of the thermal Sunyaev–Zel’dovich (tSZ) effect down to arcminute scales using cosmic microwave background (CMB) data from the South Pole Telescope (SPT) over a roughly 100 deg 2 field. The analysis incorporates data from the 2019–2020 seasons of the SPT-3G survey in bands centered at 95, 150, and 220 GHz; from the full SPTpol dataset at 150 GHz; and from the Herschel–SPIRE survey in bands centered at 600 and 857 GHz. We combine data from all the above bands using linear combination (LC) techniques to produce a tSZ or Compton-y map. We modify the LC weights to produce multiple versions of the Compton-y map, including minimum-variance (MV) and foreground-minimized (-min) maps. We measure the auto- and cross-power spectra of a subset of these maps in the range ℓ ∈ [500, 5000]. While this power spectrum includes contributions from signals other than tSZ, we present numerous checks to show that the most challenging foreground signal, the cosmic infrared background (CIB), is much lower than the desired tSZ signal in the scales of interest in this work. The final tSZ power spectrum is measured at 9.3σ with both the MV and CIB-min maps. Our results are consistent with those reported in other CMB surveys across the literature. Using the difference in the tSZ power spectrum from the MV and CIB-min maps, we reconstruct the scale-dependent tSZ–CIB cross correlation $ρ^{\textrm{tSZ}}_{ℓ}$ x CIB, finding 3.1σ evidence for a nonzero correlation coefficient that is positive on large scales and approaches zero for ℓ > 2500. This result represents the deepest tSZ maps ever produced and provides new constraints that can help refine astrophysical feedback mechanisms and models of the intracluster medium.

Raghunathan, S. [Univ. of California, Davis, CA (U↗

Intrinsic Junction Thermocouples For Surface Temperature Measurement

The material selection, attachment, and calibration of intrinsic junction thermocouples is discussed. Intrinsic junction thermocouples are utilized for their fast response times in surface measurements during high thermal transients. The as-is measurement and calibrated corrections are presented for both the out-of-pile pulse power system and the critical heat flux experiments in the Idaho National Laboratory Transient Reactor Test facility. The fin effect from temperature measurements on the surface of fuel cladding is corrected using a linear coefficient, m, and temperature corrections are sometimes 100 °C or more—representing 18% of the original temperature measurement.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗