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At least 235 records · Page 13

Development of experimental and computational frameworks to predict subcooled flow boiling in the LANL Isotope Production Facility

Cooling is crucial to maintain the integrity of target systems in isotope production facilities. At Los Alamos National Laboratory (LANL)’s Isotope Production Facility (IPF), multiple encapsulated targets are stacked and irradiated in tandem with a 100 MeV, ~250μA proton beam. To facilitate effective heat removal, these stacked targets are separated and cooled via a series of water channels. At these beam currents, this high-energy proton beam heats the target system, likely initiating subcooled flow boiling in the cooling channels. However, in-beam monitoring of the IPF target system is not possible due to the extreme radiation environment, and the necessarily significant shielding. To better understand high-power target performance, we developed ex-situ experimental and computational frameworks to predict the behavior of subcooled flow boiling at IPF. Subcooled flow boiling experiments on Inconel 625 samples under IPF conditions (2 bar pressure, 10 GPM flow rate (i.e., 2249 kg/m 2 /s), 85 K subcooling) revealed that IPF's average operating power is at the early stage of boiling with a heat transfer coefficient of 48,000 W/m 2 /s. The proposed modeling framework enables us to predict a complete boiling curve, i.e., single-phase heat transfer, onset of nucleate boiling, two-phase heat transfer, and critical heat flux (CHF), with specification of input boiling parameters up to intermediate heat flux levels. The estimated CHF under IPF conditions is 5.2 MW/m 2 . Experimental data under reduced conditions (2 bar pressure, 1.5 GPM flow rate (i.e., 337 kg/m 2 /s), 45 K subcooling) served as validation cases for the computational modeling. This computational model can be further extended to more complicated systems replicating the real IPF configuration, for instance, to study void distribution as a function of the incident proton beam profile and coolant velocity profile of multiple cooling channels. Finally, the proposed experimental and computational frameworks provide a means to better understand cooling systems in the isotope production facilities at different accelerators, where in-beam monitoring of the cooling process is not available.

07 ISOTOPE AND RADIATION SOURCES↗

Sensing performance of sub-100-nm vanadium oxide films for room temperature thermal detection applications

Vanadium oxide films are widely employed as thermal detectors in uncooled infrared detection systems due to their high temperature coefficient of resistance near room temperature. One strategy toward maximizing detectivity and reducing the thermal time constant in these systems is to minimize the system platform dimensions. This approach necessitates thinner film thicknesses ([Formula: see text]100 nm), for which there is little information regarding thermal sensing performance. Herein, we report on the sensitivity of reactively sputtered vanadium oxide thin film resistive thermometers nominally ranging from 100 to 25 nm and assess the influence of thermal annealing. Here we demonstrate that films in this minimum limit of thickness maintain a high temperature coefficient while additionally providing an enhancement in characteristics of the noise equivalent power.

36 MATERIALS SCIENCE↗

Renormalization of beta decay at three loops and beyond

The anomalous dimension for heavy-heavy-light effective theory operators describing nuclear beta decay is computed through three-loop order in the static limit. The result at order Z 2 α 3 corrects a previous result in the literature. An all-orders symmetry is shown to relate the anomalous dimensions at leading and subleading powers of Z at a given order of α . The first unknown coefficient for the anomalous dimension now appears at O ( Z 2 α 4 ) . Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Simulation of CEFR neutronic start-up tests with FENNECS

This paper presents simulation results of selected Neutronic Start-up Tests of the China Experimental Fast Reactor (CEFR) obtained by the neutronics code FENNECS that have been performed within the frame of the IAEA Coordinated Research Program I31032. The Finite Element Neutronics code FENNECS is developed at GRS and solves the few-group steady-state and transient diffusion equation using a Galerkin-based finite element approach. Its main purpose is the safety assessment of Small Modular Reactors and Micro Reactors with complex geometry (e.g., rotating control drums) which gain increased interest internationally. Serpent has been applied to create reference models of the CEFR and cross-section libraries in 10 energy groups for FENNECS. Using these libraries, the following experiments have been simulated with FENNECS: net criticality, control rod integral and differential worth, void reactivity effect, subassembly exchange reactivity effects and reaction rate distribution. The obtained satisfactory agreements with the measurements represent a valuable contribution to the validation of FENNECS. (author)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Field Validation of Air-Source Heat Pumps for Cold Climates

Heating energy is the largest end-use for U.S. residential buildings accounting for approximately one-third of residential building energy consumption (EIA 2021). Historically, air-source heat pumps have been limited to temperate climates because of subpar performance at extremely cold outdoor air temperatures. However, recent advances to cold-climate air-source heat pump technology, which typically rely on inverter-driven, variable-speed compressors and variable-speed fans, have significantly improved low-temperature heat pump performance enabling the technology to save energy for many homes in cold climates. The primary objective of this project was to measure in-field performance of centrally ducted, variable-capacity air-source heat pumps in cold climates to validate performance and develop field-based performance maps. The project focused on quantifying heat pump performance at cold temperatures. The sites identified for the study were primarily located in the Northwest United States since homes in the region tend to have all-electric space heating systems and high-efficiency heat pumps have been incentivized in the region for several years. NREL partnered with Ecotope, Inc., a small energy consulting firm located in Seattle, WA, for site recruitment, monitoring equipment installation, data quality management. All the sites included in the study had previously installed a high-efficiency, central heat pump system. One site was in a Denver, CO suburb, which was the only dual fuel heat pump in the study. We used airside and power measurements, collected at 5-second intervals, to quantify heat pump capacity, coefficient of performance (COP), and auxiliary heater energy consumption. We developed algorithms to automatically determine the heat pump operating mode including defrost and auxiliary heating operation. A whole-house thermal and duct audit was completed during the initial site visit to estimate winter heating loads and assess heat pump sizing. Whole-home heating design loads were calculated at ASHRAE 99% design temperatures and compared to manufacturer-reported maximum capacities to assess the heat pump sizing at each site.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Electrocaloric cooling with electrostatic actuation

A solid-state heat transporting device including a heat transporting element whose uniformity of contact with one or multiple surfaces is controllable so that various amounts of heat may be transported to and from the one or multiple surfaces. The heat transporting element uses the electrocaloric effect to absorb and release the heat and the uniformity of contact is controlled using an electrostatic effect which may change the shape of the heat transporting element. In one embodiment, the heat transporting element is an electrostatically actuated P(VDF-TrFE-CFE) polymer stack achieving a high specific cooling power of 2.8 W/g and a COP of 13 (the highest reported coefficient of performance to date) when used as a cooling device.

42 ENGINEERING↗

Quantitative comparison of power production and power quality onshore and offshore: a case study from the eastern United States

Abstract. A major issue in quantifying potential power generation from prospective wind energy sites is the lack of observations from heights relevant to modern wind turbines, particularly for offshore where blade tip heights are projected to increase beyond 250 m. We present analyses of uniquely detailed data sets from lidar (light detection and ranging) deployments in New York State and on two buoys in the adjacent New York Bight to examine the relative power generation potential and power quality at these on- and offshore locations. Time series of 10 min wind power production are computed from these wind speeds using the power curve from the International Energy Agency 15 MW reference wind turbine. Given the relatively close proximity of these lidar deployments, they share a common synoptic-scale meteorology and seasonal variability with lowest wind speeds in July and August. Time series of power production from the on- and offshore location are highly spatially correlated with the Spearman rank correlation coefficient dropping below 0.4 for separation distances of approximately 350 km. Hence careful planning of on- and offshore wind farms (i.e., separation of major plants by > 350 km) can be used reduce the system-wide probability of low wind energy power production. Energy density at 150 m height at the offshore buoys is more than 40 % higher, and the Weibull scale parameter is 2 m s−1 higher than at all but one of the land sites. Analyses of power production time series indicate annual energy production is almost twice as high for the two offshore locations. Further, electrical power production quality is higher from the offshore sites that exhibit a lower amplitude of diurnal variability, plus a lower probability of wind speeds below the cut-in and of ramp events of any magnitude. Despite this and the higher resource, the estimated levelized cost of energy (LCoE) is higher from the offshore sites mainly due to the higher infrastructure costs. Nonetheless, the projected LCoE is highly competitive from all sites considered.

Foody, Rebecca↗

High Seebeck Coefficient from Screen-Printed Colloidal PbSe Nanocrystals Thin Film

Thin-film thermoelectrics (TEs) with a thickness of a few microns present an attractive opportunity to power the internet of things (IoT). Here, we propose screen printing as an industry-relevant technology to fabricate TE thin films from colloidal PbSe quantum dots (QDs). Monodisperse 13 nm-sized PbSe QDs with spherical morphology were synthesized through a straightforward heating-up method. The cubic-phase PbSe QDs with homogeneous chemical composition allowed the formulation of a novel ink to fabricate 2 μm-thick thin films through robust screen printing followed by rapid annealing. A maximum Seebeck coefficient of 561 μV K -1 was obtained at 143 °C and the highest electrical conductivity of 123 S m -1 was reached at 197 °C. Power factor calculations resulted in a maximum value of 2.47 × 10 -5 W m -1 K -2 at 143 °C. To the best of our knowledge, the observed Seebeck coefficient value is the highest reported for TE thin films fabricated by screen printing. Thus, this study highlights that increased Seebeck coefficients can be obtained by using QD building blocks owing to quantum confinement.

36 MATERIALS SCIENCE↗

Sensitivity and uncertainty analysis of PWR spent fuel observables to operational and model parameters

Sensitivity and uncertainty analyses of spent nuclear fuel (SNF) observables - decay heat, neutron and γ-ray emission rate - to operational and model parameters have been performed. A 2D model representing a typical PWR 17x17 UO{sub 2} fuel assembly has been taken as reference. The Serpent code and ENDF/B-VII.1 evaluated nuclear data library have been used for the analyses. Relative uncertainty of decay heat, neutron and γ-ray emission rates due to Monte Carlo counting statistics, as well as the number of fuel pin radial regions required for an accurate characterization of SNF neutron emission, have been estimated. A parametric study has been carried out to investigate the impact of the homogenization to an average value of the fuel and moderator temperature, boron concentration power and burnup on the prediction of the selected observables. In addition, linear sensitivity coefficients have been calculated. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

An Investigation of the Effects of Volume Fraction on Drag Coefficient of Non-Spherical Particles Using PR-DNS

Prediction of the drag coefficient is required in gas-particle multiphase flow modeling and simulation. Experimental data and correlations on the fixed-bed system of spherical particles with high volume fractions for various possible arrangements are available in the literature. However, the effect of volume fraction on the drag coefficient of non-spherical particles is not well studied. In solving the momentum equation, the volume fraction plays a vital role in determining the flow resistances. In this paper, we study the impact of volume fraction in the range of 0.069 to 0.65 on the drag coefficient using the computational fluid dynamics (CFD) simulation of air for Reynold number in the range of 10 to 10000 using particle resolved direct numerical solution (PR-DNS). Regular non-spherical particles such as a cube, tetrahedron, and spheroids are used in this study since their single particle’s drag coefficient data are available in the literature for comparison. For this work, the simulations are carried out in the Ansys Fluent using polyhedral mesh, which consumes significantly less computational time and power. The study showed the sphericity and volume fraction have significant impact on the bed pressure drop and average drag coefficient of the particles in the bed especially in high Reynolds number regime. The bed of the spheroid experiences the lowest drag being the most streamlined particle, and the particles with the edges result in a large drag coefficient due to flow separation at the discontinuity. The vector plots verify this behavior where large wake regions are observed behind the tetrahedron particle.

Mahyawansi, Pratik↗

Simulation of the SPARC plasma boundary with the UEDGE code

Here in this work, the UEDGE edge transport code is used to examine conditions in the SPARC divertor and edge plasma for various levels of carbon impurity and power from the core (P SOL ). A double-null magnetic configuration is simulated assuming up-down symmetry in geometry and physics. The anomalous heat and particle transport coefficients are tuned to match empirical predictions for SPARC's midplane density profiles, target plate heat flux profiles, and inner/outer divertor power sharing. Convective transport is included on the low-field side, while on the high-field side the transport is modeled as purely diffusive. Hydrogen neutrals are modeled as a fluid with inertial effects, and a carbon impurity is included using the fixed-fraction model. We find that detachment induced by impurity seeding could significantly reduce the heat flux to the divertor surfaces in the SPARC tokamak. At P SOL = 28 MW (the value predicted for SPARC's full-power H-mode scenario) cases with both divertor legs detached were obtained with a carbon impurity fraction between 0.3%–1.4%, far below Z eff limits for SPARC. When the plasma in the outer leg is detached, the peak heat flux density perpendicular to the target plate is below 1 MW m -2 , electron and ion temperatures are less than 1.5 eV, and momentum detachment is observed. However, the detachment state is found to be sensitive to the side-wall boundary conditions, the level of neutral pumping, and the target plate tilt. Finally, a broadly similar SOLPS simulation of SPARC is used to assess the appropriateness of the simpler impurity and neutral models used in UEDGE.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Multitiered computational methodology for extracting three-dimensional rotational diffusion coefficients from x-ray photon correlation spectroscopy data without structural information

X-ray photon correlation spectroscopy (XPCS) is a powerful technique for analyzing particle systems by investigating their dynamics in suspensions across a broad range of temporal and spatial scales. This is done by illuminating samples with coherent x-ray beams and calculating the correlation function of the obtained x-ray scattering images. XPCS is uniquely suited for studying Brownian dynamics, consisting of translational and rotational diffusion. While traditional XPCS image analysis techniques can extract translational diffusion components, they are unable to estimate rotational diffusion coefficients. Here, we introduce a methodology that combines the angular-temporal cross-correlation analysis and a algorithmic framework called Multi-Tiered Estimation for Correlation Spectroscopy in 3D for estimating three-dimensional rotational diffusion coefficients from XPCS images of three-dimensional particle systems. We demonstrate our methodology for extracting rotational diffusion coefficients from XPCS data by applying it to simulated noisy x-ray images of systems of crossing nanotubes and proteins that evolve under translational and rotational Brownian motion for different diffusion rates. Furthermore, our results show that our approach determines rotational diffusion coefficients within a few percent error.

97 MATHEMATICS AND COMPUTING↗

Dynamic Model Development of a Wind Power Plant Using Neural Net Method to Forecast Wind Power Output (CRADA Final Report)

This project is intended to model wind power plant based on monitored data at the wind power plant. This project will promote the university research in Renewable Energy area and trains the future highly qualified engineers. The dynamic model will be based on neural net model with the input from the two met towers (12 inputs), and the number of turbines in operation (one input). The overall input will be 13 inputs to drive the simulations. The output power at the point of interconnection will be used to tune the neural net weight coefficients. Two neural net concepts will be investigated (the back propagation neural net and the dynamic recurrent neural net with feedback).

17 WIND ENERGY↗

Interfacial characteristics of P91 steel - Inconel 740H bimetallic structure fabricated using wire-arc additive manufacturing

Although bimetallic structures can offer unique solutions to engineering problems with varying functionality, joining two dissimilar alloys using additive manufacturing involves challenges such as cracking and segregation. In this work, bimetallic structures of Inconel 740H superalloy and P91 steel are processed using wire-arc additive manufacturing (WAAM) for the first time. P91 steel is directly deposited over 740H with a cooling time of 20 minutes in between the two depositions. During microstructure characterization, a large gradient zone with coarse grains spanning for ~2200 μm is observed. Moreover, the microhardness of the gradient zone is the least in comparison with the P91 and 740H deposits. No deleterious phase formation is found; however, intergranular cracks are observed along the gradient zone. In order to deduce the reason for cracking, non-equilibrium solidification simulations are performed for the mixed compositions of P91 and 740H in the gradient zone. Here, the reasons for crack formation in the gradient zone are the sudden change in the volumetric coefficient of thermal expansion due to the formation of MC carbides as well as the development of local strains from the thermal residual stresses. Therefore, altering the deposition sequence and introducing gradient layers with mixed composition between the P91 and 740H deposits will be beneficial in achieving defect-free builds. Through the integration of experiments and simulation, this work gains valuable insights into the processability of dissimilar alloy manufacturing using the WAAM technique.

20 FOSSIL-FUELED POWER PLANTS↗

High temperature thick film sensor development based on doped lanthanum chromites refractory semiconductors materials

High temperature advanced sensing materials have generated high demand due the high accuracy temperature measurements requirements for process optimization, controlling and sensing. Some technological applications of harsh conditions sensing include monitoring tiles of space shuttles, rotating bearings in aircraft engines, turbines, jet engines dynamics and chemical reactors. High temperature conditions limit the sensing strategies, where typically traditional metal thermocouples are unstable, and the sensing options are limited to optical spectroscopy methods. Recently, refractory semiconductors thick- and thin-film thermocouples have been developed and, in many cases, preferred over conventional metallic thermocouples due their spatial resolution, and capability of direct deposition on any surface. Rare earth chromites ceramics materials, exhibit some properties of interest for high temperature sensing technologies development, such as: high microstructure and sintering stability, excellent conductive behavior at high temperatures, and matching thermal expansion coefficients relative to other conductors and refractory ceramics. In this work, high performance ultra-high temperature thermocouples using p-type and n-type doped lanthanum chromites materials were fabricated and tested at temperatures up to 1500 o C. Thermoelectric voltage, Seebeck Coefficients were established for all devices, evidencing high stability and performance in prolongated operational time and harsh conditions.

20 FOSSIL-FUELED POWER PLANTS↗

Factorial growth at low orders in perturbative QCD: control over truncation uncertainties

A method, known as “minimal renormalon subtraction”, relates the factorial growth of a perturbative series (in QCD) to the power p of a power correction Λ p /Q p . (Λ is the QCD scale, Q some hard scale.) Here, the derivation is simplified and generalized to any p , more than one such correction, and cases with anomalous dimensions. Strikingly, the well-known factorial growth is seen to emerge already at low or medium orders, as a consequence of constraints on the Q dependence from the renormalization group. The effectiveness of the method is studied with the gluonic energy between a static quark and static antiquark (the “static energy”). Truncation uncertainties are found to be under control after next-to-leading order, despite the small exponent of the power correction ( p = 1) and associated rapid growth seen in the first four coefficients of the perturbative series.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Harnessing Machine Learning to Predict MoS 2 Solid Lubricant Performance

Physical vapor deposited (PVD) molybdenum disulfide (MoS 2 ) solid lubricant coatings are an exemplar material system for machine learning methods due to small changes in process variables often causing large variations in microstructure and mechanical/tribological properties. Here, in this work, a gradient boosted regression tree machine learning method is applied to an existing experimental data set containing process, microstructure, and property information to create deeper insights into the process-structure–property relationships for molybdenum disulfide (MoS 2 ) solid lubricant coatings. The optimized and cross-validated models show good predictive capabilities for density, reduced modulus, hardness, wear rate, and initial coefficients of friction. The contribution of individual deposition variables (i.e., argon pressure, deposition power, target conditioning) on coating properties is highlighted through feature importance. The process-property relationships established herein show linear and non-linear relationships and highlight the influence of uncontrolled deposition variables (i.e., target conditioning) on the tribological performance.

MoS2↗

Low-energy Scattering and Effective Interactions of Two Baryons at $m_{\pi}\sim$ 450 MeV from Lattice Quantum Chromodynamics

The interactions between two octet baryons are studied at low energies using lattice QCD (LQCD) with larger-than-physical quark masses corresponding to a pion mass of $m_{\pi}\sim 450$ MeV and a kaon mass of $m_{K}\sim 596$ MeV. The two-baryon systems that are analyzed range from strangeness $S=0$ to $S=-4$ and include the spin-singlet and triplet $NN$, $\Sigma N$ ($I=3/2$), and $\Xi\Xi$ states, the spin-singlet $\Sigma\Sigma$ ($I=2$) and $\Xi\Sigma$ ($I=3/2$) states, and the spin-triplet $\Xi N$ ($I=0$) state. The $s$-wave scattering phase shifts, low-energy scattering parameters, and binding energies when applicable, are extracted using L\"uscher's formalism. While the results are consistent with most of the systems being bound at this pion mass, the interactions in the spin-triplet $\Sigma N$ and $\Xi\Xi$ channels are found to be repulsive and do not support bound states. Using results from previous studies at a larger pion mass, an extrapolation of the binding energies to the physical point is performed and is compared with experimental values and phenomenological predictions. The low-energy coefficients in pionless EFT relevant for two-baryon interactions, including those responsible for $SU(3)$ flavor-symmetry breaking, are constrained. The $SU(3)$ symmetry is observed to hold approximately at the chosen values of the quark masses, as well as the $SU(6)$ spin-flavor symmetry, predicted at large $N_c$. A remnant of an accidental $SU(16)$ symmetry found previously at a larger pion mass is further observed. The $SU(6)$-symmetric EFT constrained by these LQCD calculations is used to make predictions for two-baryon systems for which the low-energy scattering parameters could not be determined with LQCD directly in this study, and to constrain the coefficients of all leading $SU(3)$ flavor-symmetric interactions, demonstrating the predictive power of two-baryon EFTs matched to LQCD.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗