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Blade Designs For Improved Multi-Phase Performance In sCO 2 Compressors; Part II - Optical Diagnostics In sCO 2 And Experimental Evaluation With Particle Image Velocimetry

This paper presents the second part of a study in which the leading-edge and suction surface of a compressor blade was modified to delay onset of phase change for sCO 2 compressors operating near the critical point. Using a first-of-its-kind apparatus for the measurement of sCO 2 flow fields, Particle Image Velocimetry (PIV) is used for local flow field measurements of two compressor blade geometries: the modified “biased-wedge,” and a conventional constant thickness blade. Utilizing the developed hardware, the feasibility of a simple, laser-based diagnostic for qualitatively measuring liquid phase regions, is also presented. The design of the optical diagnostics rig, a discussion of numerous challenges, and necessary considerations involved in performing optical-based measurements like PIV, in sCO 2 , are discussed. Velocity field measurements for the modified compressor profile show a much lower suction peak compared to a conventional blade. Furthermore, these results validate numerical results at the tested conditions, where the suction side profile of the biased wedge works to minimize the local pressure gradient.

14 SOLAR ENERGY

Development of a coupled experimental–computational approach for engineering optimization of spout-fluidized bed particle coating systems

The design of spout-fluidized bed (SFB) coating systems for nuclear particle fuels typically relies on trial-and-error processes, comprising iterative and time-consuming coating deposition experiments and post-deposition characterization. At an engineering scale, this approach to guided SFB system design is inefficient, highlighting the need for streamlined experimental methodologies which can correlate fluidization conditions to downstream coating outcomes. In this study, we combine time-resolved particle image velocimetry (PIV) with CFD–DEM simulations to benchmark hydrodynamic behavior in a 3D spout-fluidized bed. By exploiting easily accessible optical measurements of particle motion at the bed wall and within the spouting region, we obtain quantitative velocity fields that can be directly compared with model predictions of the occluded bed region, without resorting to complex imaging and characterization techniques such as X-ray or magnetic resonance tomography. Experimental benchmarking reveals strong agreement between CFD–DEM and PIV in the spout and annulus regions, while discrepancies near the wall highlight areas for future model development. Here, the proposed integrated experimental–numerical framework will enable a direct connection between measured variables and numerically predicted fluidization performance of dense, surrogate nuclear particle fuel feedstock such that experimental SFB component design can be rapidly evaluated, informing design decisions for nozzle geometry and operating conditions. Future work will extend this framework by correlating quantified fluidization metrics across nozzle geometries and operating conditions with the resulting coating morphology, microstructure, and uniformity. Establishing these correlations will enable predictive links between hydrodynamic performance and coating quality, providing a rational, scalable basis for optimizing SFB design prior to coating deposition.

CFD/DEM

Multimode turbulent flow measurements using magnetic resonance imaging- and laser-based techniques and computational fluid dynamics simulations

We studied the flow field characteristics of a turbulent flow over a regularized cube array with a perpendicular injection flow through the floor between the second and third cubical elements, representing the complex flow interactions of a 3D jet and the wake flows behind cubical obstacles. Four different experimental measurements were performed: two magnetic resonance imaging-based measurements for three-dimensional three-component velocity (MRV) and concentration (MRC) and two laser-based techniques, particle image velocimetry (PIV) and planar laser-induced fluorescence (PLIF), for two-dimensional two-component velocity and concentration measurement, respectively. The mainstream Reynolds number is Re = 15 000⁠, based on the primary inlet velocity U m and channel height D H ⁠, whereas the injector Reynolds number is Re j = 3400⁠, based on the injector velocity U j and the injector's exit width D j ⁠. Numerical simulations were performed for the studied flow configuration of turbulent flow over a regularized cube array using Reynolds-averaged Navier–Stokes (RANS) and large-eddy simulation (LES) approaches. Results obtained from experimental measurements—including MRV, MRC, PIV, and PLIF—as well as RANS and LES simulations are discussed and compared along several horizontal and vertical planes of the studied configuration. In addition, 3D turbulent flow structures, such as leading-edge vortex, horseshoe vortex, and jet shear-layer vortex, and the isosurfaces of scalar concentration successfully revealed by MRV and MRC techniques were found to be in very good agreement with those 3D features extracted from RANS and LES simulations. In conclusion, the high-resolution experimental and numerical database obtained from this study could be useful for validation and verification of numerical codes.

Computational fluid dynamics

Time evolution of a pumped molecular magnet—A time-resolved inelastic neutron scattering study

Introducing an experimental technique of time-resolved inelastic neutron scattering (TRINS), we explore the time-dependent effects of resonant pulsed microwaves on the molecular magnet Cr 8 F 8 Piv 16 . The octagonal rings of magnetic Cr 3+ atoms with antiferromagnetic interactions form a singlet ground state with a weakly split triplet of excitations at 0.8 meV. A 4.6 tesla field was applied to tune the splitting between two members of the triplet excited level |1$\rangle$ ↔ |2$\rangle$ to resonance with 105 GHz (0.434 meV) microwaves. The time-dependent occupations of the ground state |0$\rangle$, lower lying levels |1$\rangle$ and |2$\rangle$, and higher energy states |λ ≥ 3$\rangle$ were extracted during and after 20 s long microwave pulses incident along the (101) direction of a Cr 8 F 8 Piv 16 crystal held at 1.9 K. At significantly elevated spin temperatures, we found underpopulation relative to thermal equilibrium of |2$\rangle$ and spin-lattice thermalization time scales ranging from 1.6(2) s to 5.7(2) s depending on the power level. This contrasts with the relaxation time τ 1 (T → 0) = 27(5) 𝛍 s inferred for |2$\rangle$ from in situ Electron Spin Resonance measurements. By probing a broad range of excited states during intense microwave pumping, TRINS thus provides a first view of long lived excited states in a molecular antiferromagnet.

Science & Technology - Other Topics

Flow and Performance Characterization of Rotating Detonation Combustor Integrated with Various Convergent Nozzles

In this study, convergent nozzles of various area ratios (ARs) are used downstream of an annular rotating detonation combustor (RDC) to increase the operating pressure and approach sonic conditions at the nozzle throat. Reactant methane and oxygen-enriched air (67% [Formula: see text] and 33% [Formula: see text] by volume) are supplied in counterflow arrangement from two separate plenums located at the base of the RDC annulus. Based on experimentation, a total mass flow rate of [Formula: see text] was chosen to achieve stable, single-wave mode RDC operation for all test cases, allowing for one-to-one comparisons. The internal performance of the RDC was characterized by ion probes and pressure measurements (wall static and oscillating) in supply plenums and across different axial locations of the combustor. Particle image velocimetry (PIV) at 100 kHz was utilized to measure axial and circumferential velocity components within a two-dimensional region of interest located downstream of the converging nozzle exit. Results show higher internal performance of the RDC with increasing AR of the convergent nozzle. PIV measurement illustrated that the flow oscillation amplitudes decrease with an increasing AR of the converging nozzle. The exit flow contained significant nonuniformity and unsteadiness even with a converging nozzle of AR 2.0, indicating incomplete choking of the flow at the nozzle throat.

Engineering

NeuroSEM: A hybrid framework for simulating multiphysics problems by coupling PINNs and spectral elements

Multiphysics problems that are characterized by complex interactions among fluid dynamics, heat transfer, structural mechanics, and electromagnetics, are inherently challenging due to their coupled nature. While experimental data on certain state variables may be available, integrating these data with numerical solvers remains a significant challenge. Physics-informed neural networks (PINNs) have shown promising results in various engineering disciplines, particularly in handling noisy data and solving inverse problems in partial differential equations (PDEs). However, their effectiveness in forecasting nonlinear phenomena in multiphysics regimes, particularly involving turbulence, is yet to be fully established. Here, this study introduces NeuroSEM, a hybrid framework integrating PINNs with the highfidelity Spectral Element Method (SEM) solver, Nektar++. NeuroSEM leverages the strengths of both PINNs and SEM, providing robust solutions for multiphysics problems. PINNs are trained to assimilate data and model physical phenomena in specific subdomains, which are then integrated into the Nektar++ solver. We demonstrate the efficiency and accuracy of NeuroSEM for thermal convection in cavity flow and flow past a cylinder. The framework effectively handles data assimilation by addressing those subdomains and state variables where the data is available. We applied NeuroSEM to the Rayleigh-B´enard convection system, including cases with missing thermal boundary conditions and noisy datasets. Finally, we applied the proposed NeuroSEM framework to real particle image velocimetry (PIV) data to capture flow patterns characterized by horseshoe vortical structures. Our results indicate that NeuroSEM accurately models the physical phenomena and assimilates the data within the specified subdomains. The framework’s plug-and-play nature facilitates its extension to other multiphysics or multiscale problems. Furthermore, NeuroSEM is optimized for efficient execution on emerging integrated GPU-CPU architectures. This hybrid approach enhances the accuracy and efficiency of simulations, making it a powerful tool for tackling complex engineering challenges in various scientific domains.

42 ENGINEERING

A miniature jet pump for slurries

Here, this work reports on the design and performance of a jet pump system to pump slurries. The jet pump uses a high-velocity water jet to entrain and pump the slurry. This pumping action requires no valves and does not use moving solid parts. Hence, the system can be readily sealed, and the pumping action creates no observable mechanical damage to slurry particles. We tested carbon black beads suspended in water at concentrations of 0.0, 0.2, and 2.0 wt% at primary jet flow rates of 50 and 100 mL/min. Our measurements show an approximately linear decrease in entrainment ratio (slurry-to-jet flow rate) and absolute slurry flow rate with increasing adverse (load) pressure difference. The entrainment ratio is a strong function of the absolute jet flow rate. Pump performance was insensitive to slurry composition. Micron-resolution particle image velocimetry (micro-PIV) revealed qualitative changes in the pump’s internal flow due to changes in absolute jet flow rate, including evidence of the suppression of a vortex at higher flow rates. These findings establish key operational parameters for the jet pump and highlight its potential in a variety of slurry flow pumping applications. The pump is particularly suited for flow electrode slurries (e.g. as used for energy storage and water treatment) as it maintains particle integrity and can be used with standard tubing, tube fittings, and sealing methods.

42 ENGINEERING

BOS Gas Detection Pipeline (Integrated System for Optical Hydrogen Detection Using Background Oriented Schlieren and Machine Learning) [SWR-26-007]

This software is the world's first integrated background oriented schlieren and machine learning-based leak detection system. The system provides real time visualization of gas leaks and machine learning interpenetration of leak severity. The software is supplemented by SWR-25-177, "gpu_piv (Graphics Processing Unit Accelerated Background Oriented Schlieren Algorithm", also developed by the National Laboratory of the Rockies. SEE DOECODE ID 182832.

Palin, Ian [National Laboratory of the Rockies (NL

Advancements in Heat Transfer and Fluid Mechanics (Fundamentals and Applications)

Thermo-fluid science is a foundational discipline for numerous mechanical systems, particularly in energy production and building equipment, where thermal and mechanical energy transfer play critical roles. Advancements in heat transfer and fluid mechanics have significantly enhanced these systems, driving progress in associated market sectors. For instance, evaporator and condenser coils are essential for optimizing vapor compression cycles in building equipment. Heat pumps used for space and water heating constitute a major share of building systems, with microchannel heat exchanger technology at the forefront of these innovations. It is worth mentioning that advancements in heat transfer and fluid mechanics significantly alleviate the challenge of designing energy-efficient building equipment. The development of research techniques has contributed significantly to the advancement of science; for example, in the experimental field, non-intrusive measurement techniques such as Particle Image Velocimetry (PIV) are now capable of resolving flow behavior in a 3D format for different length and time scales.

42 ENGINEERING

Multicycle large-eddy simulations of a direct-injection hydrogen-fueled optical engine

Hydrogen (H 2 ) is a carbon-free chemical energy carrier and one promising solution for achieving effective decarbonization of the transportation sector, particularly for internal combustion engines (ICEs). With a focus on ICEs, and compared to port-fuel injection, direct injection (DI) of gaseous H 2 during the compression stroke offers potential advantages, which include backfire avoidance and reduction of preignition occurrence. In these last two decades, much research, experimental and numerical, has been devoted to understanding H 2 's mixing and combustion processes in ICEs. Computational fluid dynamics modeling efforts commonly rely on unsteady Reynolds-averaged Navier Stokes (URANS) turbulence frameworks, mostly due to their computational affordability. However, many authors have pointed out the opportunity to perform large-eddy simulations (LESs) to investigate the cyclic variability of H 2 engines and assess potential advantages of using LES in place of URANS, especially for lean operation. This study addresses this knowledge gap and presents a computational fluid dynamics (CFD) study of the H 2 DI process in an optical engine operating at relatively low tumble conditions, using multicycle LESs. In conclusion, the manuscript presents a thorough validation of the results against experimental data available from the literature as well as direct comparison with URANS, demonstrating the feasibility of multicycle LESs for CFD modeling of DI H 2 -fueled ICEs.

Direct injection

One-shot omnidirectional pressure integration through matrix inversion

In this work, we present a method to perform 2D and 3D omnidirectional pressure integration from velocity measurements with a single-iteration matrix inversion approach. This work builds upon our previous work, where the rotating parallel ray approach was extended to the limit of infinite rays by taking continuous projection integrals of the ray paths and recasting the problem as an iterative matrix inversion problem. This iterative matrix equation is now 'fast-forwarded' to the 'infinity' iteration, leading to a different matrix equation that can be solved in a single step, thereby presenting the same computational complexity as the Poisson equation. We observe computational speedups of ~10 6 when compared to brute-force omnidirectional integration methods, enabling the treatment of grids of ~10 9 points and potentially even larger in a desktop setup at the time of publication. Further examination of the boundary conditions of our one-shot method shows that omnidirectional pressure integration implements a boundary condition where the boundary points are treated as interior points to the extent that information is available. Finally, we show how the method can be extended from the regular grids typical of particle image velocimetry to the unstructured meshes characteristic of particle tracking velocimetry data.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC