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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Quantifying sensitivity in numerical weather prediction-modeled offshore wind speeds through an ensemble modeling approach

A decade of research has shown that numerical weather prediction (NWP)-modeled wind speeds can be highly sensitive to the inputs and setups within the NWP model. For wind resource characterization applications, this sensitivity is often addressed by constructing a range of setups and selecting the one that best validates against observations. However, this approach is not possible in areas that lack high-quality hub height observations, especially offshore wind areas. In such cases, techniques to quantify and disseminate confidence in NWP-modeled wind speeds in the absence of observations are needed. We address this need in the present study and propose best practices for quantifying the spread in NWP-modeled wind speeds. We implement an ensemble approach in which we consider 24 different setups to the Weather Research and Forecasting (WRF) model. We construct the ensemble by considering variations in WRF version, WRF namelist, atmospheric forcing, and sea surface temperature (SST) forcing. Our analysis finds that the standard deviation produces more consistent estimates compared to the interquartile range and tends to be the more conservative estimator for ensemble variability. We further find that model spread increases closer to the surface and on shorter time scales. In conclusion, we explore methods to attribute total ensemble variability to the different ensemble components (e.g., atmospheric forcing and SST product) and find that contributions by components also vary depending on time scale. We anticipate that the methods and results presented in this paper will provide a reasonable foundation for further research into ensemble-based wind resource data sets.

17 WIND ENERGY↗
DOE OSTI2017

Low- and high-order accurate boundary conditions: From Stokes to Darcy porous flow modeled with standard and improved Brinkman lattice Boltzmann schemes

The present contribution focuses on the accuracy of reflection-type boundary conditions in the Stokes–Brinkman–Darcy modeling of porous flows solved with the lattice Boltzmann method (LBM), which we operate with the two-relaxation-time (TRT) collision and the Brinkman-force based scheme (BF), called BF-TRT scheme. In parallel, we compare it with the Stokes–Brinkman–Darcy linear finite element method (FEM) where the Dirichlet boundary conditions are enforced on grid vertices. In bulk, both BF-TRT and FEM share the same defect: in their discretization a correction to the modeled Brinkman equation appears, given by the discrete Laplacian of the velocity-proportional resistance force. This correction modifies the effective Brinkman viscosity, playing a crucial role in the triggering of spurious oscillations in the bulk solution. While the exact form of this defect is available in lattice-aligned, straight or diagonal, flows; in arbitrary flow/lattice orientations its approximation is constructed. At boundaries, we verify that such a Brinkman viscosity correction has an even more harmful impact. Already at the first order, it shifts the location of the no-slip wall condition supported by traditional LBM boundary schemes, such as the bounce-back rule. For that reason, this work develops a new class of boundary schemes to prescribe the Dirichlet velocity condition at an arbitrary wall/boundary-node distance and that supports a higher order accuracy in the accommodation of the TRT-Brinkman solutions. For their modeling, we consider the standard BF scheme and its improved version, called IBF; this latter is generalized in this work to suppress or to reduce the viscosity correction in arbitrarily oriented flows. Our framework extends the one- and two-point families of linear and parabolic link-wise boundary schemes, respectively called B-LI and B-MLI, which avoid the interference of the Brinkman viscosity correction in their closure relations. The performance of LBM and FEM is thoroughly evaluated in three benchmark tests, which are run throughout three distinctive permeability regimes. The first configuration is a horizontal porous channel, studied with a symbolic approach, where we construct the exact solutions of FEM and BF/IBF with different boundary schemes. The second problem refers to an inclined porous channel flow, which brings in as new challenge the formation of spurious boundary layers in LBM; that is, numerical artefacts that arise due to a deficient accommodation of the bulk solution by the low-accurate boundary scheme. The third problem considers a porous flow past a periodic square array of solid cylinders, which intensifies the previous two tests with the simulation of a more complex flow pattern. The ensemble of numerical tests provides guidelines on the effect of grid resolution and the TRT free collision parameter over the accuracy and the quality of the velocity field, spanning from Stokes to Darcy permeability regimes. It is shown that, with the use of the high-order accurate boundary schemes, the simple, uniform-mesh-based TRT-LBM formulation can even surpass the accuracy of FEM employing hardworking body-fitted meshes.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Acquire and Test IDAES Framework Components

The cooperation under the Grid Modernization Initiative and the Applied Energy Tri-Laboratory umbrellas requires mutual understanding of capabilities and a common effort to identify gaps existing in the available computational modeling and analysis tools. In this work, we report acquisition and testing of the National Energy Technology Laboratory’s Institute for the Design of Advanced Energy Systems (IDAES) framework, particularly including both electric power systems production cost model simulator Prescient as well as system optimization IDAES itself. Further, we consider the methods in which developments in Prescient and IDAES for grid-energy simulation and optimization may be included in the Framework for Optimization of ResourCes and Economics (FORCE) ecosystem that has been under collaborative development by Idaho National Laboratory, Argonne National Laboratory, and Oak Ridge National Laboratory. We propose two integration methods to introduce Prescient and IDAES into existing FORCE automated workflows. One integration involves using Prescient as a market reduced-order model and IDAES models similar to how existing Modelica models are used. The other integration involves wrapping the Prescient-IDAES dispatch optimization process with the stochastic capacity optimization workflow in FORCE.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2014

WE-G-BRF-09: Force- and Image-Adaptive Strategies for Robotised Placement of 4D Ultrasound Probes

Purpose: To allow continuous acquisition of high quality 4D ultrasound images for non-invasive live tracking of tumours for IGRT, image- and force-adaptive strategies for robotised placement of 4D ultrasound probes are developed and evaluated. Methods: The developed robotised ultrasound system is based on a 6-axes industrial robot (adept Viper s850) carrying a 4D ultrasound transducer with a mounted force-torque sensor. The force-adaptive placement strategies include probe position control using artificial potential fields and contact pressure regulation by a PD controller strategy. The basis for live target tracking is a continuous minimum contact pressure to ensure good image quality and high patient comfort. This contact pressure can be significantly disturbed by respiratory movements and has to be compensated. All measurements were performed on human subjects under realistic conditions. When performing cardiac ultrasound, rib- and lung shadows are a common source of interference and can disrupt the tracking. To ensure continuous tracking, these artefacts had to be detected to automatically realign the probe. The detection is realised by multiple algorithms based on entropy calculations as well as a determination of the image quality. Results: Through active contact pressure regulation it was possible to reduce the variance of the contact pressure by 89.79% despite respiratory motion of the chest. The results regarding the image processing clearly demonstrate the feasibility to detect image artefacts like rib shadows in real-time. Conclusion: In all cases, it was possible to stabilise the image quality by active contact pressure control and automatically detected image artefacts. This fact enables the possibility to compensate for such interferences by realigning the probe and thus continuously optimising the ultrasound images. This is a huge step towards fully automated transducer positioning and opens the possibility for stable target tracking in ultrasoundguided radiation therapy requiring contact pressure of 5–10 N. This work was supported by the Graduate School for Computing in Medicine and Life Sciences funded by Germany's Excellence Initiative [DFG GSC 235/1].

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Emissions and temperature benefits: The role of wind power in China

Background: As a non-fossil technology, wind power has an enormous advantage over coal because of its role in climate change mitigation. Therefore, it is important to investigate how substituting wind power for coal-fired electricity will affect emission reductions, changes in radiative forcing and rising temperatures, particularly in the context of emission limits. Methods: We developed an integrated methodology that includes two parts: an energy-economy-environmental (3E) integrated model and an emission-temperature response model. The former is used to simulate the dynamic relationships between economic output, wind energy and greenhouse gas (GHG) emissions; the latter is used to evaluate changes in radiative forcing and warming. Results: Under the present development projection, wind energy cannot serve as a major force in curbing emissions, even under the strictest space-restraining scenario. China's temperature contribution to global warming will be up to 21.76% if warming is limited to 2 degrees. With the wind-for-coal power substitution, the corresponding contribution to global radiative forcing increase and temperature rise will decrease by up to 10% and 6.57%, respectively. Conclusions: Substituting wind power for coal-fired electricity has positive effects on emission reductions and warming control. However, wind energy alone is insufficient for climate change mitigation. It forms an important component of the renewable energy portfolio used to combat global warming. - Highlights: • We assess the warming benefits associated with substitution of wind power for coal. • The effect of emission space limits on climate responses is deeply examined. • China is responsible for at most 21.76% of global warming given the 2-degree target. • Wind power alone may not be sufficient to face the challenge of climate change. • A fertile policy soil and an aggressive plan are necessary to boost renewables.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

MAGNETO-FRICTIONAL MODELING OF CORONAL NONLINEAR FORCE-FREE FIELDS. I. TESTING WITH ANALYTIC SOLUTIONS

We report our implementation of the magneto-frictional method in the Message Passing Interface Adaptive Mesh Refinement Versatile Advection Code (MPI-AMRVAC). The method aims at applications where local adaptive mesh refinement (AMR) is essential to make follow-up dynamical modeling affordable. We quantify its performance in both domain-decomposed uniform grids and block-adaptive AMR computations, using all frequently employed force-free, divergence-free, and other vector comparison metrics. As test cases, we revisit the semi-analytic solution of Low and Lou in both Cartesian and spherical geometries, along with the topologically challenging Titov–Démoulin model. We compare different combinations of spatial and temporal discretizations, and find that the fourth-order central difference with a local Lax–Friedrichs dissipation term in a single-step marching scheme is an optimal combination. The initial condition is provided by the potential field, which is the potential field source surface model in spherical geometry. Various boundary conditions are adopted, ranging from fully prescribed cases where all boundaries are assigned with the semi-analytic models, to solar-like cases where only the magnetic field at the bottom is known. Our results demonstrate that all the metrics compare favorably to previous works in both Cartesian and spherical coordinates. Cases with several AMR levels perform in accordance with their effective resolutions. The magneto-frictional method in MPI-AMRVAC allows us to model a region of interest with high spatial resolution and large field of view simultaneously, as required by observation-constrained extrapolations using vector data provided with modern instruments. The applications of the magneto-frictional method to observations are shown in an accompanying paper.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Using Computationally-Determined Properties for Machine Learning Prediction of Self-Diffusion Coefficients in Pure Liquids

The ability to predict transport properties of liquids quickly and accurately will greatly improve our understanding of fluid properties both in bulk and complex mixtures, as well as in confined environments. Such information could then be used in the design of materials and processes for applications ranging from energy production and storage to manufacturing processes. As a first step, we consider the use of machine learning (ML) methods to predict the diffusion properties of pure liquids. Recent results have shown that Artificial Neural Networks (ANNs) can effectively predict the diffusion of pure compounds based on the use of experimental properties as the model inputs. In the current study, a similar ANN approach is applied to modeling diffusion of pure liquids using fluid properties obtained exclusively from molecular simulations. A diverse set of 102 pure liquids is considered, ranging from small polar molecules (e.g., water) to large nonpolar molecules (e.g., octane). Self-diffusion coefficients were obtained from classical molecular dynamics (MD) simulations. Since nearly all the molecules are organic compounds, a general set of force field parameters for organic molecules was used. The MD methods are validated by comparing physical and thermodynamic properties with experiment. Computational input features for the ANN include physical properties obtained from the MD simulations as well as molecular properties from quantum calculations of individual molecules. Furthermore, fluid properties describing the local liquid structure were obtained from center of mass radial distribution functions (COM-RDFs). Feature sensitivity analysis revealed that isothermal compressibility, heat of vaporization, and the thermal expansion coefficient were the most impactful properties used as input for the ANN model to predict the MD simulated self-diffusion coefficients. The MD-based ANN successfully predicts the MD self-diffusion coefficients with only a subset (2 to 3) of the available computationally determined input features required. A separate ANN model was developed using literature experimental self-diffusion coefficients as model targets. Although this second ML model was not as successful due to a limited number of data points, a good correlation is still observed between experimental and ML predicted self-diffusion coefficients.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2013

A Case Study of Truncated Electrostatics for Simulation of Polyelectrolyte Brushes on GPU Accelerators

Numerous issues have disrupted the trend for increasing computational performance with faster CPU clock frequencies. In order to exploit the potential performance of new computers, it is becoming increasingly desirable to re-evaluate computational physics methods and models with an eye towards towards approaches that allow for increased concurrency and data locality. The evaluation of long-range Coulombic interactions is a common bottleneck for molecular dynamics simulations. Enhanced truncation approaches have been proposed as an alternative method and are particularly well suited for many-core architectures and GPUs due to the inherent fine-grain parallelism that can be exploited. In this paper, we compare efficient truncation-based approximations to evaluation of electrostatic forces with the more traditional particle-particle particle-mesh (P3M) method for molecular dynamics simulation of polyelectrolyte brush layers. We show that with the use of GPU accelerators, large parallel simulations using P3M can be greater than 3 times faster due to a reduction in the mesh-size required. Alternatively, using a truncation-based scheme can improve performance even further. This approach can be up to 3.9 times faster than GPU-accelerated P3M for many polymer systems and results in accurate calculation of shear velocities and disjoining pressures for brush layers. For configurations with highly non-uniform charge distributions, however, we find that it is more efficient to use P3M; for these systems, computationally efficient parameterizations of the truncation-based approach do not produce accurate counterion density profiles or brush morphologies.

Nguyen, Trung D↗
DOE OSTI2013

Monte Carlo solution for uncertainty propagation in particle transport with a stochastic Galerkin method

The stochastic Galerkin method (SGM) is an intrusive technique for propagating data uncertainty in physical models. The method reduces the random model to a system of coupled deterministic equations for the moments of stochastic spectral expansions of result quantities. We investigate solving these equations using the Monte Carlo technique. We compare the efficiency with brute-force Monte Carlo evaluation of uncertainty, the non-intrusive stochastic collocation method (SCM), and an intrusive Monte Carlo implementation of the stochastic collocation method. We also describe the stability limitations of our SGM implementation. (authors)

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Computational Studies of Water-Exchange Rates around Aqueous Mg2+ and Be2+

The water-exchange mechanisms occurring around aqueous divalent Mg2+ and Be2+ ions were studied using molecular dynamics simulations and rate theory methods. Properties associated with the water-exchange process, such as ion-water potentials of mean force, time-dependent transmission coefficients, and rate constants, were examined along with transition rate theory and the reactive flux method, which includes the role of solvent friction. The effects of pressure on water-exchange rates and activation volumes also were studied. The simulated activation volume values and mechanism were different for Mg2+ and Be2+ because of the nature of their solvation shells. We found the agreement with experiments was improved up on solvent effects were taken into account. The Division of Chemical Sciences, Geosciences, and Biosciences, Office of Basic Energy Sciences (BES), of the U.S. Department of Energy (DOE) funded this work. Battelle operates Pacific Northwest National Laboratory for DOE. The calculations were carried out using computer resources provided by BES.

Dang, Liem X.↗
DOE OSTI2014

Stochastic many-body perturbation theory for anharmonic molecular vibrations

A new quantum Monte Carlo (QMC) method for anharmonic vibrational zero-point energies and transition frequencies is developed, which combines the diagrammatic vibrational many-body perturbation theory based on the Dyson equation with Monte Carlo integration. The infinite sums of the diagrammatic and thus size-consistent first- and second-order anharmonic corrections to the energy and self-energy are expressed as sums of a few m- or 2m-dimensional integrals of wave functions and a potential energy surface (PES) (m is the vibrational degrees of freedom). Each of these integrals is computed as the integrand (including the value of the PES) divided by the value of a judiciously chosen weight function evaluated on demand at geometries distributed randomly but according to the weight function via the Metropolis algorithm. In this way, the method completely avoids cumbersome evaluation and storage of high-order force constants necessary in the original formulation of the vibrational perturbation theory; it furthermore allows even higher-order force constants essentially up to an infinite order to be taken into account in a scalable, memory-efficient algorithm. The diagrammatic contributions to the frequency-dependent self-energies that are stochastically evaluated at discrete frequencies can be reliably interpolated, allowing the self-consistent solutions to the Dyson equation to be obtained. This method, therefore, can compute directly and stochastically the transition frequencies of fundamentals and overtones as well as their relative intensities as pole strengths, without fixed-node errors that plague some QMC. It is shown that, for an identical PES, the new method reproduces the correct deterministic values of the energies and frequencies within a few cm{sup −1} and pole strengths within a few thousandths. With the values of a PES evaluated on the fly at random geometries, the new method captures a noticeably greater proportion of anharmonic effects.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2019

Renormalization group computation of likelihood functions for cosmological data sets

I show how a renormalization group (RG) method can be used to incrementally integrate the information in cosmological large-scale structure data sets (including CMB, galaxy redshift surveys, etc.). I show numerical tests for Gaussian fields, where the method allows arbitrarily close to exact computation of the likelihood function in order N time, even for problems with no symmetry, compared to N 3 for brute force linear algebra (where N is the number of data points - to be fair, methods already exist to solve the Gaussian problem in at worst N log N time, and this method will not necessarily be faster in practice). The method requires no sampling or other Monte Carlo (random) element. Nonlinearity/non-Gaussianity can be accounted for to the extent that terms generated by integrating out small scale modes can be projected onto a sufficient basis, e.g., at least in the sufficiently perturbative regime. The formulas to evaluate are straightforward and require no understanding of quantum field theory, but this paper may also serve as a pedagogical introduction to Wilsonian RG for astronomers.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2014

An AFM-based pit-measuring method for indirect measurements of cell-surface membrane vesicles

Highlights: • Air drying induced the transformation of cell-surface membrane vesicles into pits. • An AFM-based pit-measuring method was developed to measure cell-surface vesicles. • Our method detected at least two populations of cell-surface membrane vesicles. - Abstract: Circulating membrane vesicles, which are shed from many cell types, have multiple functions and have been correlated with many diseases. Although circulating membrane vesicles have been extensively characterized, the status of cell-surface membrane vesicles prior to their release is less understood due to the lack of effective measurement methods. Recently, as a powerful, micro- or nano-scale imaging tool, atomic force microscopy (AFM) has been applied in measuring circulating membrane vesicles. However, it seems very difficult for AFM to directly image/identify and measure cell-bound membrane vesicles due to the similarity of surface morphology between membrane vesicles and cell surfaces. Therefore, until now no AFM studies on cell-surface membrane vesicles have been reported. In this study, we found that air drying can induce the transformation of most cell-surface membrane vesicles into pits that are more readily detectable by AFM. Based on this, we developed an AFM-based pit-measuring method and, for the first time, used AFM to indirectly measure cell-surface membrane vesicles on cultured endothelial cells. Using this approach, we observed and quantitatively measured at least two populations of cell-surface membrane vesicles, a nanoscale population (<500 nm in diameter peaking at ∼250 nm) and a microscale population (from 500 nm to ∼2 μm peaking at ∼0.8 μm), whereas confocal microscopy only detected the microscale population. The AFM-based pit-measuring method is potentially useful for studying cell-surface membrane vesicles and for investigating the mechanisms of membrane vesicle formation/release.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Atmospheric River Detection Under Changing Seasonality and Mean-State Climate: ARTMIP Tier 2 Paleoclimate Experiments

Atmospheric rivers (ARs) are filamentary structures within the atmosphere that account for a substantial portion of poleward moisture transport and play an important role in Earth's hydroclimate. However, there is no one quantitative definition for what constitutes an atmospheric river, leading to uncertainty in quantifying how these systems respond to global change. This study seeks to better understand how different AR detection tools (ARDTs) respond to changes in climate states utilizing single-forcing climate model experiments under the aegis of the Atmospheric River Tracking Method Intercomparison Project (ARTMIP). We compare a simulation with an early Holocene orbital configuration and another with CO2 levels of the Last Glacial Maximum to a preindustrial control simulation to test how the ARDTs respond to changes in seasonality and mean climate state, respectively. We find good agreement among the algorithms in the AR response to the changing orbital configuration, with a poleward shift in AR frequency that tracks seasonal poleward shifts in atmospheric water vapor and zonal winds. In the low CO2 simulation, the algorithms generally agree on the sign of AR changes, but there is substantial spread in their magnitude, indicating that mean-state changes lead to larger uncertainty. This disagreement likely arises primarily from differences between algorithms in their thresholds for water vapor and its transport used for identifying ARs. These findings warrant caution in ARDT selection for paleoclimate and climate change studies in which there is a change to the mean climate state, as ARDT selection contributes substantial uncertainty in such cases.

Atmospheric river, paleoclimate↗
DOE OSTI2015

Speeding up N-body simulations of modified gravity: Vainshtein screening models

We introduce and demonstrate the power of a method to speed up current iterative techniques for N-body modified gravity simulations. Our method is based on the observation that the accuracy of the final result is not compromised if the calculation of the fifth force becomes less accurate, but substantially faster, in high-density regions where it is relatively weak due to screening. We focus on the nDGP model which employs Vainshtein screening, and test our method by running AMR simulations in which the fifth force on the finer levels of the mesh (high density) is not obtained iteratively, but instead interpolated from coarser levels. The calculation of the standard gravity component of the force still employs the full AMR structure. We show that the impact this has on the matter power spectrum is below 1% for k < 5h/Mpc at 0z = , and even smaller at higher redshift. The impact on halo properties is also small (∼< 3% for abundance, profiles, mass; and ∼< 0.05% for positions and velocities). The method can boost the performance of modified gravity simulations by more than a factor of 10. This allows them to run on timescales similar to GR simulations and to push them to resolution levels that were previously hard to achieve.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Super-resolution and signal separation in contact Kelvin probe force microscopy of electrochemically active ferroelectric materials

In this work, imaging mechanisms in contact Kelvin probe force microscopy (cKPFM) are explored via information theory-based methods. Gaussian processes are used to achieve super-resolution in the cKPFM signal, effectively extrapolating across the spatial and parameter space. Tensor factorization is applied to reduce the multidimensional signal to the tensor convolution of the scalar functions that show a clear trending behavior with the imaging parameters. These methods establish a workflow for the analysis of the multidimensional datasets that can then be related to the relevant physical mechanisms. We also provide an interactive Google Colab notebook that goes through all the analyses discussed in the paper.

36 MATERIALS SCIENCE↗
DOE OSTI2015

The polarized Debye sheath effect on Kadomtsev-Petviashvili electrostatic structures in strongly coupled dusty plasma

We give a theoretical investigation on the dynamics of nonlinear electrostatic waves in a strongly coupled dusty plasma with strong electrostatic interaction between dust grains in the presence of the polarization force (i.e., the force due to the polarized Debye sheath). Adopting a reductive perturbation method, we derived a three-dimensional Kadomtsev-Petviashvili equation that describes the evolution of weakly nonlinear electrostatic localized waves. The energy integral equation is used to study the existence domains of the localized structures. The analysis provides the localized structure existence region, in terms of the effects of strong interaction between the dust particles and polarization force.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2018

Experimental demonstration of hydraulic jump control in liquid metal channel flow using Lorentz force

Here in this paper, hydraulic jump control using electromagnetic force in a liquid metal flow is presented. The control methods used give insight into the hydraulic jump behavior in the presence of magnetic fields and electrical currents. Flowing liquid metals is a proposed solution to heat flux challenges posed in fusion reactors, specifically the tokamak. Unfortunately, thin, fast-flowing liquid metal divertor concepts for fusion reactors are susceptible to hydraulic jumps that drastically reduce the liquid metal flow speed, leading to potential problems such as excessive evaporation, unsteady power removal, and possible plasma disruption. Highly electrically conductive flows within the magnetic fields do not exhibit traditional hydraulic jump behavior. There is very little research investigating the use of externally injected electrical currents and magnetic fields to control liquid metal hydraulic jumps. By using externally injected electrical currents and a magnetic field, a Lorentz force (also referred to as j × B force) may be generated to control the liquid metal jump behavior. In this work, a free-surface liquid metal—GaInSn eutectic or “galinstan”$-$flow through an electrically insulating rectangular duct was investigated. It was shown that applying a Lorentz force has a repeatable and predictable impact on the hydraulic jump, which can be used for liquid metal control within next-generation fusion reactors.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗