A machine learning-based characterization framework for parametric representation of liquid sloshing
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97 MATHEMATICS AND COMPUTING↗
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Two-fluid and kinetic transport physics of Kelvin–Helmholtz instabilities in nonuniform low-beta plasmas
Hall-magnetohydrodynamic (Hall-MHD) theory, two-fluid simulations, and kinetic simulations are used in this work to investigate the cross-field transport properties of Kelvin–Helmholtz instabilities in nonuniform low-beta collisionless plasmas. Hall-MHD analysis shows how the linear properties of the instability are modified by density gradients and magnetization. High-order accurate two-fluid and kinetic simulations, with complete dynamics of finite-mass electrons and ions, are applied to a suite of parameter cases to systematically assess the effects of diamagnetic drift, magnetization, charge separation, and finite Larmor motion. Initialization of exact two-species kinetic equilibria facilitates the study of isolated physical effects and enables detailed cross-comparisons between two-fluid and kinetic simulations, including for cases where ion gyroradii are comparable to gradient scale lengths. For nonuniform plasmas with significant space charge, the results of two-fluid and kinetic simulations are found to disagree with Hall-MHD predictions. Kelvin–Helmholtz instability growth rates, per unit shear, are shown to be smaller when ion diamagnetic drift and $E \times B$ drift are parallel and larger when the two drifts are antiparallel. The effect is attributed to polarization drift in the shear layer, which leads to redistribution of charge, alters the electric field that drives plasma advection, and consequently modifies growth rates. Instability-induced mass transport for different parameters is characterized in terms of the flux across the shear layer and a simplified diffusion model. Distribution functions from kinetic simulations are shown to deviate substantially from Maxwellian reconstructions, indicating the importance of kinetic physics during the nonlinear phase of the instability.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Collaborative Research: Polymer Macrocycles: A novel topology to control dynamics of rubbery materials
Understanding the dynamics of polymers of different topologies is an important field of study and one of the most important unanswered questions in this field is "how do circular polymers move," particularly in the melt state. New information suggests that molecular topology, specifically circular rings, impacts the response of materials in nanometer- scale confinement. The work performed here tackles these subjects through a collaboration in which specialists in polymer synthesis, polymer rheology and scattering methods, and in the physics of nanoconfinement work together to investigate the thermophysical behavior of circular macromolecules. The project goals are to use a novel synthesis method of "green" oxidative polymerization to produce high purity macrocycles and to investigate their linear viscoelastic behavior in order to fully characterize the dynamics of circular macromolecules to sizes that correspond to linear molecule entanglement densities higher than previously obtainable with synthetic polymers. Chemical chain end characterization and critical edge fractionation coupled with direct visualization of the prepared polymers through the use of polymer amplification methods are proposed in order to quantify the numbers of circular and linear molecules in each sample. The study of the linear viscoelastic response of blends of linear and circular molecules is also to be undertaken in the project. Nonlinear viscoelastic measurements, including extensional viscosity, are to be made. Strong differences in behavior between linear chains and circular ones also provides an important opportunity for new technology to break the "magic triangle" for tires: it is believed that improving one of the three key attributes - traction, wear, rolling resistance - necessarily sacrifices at least one of the others. Rubber made from cyclic polymers has the potential to break out of this triangle by reducing the so-called Payne effect in reinforced rubbers because circular macromolecules are less sensitive to nanoconfinement than their linear counterparts. The work has as one objective to characterize the impact of nanoconfinement on the behavior of large circular macromolecules. In addition, the dynamics of carbon black filled circular macromolecules are to be studied to test the hypothesis that the resulting rubbery materials will exhibit a reduced Payne effect.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Investigation of flow regimes in arc plasma–gas interactions using a two-temperature arc in crossflow model
The perpendicular impingement of a gas stream on an electric arc, a configuration known as the arc in crossflow, is of primary relevance in the study of plasma-gas interactions, as well as in industrial applications such as circuit breakers and wire-arc spraying. The flow dynamics in the arc in crossflow are the result of coupled fluid-thermal-electromagnetic phenomena accompanied by large property gradients, which can produce significant deviations from Local Thermodynamic Equilibrium (LTE) among electrons and gas species. These characteristics can lead to the establishment of distinct flow regimes depending on the relative values of the controlling parameters of the system, such as inflow velocity, arc current, and inter-electrode spacing. A two-temperature non-LTE (NLTE) model is used to investigate the arc dynamics and the establishment of flow regimes in the arc in crossflow. The plasma flow model is implemented within a nonlinear Variational Multiscale (VMS) numerical discretization approach that is less dissipative, and hence better suited to capture unstable behavior, than traditional VMS methods commonly used in computational fluid dynamics simulations. The Reynolds and the Enthalpy dimensionless numbers, characterizing the relative flow strength and arc strength, respectively, are chosen as the controlling parameters of the system. Simulation results reveal the onset of dynamic behavior and the establishment of steady, periodic, quasi-periodic, and chaotic or potentially turbulent, regimes, as identified by distinct spatiotemporal fluctuations. The computational findings reveal the role of increasing the relative arc strength on enhancing flow stability by delaying the growth of fluctuating and unstable flow behavior.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Statistical relationships across epigenomes using large-scale hierarchical clustering
Recent advances in genomics and sequencing platforms have revolutionized our ability to create immense data sets, particularly for studying epigenetic regulation of gene expression. However, the avalanche of epigenomic data is difficult to parse for biological interpretation given nonlinear complex patterns and relationships. This attractive challenge in epigenomic data lends itself to machine learning for discerning infectivity and susceptibility. In this study, we explore over 3000 epigenomes of uninfected individuals and provide a framework to characterize the relationships among epigenetic modifiers, their modifiers, genetic loci, and specific immune cell types across all chromosomes using hierarchical clustering. Hierarchical clustering of epigenomic data revealed consistent epigenetic patterns across chromosomes, demonstrating that variation due to epigenetic modifiers is greater than variation between cell types. Gene Ontology and KEGG pathway analyses indicated significant enrichment of genes involved in chromatin remodeling, mRNA splicing, immune responses, and the regulation of microRNAs and snoRNAs. Epigenetic modifiers frequently formed biologically relevant clusters, including the cohesin complex, RNA Polymerase II transcription factors, and PRC2 complex members. These clustering behaviors remained consistent across all chromosomes, supported by entropy analysis and high Adjusted Rand Index scores, indicating robust cross-chromosomal similarity. Co-occurrence analysis further revealed specific sets of modifiers that consistently appeared together within clusters, reflecting shared biological functions and interactions. Validation using another dataset confirmed the reproducibility of these clustering patterns and modifier co-occurrence relationships, underscoring the reliability and generalizability of the methodology.
97 MATHEMATICS AND COMPUTING↗
CO 2 storage site characterization using ensemble-based approaches with deep generative models
Estimating spatially distributed properties such as permeability from available sparse measurements is a great challenge in efficient subsurface CO 2 storage operations. In this paper, a deep generative model that can accurately capture complex subsurface structure is tested with an ensemble-based inversion method for accurate and accelerated characterization of CO 2 storage sites. We chose Wasserstein Generative Adversarial Network with Gradient Penalty (WGAN-GP) for its realistic reservoir property representation and Ensemble Smoother with Multiple Data Assimilation (ES-MDA) for its robust data fitting and uncertainty quantification capability. WGAN-GP are trained to generate high-dimensional permeability fields from a low-dimensional latent space and ES-MDA then updates the latent variables by assimilating available measurements. Several subsurface site characterization examples including Gaussian, channelized, and fractured reservoirs are used to evaluate the accuracy and computational efficiency of the proposed method and the main features of the unknown permeability fields are characterized accurately with reliable uncertainty quantification. Furthermore, the estimation performance is compared with a widely-used variational, i.e., optimization-based, inversion approach, and the proposed approach outperforms the variational inversion method in several benchmark cases. We explain such superior performance by visualizing the objective function in the latent space: because of nonlinear and aggressive dimension reduction via generative modeling, the objective function surface becomes extremely complex while the ensemble approximation can smooth out the multi-modal surface during the minimization. This suggests that the ensemble-based approach works well over the variational approach when combined with deep generative models at the cost of forward model runs unless convergence-ensuring modifications are implemented in the variational inversion.
42 ENGINEERING↗
Linear and Nonlinear Solvers for Simulating Multiphase Flow within Large-Scale Engineered Subsurface Systems
Simulation of multiphase flow in the subsurface is well-known to be computationally challenging. While there have been many studies that have explored approaches to overcoming these challenges, they often utilize relatively simple case studies. In this paper, we focus on the unique numerical challenges posed by modeling large-scale engineered subsurface systems, characterized by discrete features embedded in a heterogeneous natural subsurface setting. The man-made features such as shafts, tunnels, and barriers often cause multiple challenges in modeling the domain for multiphase porous media flow. This flow scenario can have a wide range of applications such as nuclear waste repositories, enhanced recovery of a petroleum reservoir, geothermal engineering, and carbon sequestration. An example of these severe numerical challenges is the case of performance assessment (PA) for Waste Isolation Pilot Plant (WIPP), the only operating deep geological repository in the US, which simulates extreme material properties of bedded salt rock formation and extreme contrast due to open excavation next to the formation. The models have extremes not only of permeability and porosity but also of the constitutive models needed for multiphase flow; additionally, they have process models like salt creep closure reducing porosity over time, fracturing in clay and anhydrite interbeds of the bedded salt, gas generation from the waste materials, and unintentional human borehole intrusions in some scenarios. Numerical simulations require the solution of coupled systems of nonlinear PDEs; in our work, we use the open-source simulator PFLOTRAN which is based on Finite Volume discretization. The solution of the nonlinear equations requires use of the Newton-Raphson iteration at each time step, which entails the solution of the linearized Jacobian system at each iteration. The effects of all the processes (i.e., large number of unknowns, highly nonlinear constitutive relations, large contrasts in material properties in short distances) lead to an ill-conditioned Jacobian matrix that severely challenges traditional linear solver, i.e., stabilized biconjugate gradient with block Jacobi incomplete LU preconditioner (BCGS-ILU) leading to non-convergence for traditional Newton-Raphson nonlinear solver causing unacceptably long computation time for each model. This paper presents linear solvers such as constrained pressure residual (CPR) two-stage preconditioner with alternate-block-factorization (ABF) and quasi- implicit pressure and explicit saturation (QIMPES) decouplers and flexible generalized residual solver (FGMRES). The new general-purpose nonlinear solver, Newton trust-region dogleg Cauchy (NTRDC), is also introduced to resolve extreme nonlinearities in the models. We demonstrate the effectiveness of each method relative to the default BCGS-Newton solver. The two best cases had nearly 50 times speed-up and achieved completion of a simulation in 14 hours that never completed due to non-convergence with the default solver. We also investigate the strong scalability of each method and discuss some of the deficiencies found for Block Jacobi preconditioner using parallel domain decomposition, and node packing effects of modern processor architecture.
Preconditioner, Nonlinear, Porous media, Multiphas↗
Time Domain Thermoreflectance and Photodeflection Signatures of He Bubbles in Metals
The mechanical properties of the steel and weldments for different components are affected by the formation of helium bubbles as a result of tritium decay. Therefore, periodic analyses of metals exposed to tritium gas are conducted to determine structural defects and temporal damage from tritium gas decay and He precipitation. Transmission electron microscopy (TEM) and autoradiography are the current analytical methods for the evaluation of metal damage. These methods are functional after several years of damage to the crystal lattice where 3He bubble formation damage can be seen with TEM. New analytical methods that can assess the damage to the crystal lattice early during the exposure to tritium are highly sought to ascertain the effects of material processing and tritium interactions. Further, simple sample preparation, compared to TEM, at a significantly reduced cost is highly desirable. A pump-probe laser technique using a femtosecond laser has been demonstrated to measure the thermal diffusivity of different materials. The time domain thermoreflectance (TDTR) laser setup can provide thermal diffusivity and phonon lifetime, which can be correlated with lattice damage. This advanced nonlinear optical technique will enable measurements of nanostructure damage in the metal before and after tritium exposure within a year. This report discusses current efforts in the design and development of the technique and the application to material characterization.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Effective kinetics driven by dynamic concentration gradients under coupled transport and reaction
Biogeochemical reaction kinetics are generally established from batch reactors where concentrations are uniform. In natural systems, many biogeochemical processes are characterized by spatially and temporally variable concentration gradients that often occur at scales which are not resolved by field measurements or biogeochemical and reactive transport models. Yet, it is not clear how these sub-scale chemical gradients affect reaction kinetics compared to batch kinetics. Here we investigate this question by studying the paradigmatic case of localized pulses of solute reacting with a solid or a dissolved species in excess. Additionally, we consider non-linear biogeochemical reactions, representative of mineral dissolution, adsorption and redox reactions, which we quantify using simplified power-law kinetics. The combined effect of diffusion and reaction leads to effective kinetics that differ quantitatively and qualitatively from the batch kinetics. Depending on the nonlinearity (reaction order) of the local kinetics, these effects lead to either enhancement or decrease of the overall reaction rate, and result in a rich variety of reaction dynamics. We derive analytical results for the effective kinetics, which are validated by comparison to direct numerical simulations for a broad range of Damköhler numbers and reaction order. Our findings provide new insights into the interpretation of imperfectly mixed lab experiments, the effective kinetics of field systems characterized by intermittent reactant release and the integration of sub-scale concentration gradients in reactive transport models.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Visualization and quantum control of light-accelerated condensates by terahertz multi-dimensional coherent spectroscopy
Abstract Characterizing and controlling high-order correlation of quantum systems is key for developing quantum devices and switching technologies. Although conventional static and ultrafast spectroscopy gives access to collective excitations characterizing quantum states, more exotic correlations cannot be easily separated from other contributions. Here we develop density matrix simulations to show that seventh-order-wave-mixing peaks with distinct temperature and field dependences in two-dimensional terahertz nonlinear spectra reveal light-induced correlations in non-equilibrium superconducting states. Above critical terahertz driving, these emerging peaks split from conventional peaks along the second axis introduced by pump-probe relative phase in two-dimensional frequency space. They are photo-generated by correlations between two-photon fluctuations and interacting quasi-particle and quasi-particle/Higgs superconductor excitations. By photo-inducing persistent symmetry breaking via light-wave propagation, we also demonstrate seventh-order-wave-mixing sensing of Higgs collective modes. Our theory suggests to use multi-dimensional spectroscopy for quantum sensing of light-driven superconductivity and paves a path for quantum operations by few-cycle-THz-periodic photocurrent modulation.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Brewster angle-cavity ringdown spectroscopy for low temperature plasma measurements in multiphases
Here we report on the development of a Brewster angle-cavity ringdown spectroscopy (BA-CRDS) system for low temperature plasma diagnostics. The system can measure gas species in solutions, with a detection limit (minimum detectable absorbance) of 9.1 × 10 -5 , which is equivalent to a detection limit of 0.04 parts per billion for measuring OH radicals in water at 308 nm. With higher reflectivity ringdown mirrors and improved design of a Brewster angle cell, the detection limit can potentially be up to 10 -6 or lower. In this exploratory study, the absorption cross sections of HgBr 2 and H 2 O 2 in the aqueous phase at 256 nm are measured to be (1.8 ± 0.1) × 10 -18 cm 2 and (5.2 ± 0.5) × 10 -20 cm 2 , respectively. Furthermore, temporal profiles of absorbance from distilled water, HgBr 2 , and H 2 O 2 solutions when interacting with a helium atmospheric plasma jet are individually characterized at different plasma powers, gas flow rates, and/or solute concentrations. The observed linear temporal profiles of absorbance from the plasma-interacted water suggest formation of H 2 O 2 from plasma-generated OH radicals, while the nonlinear temporal profiles from the plasma-treated HgBr 2 solutions reveal possible removal of HgBr 2 by OH radicals. Our results demonstrate that the new BA-CRDS system is a powerful tool for quantification of reactive plasma species in multiphases or other complex settings.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Evaluating the effect of meso/submesoscale current–wave interactions on wave energy resource characterization at northeast U.S. coast
Wave energy is a promising renewable resource, but accurate assessment is difficult in regions with strong currents due to wave–current interactions (WCI). Here, this study develops a two-way coupled WCI model within the Coupled Ocean Atmosphere Wave Sediment Transport (COAWST) framework at 2 km resolution to improve wave energy characterization along the northeastern U.S. coast, including the Mid-Atlantic Bight and Gulf of Maine. The model integrates WaveWatchIII (WWIII) and the Regional Ocean Modeling System (ROMS) to enhance wave hindcasting by accounting for Doppler-shift, refraction, and nonlinear energy exchanges. Validation against buoy and satellite observations confirms model accuracy. Analysis shows that Doppler-shifting can alter wave power density by over 20%, while strong current gradients and shear distort wave crests via focusing/defocusing and stretching/squeezing, modifying wave direction and frequency. These processes together can induce wave power fluctuations of up to 40% on synoptic scales. Applying a 2.5 MW Ocean Energy Converter power matrix shows that WCI may change harvested energy by up to 100% in shallow-waters and 60% in deep-waters. These results underscore the importance of incorporating nonlinear WCI for reliable wave climate predictions and resource assessments in energetic coastal regions.
doppler-shift↗
Zr 3 Mn 3 Sn 4 Ga: A new hetero-kagome bilayer antiferromagnet
Here, we report the magnetic and electrical transport properties of single-crystalline Zr 3 Mn 3 Sn 4 Ga, featuring two distinct kagome lattices: a non-magnetic breathing Zr 3 Sn 4 lattice and a magnetic intact Mn 3 Ga lattice. The material undergoes an antiferromagnetic phase transition at T N = 87 K, with neutron diffraction confirming commensurate ordering characterized by k = (1/3,1/3,0). Transport measurements show metallic behavior, a resistivity anomaly near T N , and 12% magnetoresistance at 2 K under 9 T. Deviations from the conventional second-order power law, along with negative magnetoresistance and nonlinear Hall slope variations near T N , suggest strong magneto-electronic coupling. Resonant photoemission spectroscopy identifies Zr 4d and Mn 3d orbitals as dominant contributors to the valence band, linking the material’s unique electronic properties to its kagome layers. Zr 3 Mn 3 Sn 4 Ga offers a valuable platform to study interactions between magnetism and topological electronic bands in hetero-kagome systems using the co- existence of magnetic and non-magnetic kagome layers and its tunable electronic structure.
Crystal structure↗
Seismic Elastic Double-Beam Characterization of Faults and Fractures for CO₂ Storage Site Selection
Site characterization for underground injection and storage of gigatonne-scale CO₂ requires reliable and cost-effective methods to detect and characterize faults and fractures and to assess their stress state and fault activation potential. This is critical, as wastewater injection and disposal have been shown to activate faults and induce earthquakes, and CO₂ leakage remains a key concern for long-term storage. In this project, we developed seismic methods to detect and characterize large-scale sedimentary and crystalline basement faults and associated small-scale fractures below conventional seismic imaging resolution using multicomponent (9C) surface seismic data. Machine learning was used to automatically interpret large-scale faults, providing key information for estimating the maximum magnitude of potential induced earthquakes. High-fidelity imaging was achieved by exploiting redundancy across multiple elastic wave modes, where independent images from different modes and frequencies cross-validate each other. We also used our nonlinear signal comparison (NLSC) method for ground roll removal, improving data quality in complex near-surface conditions. The methods were validated using field data acquired in central Montana. Results show that basement faults extend into the sedimentary section and that small-scale fractures are widespread above the basement. The inferred stress orientation is consistent with regional stress data, and the estimated maximum induced earthquake magnitude is small (Mw ~2.3). The developed workflow provides a practical approach for fault and fracture characterization and for assessing induced seismicity and leakage risk. It is directly applicable to CO₂ storage site selection and to other subsurface systems.
02 PETROLEUM↗
Measurement of the angular dependence of the spontaneous Raman scattering in anisotropic crystalline materials using spherical samples: Potassium dihydrogen phosphate as a case example
A specialized experimental configuration was created to allow for more-accurate characterization of the spontaneous Raman scattering properties in anisotropic materials. This need stems from the challenges, arising from the complexity of light propagation, in obtaining accurate measurements of the angular dependence of the Raman scattering cross section in birefringent materials. The nonlinear optical material KH 2 PO 4 (KDP) is used as a model medium. Our report is motivated by the need to improve our understanding and management of transverse stimulated Raman scattering in KDP crystals and its deuterated analog, DKDP, typically used for frequency conversion and polarization control in large-aperture laser systems. Key to this experimental platform is the use of high-quality spherical samples that enable one to measure the Raman scattering cross section in a wide range of geometries using only a single sample. The effect of polarization rotation of both the pump light and the collected Raman signal must be carefully considered in data analysis and can give rise to artifacts, which can, in part, be mitigated by reducing the input and collection cone angles.
47 OTHER INSTRUMENTATION↗
Broadband Ultrafast Dynamics of Refractory Metals: TiN and ZrN
Transition metal nitrides have recently gained attention in the fields of plasmonics, plasmon-enhanced photocatalysis, photothermal applications, and nonlinear optics because of their suitable optical properties, refractory nature, and large laser damage thresholds. Here we report comparative studies of the transient response of films of titanium nitride (TiN), zirconium nitride (ZrN), and gold (Au) under femtosecond excitation. Broadband transient optical characterization helps to adjudicate earlier, somewhat inconsistent reports regarding hot electron lifetimes based upon single wavelength measurements. These pump–probe experiments show sub-picosecond transient dynamics only within the epsilon-near-zero window of the refractory metals. The dynamics are dominated by photoinduced interband transitions resulting from ultrafast electron energy redistribution. The enhanced reflection modulation in the epsilon-near-zero window makes it possible to observe the ultrafast optical response of these films at low pump fluences. These results indicate that electron–phonon coupling in TiN and ZrN is 25–100 times greater than in Au. Strong electron–phonon coupling drives the sub-picosecond optical response and facilitates greater lattice heating compared to Au, making TiN and ZrN promising for photothermal applications. The spectral response and dynamics of TiN and ZrN are only weakly sensitive to pump fluence and pump excitation energy. However, the magnitude of the response is much greater at higher pump photon energies and higher fluences, reaching peak observed values of 15% in TiN and 50% in ZrN in the epsilon-near-zero window.
36 MATERIALS SCIENCE↗
Characterization of admissible quasisymmetries
We solve ‘half’ the problem of finding three-dimensional quasisymmetric magnetic fields that do not necessarily satisfy magnetohydrostatic force balance. This involves determining which hidden symmetries are admissible as quasisymmetries, and then showing explicitly how to construct quasisymmetric magnetic fields given an admissible symmetry. The admissibility conditions take the form of a system of overdetermined nonlinear partial differential equations involving second derivatives of the symmetry's infinitesimal generator.
Burby, J. W. (ORCID:0000000317727647)↗
Multi-objective optimization of peel and shear strengths in ultrasonic metal welding using machine learning-based response surface methodology
Ultrasonic metal welding (UMW) is a solid-state joining technique with varied industrial applications. Despite of its numerous advantages, UMW has a relative narrow operating window and is sensitive to variations in process conditions. As such, it is imperative to quantitatively characterize the influence of welding parameters on the resulting joint quality. The quantification model can be subsequently used to optimize the parameters. Conventional response surface methodology (RSM) usually employs linear or polynomial models, which may not be able to capture the intricate, nonlinear input-output relationships in UMW. Furthermore, some UMW applications call for simultaneous optimization of multiple quality indices such as peel strength, shear strength, electrical conductivity, and thermal conductivity. To address these challenges, this paper develops a machine learning (ML)-based RSM to model the input-output relationships in UMW and jointly optimize two quality indices, namely, peel and shear strengths. The performance of various ML methods including spline regression, Gaussian process regression (GPR), support vector regression (SVR), and conventional polynomial regression models with different orders is compared. A case study using experimental data shows that GPR with radial basis function (RBF) kernel and SVR with RBF kernel achieve the best prediction accuracy. The obtained response surface models are then used to optimize a compound joint strength indicator that is defined as the average of normalized shear and peel strengths. In addition, the case study reveals different patterns in the response surfaces of shear and peel strengths, which has not been systematically studied in the literature. While developed for the UMW application, the method can be extended to other manufacturing processes.
42 ENGINEERING↗