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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Many-Body Quantum Catalysts for Transforming Between Phases of Matter

A catalyst is a substance that enables otherwise impossible transformations between states of a system, without being consumed in the process. In this work, we apply the notion of catalysts to many-body quantum physics. In particular, we construct catalysts that enable transformations between different symmetry-protected topological (SPT) phases of matter using symmetric finite-depth quantum circuits. We discover a wide variety of catalysts, including GHZ-like states that spontaneously break the symmetry, gapless states with critical correlations, topological orders with symmetry fractionalization, and spin-glass states. These catalysts are all united under a single framework that has close connections to the theory of quantum anomalies, and we use this connection to put strong constraints on possible pure- and mixed-state catalysts. We also show how the catalyst approach leads to new insights into the structure of certain phases of matter, and to new methods to efficiently prepare SPT phases with long-range interactions or projective measurements.

quantum many-body systems↗
DOE OSTI2020

Efficient and Flexible Sensitivity Matrix Computation for Adaptive Electrical Capacitance Volume Tomography

Electrical capacitance tomography is a widely used sensor modality for flow imaging in many industrial settings. Adaptive Electrical Capacitance Volume Tomography (AECVT) extends the capabilities of traditional ECT by enabling direct volumetric imaging and an improved resolution. Construction of the sensitivity matrix is a necessary step to obtain flow images. This step requires computation of the electric field inside the sensing domain, which is done via a typical field solver such as the finite element method. In this work, we present an efficient and flexible method to construct the sensitivity matrix for Adaptive Electrical Capacitance Volume Tomography (AECVT) based on individual electrode segment excitations and their judicious combination to form desired matrix elements. We illustrate how the proposed method yields the same sensitivity matrix as the traditional method but at a much lower computational cost. Once all segment contributions are obtained, we also indicate how the proposed method, unlike the traditional approach, can generate the sensitivity matrix on demand for an arbitrary combination of synthetic electrodes and obviating the need for any additional field computations. Finally, we present image reconstruction results for two different experimental scenarios where the mutual capacitance data and the corresponding sensitivity vectors are obtained through the proposed measurement combination scheme.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Accelerating FEM-Based Corrosion Predictions Using Machine Learning

Atmospheric corrosion of metallic parts is a widespread materials degradation phenomena that is challenging to predict given its dependence on many factors (e.g. environmental, physiochemical, and part geometry). For materials with long expected service lives, accurately predicting the degree to which corrosion will degrade part performance is especially difficult due to the stochastic nature of corrosion damage spread across years or decades of service. The Finite Element Method (FEM) is a computational technique capable of providing accurate estimates of corrosion rate by numerically solving complex differential Eqs. characterizing this phenomena. Nevertheless, given the iterative nature of FEM and the computational expense required to solve these complex equations, FEM is ill-equipped for an efficient exploration of the design space to identify factors that accelerate or deter corrosion, despite its accuracy. In this work, a machine learning based surrogate model capable of providing accurate predictions of corrosion with significant computational savings is introduced. Specifically, this work leverages AdaBoosted Decision trees to provide an accurate estimate of corrosion current per width given different values of temperature, water layer thickness, molarity of the solution, and the length of the cathode for a galvanic couple of aluminum and stainless steel.

36 MATERIALS SCIENCE↗
DOE OSTI2018

The Effect of Aging on the Delamination Fracture Energy of Glass Solar Reflectors

Thin metal and metal oxide films deposited on glass or polymer substrates have been widely applied to manufacture front surfaced solar reflectors such as those used in the concentrated solar power (CSP) systems due to the facts that they are highly transparent, resistant to ultraviolet (UV) light and abrasion, and chemically inert. However, the reliable operation over long periods of outdoor exposure of such solar reflectors depends on the adequate adhesion between each layer to prevent delamination and subsequent failure. We report results from measurements of the delamination fracture energy (DFE) of the weakest interface in both as-deposited and aged reflectors, where the reflector construction consists of a glass/copper/silver/oxide stack. In this study, DFE was measured using a width-tapered beam method and the test results showed that the weakest interface of this solar reflector is the copper-glass interface, with a delamination fracture energy of approximately 4.4 J/m 2 . In order to verify the test results, finite element (FE) simulations were run using the commercial software package ABAQUS 6.14 based on the cohesive zone model (CZM). In the simulations, the DFE derived from the delamination measurement was treated as an input and the delamination forces from the FE simulations were compared to the experimental results. The good agreement between the tested and simulated delamination force indicated that this width-tapered beam method is accurate even for very small DFE, making it appropriate to test the DFE of front surfaced glass solar reflectors. Additionally, in order to study the aging effect on the DFE, accelerated aging tests were conducted using samples with different protective coatings, one group of samples with alumina ( Al 2 O 3 ) protective coating and the other group with titania ( TiO 2 ) protective coating. The DFE after 50 and 100 hours of accelerated aging were measured. The test results showed that the copper-glass interface would still be the weakest interface for all samples after aging, and the DFE for samples with Al 2 O 3 protective coating was unchanged whereas the copper-glass interface was found to undergo statistically significant change after both 50 and 100 hours of aging for samples with TiO 2 protective coating. We found that DFE at the copper/glass interface decreased after 50 hours of aging then increased after 100 hours of aging. The origin of this non-monotonic response of TiO 2 coated reflectors under accelerated aging conditions is unknown.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Time Scale Effects on the Temperature Coefficient of Reactivity

For a nuclear reactor, the temperature coefficient of reactivity (TCR) is of significance for both power control and safety analysis, but it is not always a constant. For example, the TCR may be dependent upon temperature due to Doppler broadening, and may be also dependent upon time scale due to heat transfer and thermal expansion. A fast burst reactor is a favorable nuclear facility to simulate the time scale effects on the TCR. Fast burst reactors are generally unmoderated research reactors of enriched uranium metal or uranium alloys. The neutrons are fast and the Doppler broadening effects can be neglected, and the TCR is mainly contributed by fuel thermal expansion. Fast burst reactors can operate on both steady state power mode and burst power mode. In steady state power mode, the systems are assumed to be in thermal equilibrium. In burst mode, the full width at half maximum (FWHM) of the power is from tens of microseconds to a few milliseconds, and the heat transfer is generally neglected. If FWHM is short enough, thermal expansion will have a time delay due to inertial effect. This paper is aimed to study the exact time scale effects on the TCR due to thermal expansion. The TCR contributed by the Doppler broadening effects was neglected, because it is relatively small (The k{sub eff} as a function of temperature was also calculated using the Monte Carlo particle transport code JMCT by our group, and no definite difference due to the temperature change was obtained near room temperature), and there is no method to evaluate the time scale dependence of the Doppler broadening effects yet. In the time scale from 1 x 10{sup -6} s to 1 x 10{sup 5} s, the TCR of a Godiva-like spherical fast burst reactor was calculated with perturbation theory. A Godiva-like spherical fast burst reactor was studied, the calculation of the time scale effects on TCR involved thermal conduction, thermoelasticity and reactivity variation analysis. Both the thermal and the thermoelastic problems were solved using ANSYS software. ANSYS is software implementation of finite element simulations, which is widely used in engineering field. The reactivity variation due to thermal expansion was calculated with perturbation theory.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2018

Three-Dimensional Mathematical Model of Oxygen Transport Behavior in Electroslag Remelting Process

A transient three-dimensional model has been proposed to investigate the oxygen transport behavior in electroslag remelting process. The electromagnetism, heat transfer, multiphase flow, and species transport were calculated simultaneously by finite volume method. The volume of fluid approach was adopted to trace the metal–slag–air three-phase flow. Based on the necessary thermodynamics of oxygen transport behavior, a kinetic model was established to predict the mass source terms in species transport equation. The kinetic correction factor was proposed to account for the effect of the oxide scale formed on the electrode on the FeO content in slag. Finally, the effect of applied current on the oxygen transfer was studied. The predicted result agrees well with the measured data when the kinetic correction factor is set to be 0.5. The temperature distribution that affects the thermodynamics differs at the interfaces. The oxygen in air is absorbed into slag due to the oxidation at the slag/air interface. The Fe{sub 2}O{sub 3} in slag and the oxide scale contribute to the increase of FeO content in slag, and the latter one plays the leading role. The oxygen transfer from slag to metal mainly occurs during the formation of the droplet at the slag/metal droplet interface. With the current increasing from 1200 to 1800 A, the oxygen content increases from 76.4 to 89.8 ppm, and then slightly declines to 89.2 ppm when the current increases to 2100 A.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Efficient Distributed Optimization of Wind Farms Using Proximal Primal-Dual Algorithms: Preprint

This paper presents a distributed approach to perform real-time optimization of large wind farms. Wind turbines in a wind farm typically operate individually to maximize their own performance regardless of the impact of aerodynamic interactions on neighboring turbines. This paper optimizes the overall power produced by a wind farm by formulating and solving a nonconvex optimization problem where the yaw angles are optimized to allow some turbines to operate in misaligned conditions and shape the aerodynamic interactions in a favorable way. The solution of the nonconvex smooth problem is tackled using a proximal primal-dual gradient method, which provably identifies a first-order stationary solution in a global sublinear manner. By adding auxiliary optimization variables for every pair of turbines that are coupled aerodynamically and properly adding consensus constraints into the underlying problem, a distributed algorithm with turbine-to-turbine message passing is obtained; this allows for turbines to be optimized in parallel using local information rather than information from the whole wind farm. This algorithm is computationally light, as it involves closed-form updates. This approach is demonstrated on a large wind farm with 60 turbines. The results indicate that similar performance can be achieved as with finite-difference gradient-based optimization at a fraction of the computational time and thus approach real-time control/optimization.

17 WIND ENERGY↗
DOE OSTI2019

Efficient Distributed Optimization of Wind Farms Using Proximal Primal-Dual Algorithms

This paper presents a distributed approach to performing real-time optimization of large wind farms. Wind turbines in a wind farm typically operate individually to maximize their own performance regardless of the impact of aerodynamic interactions on neighboring turbines. This paper optimizes the overall power produced by a wind farm by formulating and solving a nonconvex optimization problem where the yaw angles are optimized to allow some turbines to operate in misaligned conditions and shape the aerodynamic interactions in a favorable way. The solution of the nonconvex smooth problem is tackled using a proximal primal-dual gradient method, which provably identifies a first-order stationary solution in a global sublinear manner. By adding auxiliary optimization variables for every pair of turbines that are coupled aerodynamically, and properly adding consensus constraints into the underlying problem, a distributed algorithm with turbine-to-turbine message passing is obtained; this allows for turbines to be optimized in parallel using local information rather than information from the whole wind farm. This algorithm is computationally light, as it involves closed-form updates. This approach is demonstrated on a large wind farm with 60 turbines. The results indicate that similar performance can be achieved as with finite-difference gradient-based optimization at a fraction of the computational time and thus approaching real-time control/optimization.

17 WIND ENERGY↗
DOE OSTI2019

The Influence of Segregation of Mn on the Recrystallization Behavior of C-Mn Steels

The influence of Mn segregation that occurs during casting on recrystallization kinetics has been explored for a C-Mn automotive steel. A homogenization heat treatment was used to remove Mn segregation, while maintaining a similar initial austenite grain size to the segregated condition, to provide base-line comparison data. Deformation trials were carried out in a Gleeble thermomechanical simulator to 0.3 strains at 900 °C, and significant differences in both recrystallization times and final grain sizes were seen between the two conditions. The segregated sample incurred a longer recrystallization time and a wider recrystallized grain size distribution than the homogenized sample. A finite element model was used to predict the local deformation strains based on variations in material properties caused by segregation; the model used data from XRF elemental mapping of Mn to define the local mechanical properties based on differences in solid solution strengthening. Local strain variations ranging from 0.19 to 0.49 were predicted in the segregated sample for an overall applied 0.3 strain (compared to 0.26 to 0.35 in the homogenized sample); using these strains to predict the recrystallized grain sizes gave a much better prediction for the grain size distribution.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Benchmarking NIMROD continuum kinetic formulations through the steady-state poloidal flow

In this work, continuum kinetic formulations are employed as a mechanism to include closure physics in an extended magnetohydrodynamics model. Two continuum kinetic approaches have been implemented in the plasma fluid code NIMROD [Sovinec et al., “Nonlinear magnetohydrodynamics with high-order finite elements,” J. Comput. Phys. 195, 355 (2004)] including a Chapman–Enskog-like (CEL) formulation and a more conventional df approach. Ion kinetic closure schemes are employed to describe the neoclassical flow properties in axisymmetric toroidal geometry. In particular, predictions for steady-state values of poloidal flow profiles in tokamak geometry are provided using both the df formulation and two different solution techniques for the CEL approach. These results are benchmarked against analytic theory predictions as well as results from the drift kinetic code DK4D. The continuum kinetic formulations employed here show agreement with both the analytic theory and DK4D results, and offer a novel velocity space representation involving higher-order finite elements in pitch angle.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Directing the far-from-equilibrium assembly of nanoparticles in confined liquid crystals by hydrodynamic fields

The assembly of nematic colloids relies on long-range elastic interactions that can be manipulated through external stimuli. Confinement and the presence of a hydrodynamic field alter the defect structures and the energetic interactions between the particles. Here, the assembly landscape of nanoparticles embedded in a nematic liquid crystal confined in a nanochannel under a pressure-driven flow is determined. The dynamics of the liquid crystal tensor alignment field is determined through a Poisson-Bracket framework, namely the Stark–Lubensky equations, coupled with the zero-Reynolds momentum equations and the liquid crystal Landau-de Gennes free energy functional. A second order semi-implicit time integration and a three-dimensional Galerkin finite element method are used to resolve flow and nematic fields under several conditions. In general, the zero Reynolds flow displaces the defects around the particles in the upstream direction and renders the surface anchoring ineffective when the flow strength dominates over the nematic elasticity. More importantly, the potential of mean force for particle assembly is non-monotonic independent of surface anchoring. Our results show that the confinement length scale determines the repulsion/attraction transition between colloids, while the flow strength modifies the static defect structure surrounding the particles and determines the magnitude of the energetic barrier for successful assembly. In the attractive regime, the particles move at different rates through the nematic until one particle eventually catches up with the other. This process occurs against or along the direction of flow depending on the flow strength. Ultimately, these results provide a template for engineering and controlling the transport and assembly of nanoparticles under far-from equilibrium conditions in anisotropic media.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Unconventional fermionic pairing states in a monochromatically tilted optical lattice

We study the one-dimensional attractive fermionic Hubbard model under the influence of periodic driving with the time-dependent density matrix renormalization group method. We show that the system can be driven into an unconventional pairing state characterized by a condensate made of Cooper pairs with a finite center-of-mass momentum similar to a Fulde-Ferrell state. We obtain results both in the laboratory and the rotating reference frames demonstrating that the momentum of the condensate can be finely tuned by changing the ratio between the amplitude and the frequency of the driving. In particular, by quenching this ratio to the value corresponding to suppression of the tunneling and the Coulomb interaction strength to zero, we are able to “freeze” the condensate. We finally study the effects of different initial conditions and compare our numerical results to those obtained from a time-independent Floquet theory in the large frequency regime. Lastly, our work offers the possibility of engineering and controlling unconventional pairing states in fermionic condensates.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Performance analysis and implementation details of the Energy Conserving Semi-Implicit Method code (ECsim)

We present in this work the implementation of the Energy Conserving Semi-Implicit Method in a parallel code called ECsim. This new code is a three-dimensional, fully electromagnetic particle in cell (PIC) code. It is written in C/C++ and uses MPI to allow massive parallelization. ECsim is unconditionally stable in time, eliminates the finite grid instability, and has the same cycle scheme as the explicit code with a computational cost comparable to other semi-implicit PIC codes. All these features make it a very valuable tool to address situations which have not been possible to analyze until now with other PIC codes. In this work, we show the details of the algorithm implementation and we study its performance in different systems. ECsim is compared with another semi-implicit PIC code with different time and spectral resolution, showing its ability to address situations where other codes fail.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Experimental Characterization and Numerical Modeling of the Interaction Between Carbon Fiber Composite Prepregs During a Preforming Process

We report carbon fiber reinforced composites have received growing attention because of their superior performance and high potential for lightweight systems. An economic method to manufacture the parts made of these composites is a sequence of forming followed by a compression molding. The first step in this sequence is called preforming that forms the prepreg, which is the fabric impregnated with the uncured resin, to the product geometry, while the molding process cures the resin. Slip between different prepreg layers is observed in the preforming step, and it is believed to have a non-negligible impact on the resulting geometry. This paper reports a method to characterize the interaction between different prepreg layers, which should be valuable for future predictive modeling and design optimization. An experimental device was built to evaluate the interactions with respect to various industrial production conditions. The experimental results were analyzed for an in-depth understanding about how temperature, relative sliding speed, and fiber orientation affect the tangential interaction between two prepreg layers. Moreover, a hydro-lubricant model was introduced to study the relative motion mechanism of this fabric-resin-fabric system, and the results agreed well with the experiment data. Lastly, the interaction factors obtained from this research will be implemented in a preforming process finite element simulation model.

36 MATERIALS SCIENCE↗
DOE OSTI2025

The phase diagram of quantum chromodynamics in one dimension on a quantum computer

The quantum chromodynamics (QCD) phase diagram, which reveals the state of strongly interacting matter at different temperatures and densities, is key to answering open questions in physics, ranging from the behaviour of particles in neutron stars to the conditions of the early universe. However, classical simulations of QCD face significant computational barriers, such as the sign problem at finite matter densities. Quantum computing offers a promising solution to overcome these challenges. Here, we take an important step toward exploring the QCD phase diagram with quantum devices by preparing thermal states in one-dimensional non-Abelian gauge theories. We experimentally simulate the thermal states of SU(2) and SU(3) gauge theories at finite densities on a trapped-ion quantum computer using a variational method. This is achieved by introducing two features: Firstly, we add motional ancillae to the existing qubit register to efficiently prepare thermal probability distributions. Secondly, we introduce charge-singlet measurements to enforce colour-neutrality constraints. This work pioneers the quantum simulation of QCD at finite density and temperature for two and three colours, laying the foundation to explore QCD phenomena on quantum platforms.

Quantum information↗
DOE OSTI2016

SPIDER beam dump as diagnostic of the particle beam

The beam power produced by the negative ion source for the production of ion of deuterium extracted from RF plasma is mainly absorbed by the beam dump component which has been designed also for measuring the temperatures on the dumping panels for beam diagnostics. A finite element code has been developed to characterize, by thermo-hydraulic analysis, the sensitivity of the beam dump to the different beam parameters. The results prove the capability of diagnosing the beam divergence and the horizontal misalignment, while the entity of the halo fraction appears hardly detectable without considering the other foreseen diagnostics like tomography and beam emission spectroscopy.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

Hidden Mn magnetic-moment disorder and its influence on the physical properties of medium-entropy NiCoMn solid solution alloys

In this work, the ab initio Korringa-Kohn-Rostoker method combined with the coherent potential approximation (CPA) was employed to investigate the electronic, magnetic, and transport properties of medium-entropy face-centered-cubic (fcc) NiCoMn solid solution alloys. By comparing the CPA electronic structure with that from supercell calculations, we uncovered an unconventional CPA ground state, which correctly distinguishes two equally populated Mn CPA components—with large spin moments but opposite orientations. Using the spin spiral calculations, we further demonstrated that this ground state is most energetically favorable in the presence of spin noncollinearity, and no significant longitudinal spin fluctuation is observed, justifying the applicability of the Heisenberg model. The finite-temperature magnetism was further studied using different approximations based on the Heisenberg model, and we found the Mn moments to be fully disordered at low temperature due to a small net effective Weiss field on Mn. In addition, the magnetic effect on the electron scattering at finite temperatures was evaluated and compared with other scattering mechanisms. Since the magnetization-induced electron scattering is almost saturated in the ground state, (full) spin disorder only yields a small addition to the resistivity, whereas the thermal displacements increase it modestly. Finally, we elucidate the role of hydrostatic pressure on the magnetic and transport properties. In conclusion, these findings reflect the importance of the magnetic signatures on the physical properties of alloys, and they provide a window into magnetism-controlled electronic structure and energy dissipation.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Investigation of assumptions and approximations in the virtual fields method for a viscoplastic material model

The Virtual Fields Method (VFM) is an inverse technique used for parameter estimation and calibration of constitutive models. Many assumptions and approximations—such as plane stress, incompressible plasticity, and spatial and temporal derivative calculations—are required to use VFM with full-field deformation data, for example, from Digital Image Correlation (DIC). Here, this work presents a comprehensive discussion of the effects of these assumptions and approximations on parameters identified by VFM for a viscoplastic material model for 304L stainless steel. We generated synthetic data from a Finite-Element Analysis (FEA) in order to have a reference solution with a known material model and known model parameters, and we investigated four cases in which successively more assumptions and approximations were included in the data. We found that VFM is tolerant to small deviations from the plane stress condition in a small region of the sample, and that the incompressible plasticity assumption can be used to estimate thickness changes with little error. A local polynomial fit to the displacement data was successfully employed to compute the spatial displacement gradients. The choice of temporal derivative approximation (i.e., backwards difference versus central difference) was found to have a significant influence on the computed rate of deformation and on the VFM results for the rate-dependent model used in this work. Finally, the noise introduced into the displacement data from a stereo-DIC simulator was found to have negligible influence on the VFM results. Evaluating the effects of assumptions and approximations using synthetic data is a critical first step for verifying and validating VFM for specific applications. Finally, the results of this work provide the foundation for confidently using VFM for experimental data.

304L stainless steel↗