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At least 1,387 records · Page 77

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↗

Spatial density fluctuations and selection effects in galaxy redshift surveys

One of the main problems of observational cosmology is to determine the range in which a reliable measurement of galaxy correlations is possible. This corresponds to determining the shape of the correlation function, its possible evolution with redshift and the size and amplitude of large scale structures. Different selection effects, inevitably entering in any observation, introduce important constraints in the measurement of correlations. In the context of galaxy redshift surveys selection effects can be caused by observational techniques and strategies and by implicit assumptions used in the data analysis. Generally all these effects are taken into account by using pair-counting algorithms to measure two-point correlations. We review these methods stressing that they are based on the a-priori assumption that galaxy distribution is spatially homogeneous inside a given sample. We show that, when this assumption is not satisfied by the data, results of the correlation analysis are affected by finite size effects. In order to quantify these effects, we introduce a new method based on the computation of the gradient of galaxy counts along tiny cylinders. We show, by using artificial homogeneous and inhomogeneous point distributions, that this method identifies redshift dependent selection effects and disentangles them from the presence of large scale density fluctuations. We then apply this new method to several redshift catalogs and we find evidence that galaxy distribution, in those samples where selection effects are small enough, is characterized by power-law correlations with exponent γ=0.9 up to 20 Mpc/h followed by a change of slope that, in the range 20–100 Mpc/h, corresponds to a power-law exponent γ=0.25. Whether a crossover to spatial uniformity occurs at ∼ 100 Mpc/h or larger scales cannot be clarified by the present data.

79 ASTRONOMY AND ASTROPHYSICS↗

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↗

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↗

Neutron Number Probability Distributions in a Subcritical System Using the Forward Master Equation

The subject of this paper is the determination of the equilibrium probability distribution function (PDF) of the neutron population within a subcritical multiplying system in the presence of an intrinsic random source as a result of spontaneous fission (SF). Such systems are strongly stochastic and low order moments such as the mean and variance of the neutron number are not sufficient to characterize the true state of the neutron population. We base our work on the forward Master equation in a lumped model formulation for P{sub n} (t), n = 0, 1, 2,..., the probability of there existing η neutrons at time t and obtain solutions for the steady state distributions. The key parameters in this model, neutron lifetime and fission probability, are rigorously obtained by numerically solving the k-eigenvalue problem in a one-dimensional spherical system and using standard definitions of lumped parameters in terms of production and loss rates in finite systems. Previous work has examined single-chain PDFs (a single fission and the resulting progeny) for neutrons, uncoupled neutron-photon single-chain PDFs, both using a lumped backward Master equation formulation, as well as neutron PDFs in supercritical systems. In this paper, we analyze strictly subcritical systems, for which we compare analytically derived solutions with numerical computations for different multiplicity distribution models. For subcritical systems where the neutron population remains finite at steady state, we show that the forward Master equation can be very efficiently solved numerically to obtain the equilibrium distributions. Finally, this work is motivated by potential application to passive interrogation for detection of diverted nuclear materials as well to criticality safety. The equilibrium neutron number probability distribution in subcritical systems has been numerically investigated for several models of the induced and spontaneous fission multiplicity distribution. A well known approximate but closed form solution, namely the quadratic model, was shown to be unacceptably accurate for subcritical media. The matrix inversion and the recursion methods agree well and were benchmarked with the binary fission model, but the recursion formulation proves far more computationally efficient. A qualitative change in the shape of the neutron PDF is observed for increasing source strength, as expected, and a transition from a stochastic to a deterministic system is expected for a sufficiently strong source. We are currently extending this approach to obtain the equilibrium joint distribution of neutrons within the system and those that have leaked, to explicitly represent the neutron PDF as observed by an external detector. (authors)

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

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↗

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↗

Pressure distribution along the AGS vacuum chambers with new types of pump out conduits

The AGS HEBT and ring vacuum system is monitored by the discharge current of the magnet ion pumps, which is proportional to the pressure at the inlet port of these ion pumps. The discharge current is measured and suitably calibrated to indicate the ion pump pressure. In order to calculate the vacuum chamber pressure from the ion pump pressure, a detailed analysis is essential to compute their difference in different scenarios. Such analysis has been carried out numerically in the past for the system with the older type of pump out conduits, and similar analysis using FEM in ANSYS is presented in this paper with the newer type of pump out conduit.

43 PARTICLE ACCELERATORS↗

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↗

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↗

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↗

Different approaches to modeling the LANSCE H{sup −} ion source filament performance

An overview of different approaches to modeling of hot tungsten filament performance in the Los Alamos Neutron Science Center (LANSCE) H{sup −} surface converter ion source is presented. The most critical components in this negative ion source are two specially shaped wire filaments heated up to the working temperature range of 2600 K–2700 K during normal beam production. In order to prevent catastrophic filament failures (creation of hot spots, wire breaking, excessive filament deflection towards source body, etc.) and to improve understanding of the material erosion processes, we have simulated the filament performance using three different models: a semi-empirical model, a thermal finite-element analysis model, and an analytical model. Results of all three models were compared with data taken during LANSCE beam production. The models were used to support the recent successful transition from the beam pulse repetition rate of 60 Hz–120 Hz.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

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↗

Stabilization of numerical interchange in spectral-element magnetohydrodynamics

In this study, auxiliary numerical projections of the divergence of flow velocity and vorticity parallel to magnetic field are developed and tested for the purpose of suppressing unphysical interchange instability in magnetohydrodynamic simulations. The numerical instability arises with equal-order C 0 finite- and spectral-element expansions of the flow velocity, magnetic field, and pressure and is sensitive to behavior at the limit of resolution. The auxiliary projections are motivated by physical field-line bending, and coercive responses to the projections are added to the flow-velocity equation. Their incomplete expansions are limited to the highest-order orthogonal polynomial in at least one coordinate of the spectral elements. Cylindrical eigenmode computations show that the projections induce convergence from the stable side with first-order ideal-MHD equations during h-refinement and p-refinement. Hyperbolic and parabolic projections and responses are compared, together with different methods for avoiding magnetic divergence error. Lastly, the projections are also shown to be effective in linear and nonlinear time-dependent computations with the NIMROD code [C. R. Sovinec, et al., J. Comput. Phys. 195 (2004) 355-386], provided that the projections introduce numerical dissipation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

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↗

WE-DE-201-12: Thermal and Dosimetric Properties of a Ferrite-Based Thermo-Brachytherapy Seed

Purpose: The novel thermo-brachytherapy (TB) seed provides a simple means of adding hyperthermia to LDR prostate permanent implant brachytherapy. The high blood perfusion rate (BPR) within the prostate motivates the use of the ferrite and conductive outer layer design for the seed cores. We describe the results of computational analyses of the thermal properties of this ferrite-based TB seed in modelled patient-specific anatomy, as well as studies of the interseed and scatter (ISA) effect. Methods: The anatomies (including the thermophysical properties of the main tissue types) and seed distributions of 6 prostate patients who had been treated with LDR brachytherapy seeds were modelled in the finite element analysis software COMSOL, using ferrite-based TB and additional hyperthermia-only (HT-only) seeds. The resulting temperature distributions were compared to those computed for patient-specific seed distributions, but in uniform anatomy with a constant blood perfusion rate. The ISA effect was quantified in the Monte Carlo software package MCNP5. Results: Compared with temperature distributions calculated in modelled uniform tissue, temperature distributions in the patient-specific anatomy were higher and more heterogeneous. Moreover, the maximum temperature to the rectal wall was typically ∼1 °C greater for patient-specific anatomy than for uniform anatomy. The ISA effect of the TB and HT-only seeds caused a reduction in D90 similar to that found for previously-investigated NiCu-based seeds, but of a slightly smaller magnitude. Conclusion: The differences between temperature distributions computed for uniform and patient-specific anatomy for ferrite-based seeds are significant enough that heterogeneous anatomy should be considered. Both types of modelling indicate that ferrite-based seeds provide sufficiently high and uniform hyperthermia to the prostate, without excessively heating surrounding tissues. The ISA effect of these seeds is slightly less than that for the previously-presented NiCu-based seeds.

07 ISOTOPE AND RADIATION SOURCES↗

Rolling Process Modeling Report. Finite-Element Model Validation and Parametric Study on various Rolling Process parameters

Pacific Northwest National Laboratory (PNNL) has been investigating manufacturing processes for the uranium-10% molybdenum alloy plate-type fuel for high-performance research reactors in the United States. This work supports the U.S. Department of Energy National Nuclear Security Administration’s Office of Material Management and Minimization Reactor Conversion Program. This report documents modeling results of PNNL’s efforts to perform finite-element simulations to predict roll-separating forces for various rolling mill geometries for PNNL, Babcock & Wilcox Co., Y-12 National Security Complex, Los Alamos National Laboratory, and Idaho National Laboratory. The model developed and presented in a previous report has been subjected to further validation study using new sets of experimental data generated from a rolling mill at PNNL. Simulation results of both hot rolling and cold rolling of uranium-10% molybdenum coupons have been compared with experimental results. The model was used to predict roll-separating forces at different temperatures and reductions for five rolling mills within the National Nuclear Security Administration Fuel Fabrication Capability project. This report also presents initial results of a finite-element model microstructure-based approach to study the surface roughness at the interface between zirconium and uranium-10% molybdenum.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

An efficient optimization of well placement and control for a geothermal prospect under geological uncertainty

This work applies an efficient optimization technique based on a multivariate adaptive regression spline (MARS) technique to determine the optimal design and engineering of a potential geothermal production operation at a prospect near Superstition Mountain in Southern California, USA. The faster MARS-based statistical model is used as a surrogate for higher-fidelity physical models within the intensive optimization process. Its use allows for the exploration of the impacts of specific engineering design parameters in the context of geologic uncertainty as a means to both understand and maximize profitability of the production operation. The MARS model is initially developed from a training dataset generated by a finite set of computationally complex hydrothermal models applied to the prospect. Its application reveals that the optimal engineering design variables can differ considerably assuming different choices of hydrothermal flow properties, which, in turn, indicates the importance of reducing the uncertainty of key geologic properties. The major uncertainty sources in the natural-system are identified and ranked first by an efficient MARS-enabled total order sensitivity quantification, which is then used to assist evaluating the effect of geological uncertainties on optimized results. At the Southern California prospect, this parameter sensitivity analysis suggests that groundwater circulation through high permeable structures, rather than heat conduction through impermeable granite, is the primary heat transfer method during geothermal extraction. Reservoir histories simulated using optimal parameters with different constraints are analyzed and compared to investigate the longevity and maximum profit of the geothermal resources. The comparison shows that the longevity and profit are very likely to be overestimated by optimizations without appropriate constraints on natural conditions. In addition to geothermal energy production, this optimization approach can also be used to manage other geologic resource operations, such as hydrocarbon production or CO 2 sequestration, under uncertain reservoir conditions.

15 GEOTHERMAL ENERGY↗