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In this paper, we propose a novel method to design serial concatenation of an outer convolutional code with an inner trellis code with multi-level amplitude/phase modulations and a suitable bit-by-bit iterative decoding structure.
One drawback to using constraint-propagation in planning and scheduling systems is that when a problem has an unsatisfiable set of constraints such algorithms typically only show that no solution exists. While, technically correct, in practical situations, it is desirable in these cases to produce a satisficing solution that satisfies the most important constraints (typically defined in terms of maximizing a utility function). This paper describes an iterative constraint relaxation approach in which the scheduler uses heuristics to progressively relax problem constraints until the problem becomes satisfiable. We present empirical results of applying these techniques to the problem of scheduling spacecraft communications for JPL/NASA antenna resources.
Soft-input soft-output building blocks (modules) are presented to construct and iteratively decode in a distributed fashion code networks, a new concept that includes, and generalizes, various forms of concatenated coding schemes.
This paper addresses the carrier-phase estimation problem under low SNR conditions as are typical of turbo- and LDPC-coded applications. In previous publications by the first author, closed-loop carrier synchronization schemes for error-correction coded BPSK and QPSK modulation were proposed that were based on feeding back hard data decisions at the input of the loop, the purpose being to remove the modulation prior to attempting to track the carrier phase as opposed to the more conventional decision-feedback schemes that incorporate such feedback inside the loop. In this paper, we consider an alternative approach wherein the extrinsic soft information from the iterative decoder of turbo or LDPC codes is instead used as the feedback.
We propose a design approach for serial concatenation of an outer convolutional code and an inner trellis code with multilevel amplitude/phase modulations using a bit-by-bit iterative decoding scheme.
Performance degradation due to filament fracture of Nb3 Sn cable-in-conduit conductors (CICCs) is a critical issue in large-scale magnet designs such as ITER which is currently being constructed in the South of France. The critical current observed in most SULTAN TF CICC samples is significantly lower than expected and the voltage-current characteristic is seen to have a much broader transition from a single strand to the CICC. Moreover, most conductors exhibit the irreversible degradation due to filament fracture and strain relaxation under electromagnetic cyclic loading. With recent success in monitoring thermal strain distribution and its evolution under the electromagnetic cyclic loading from in situ measurement of critical temperature, we apply FEMCAM which includes strand filament breakage and local current sharing effects to SULTAN tested CICCs to study Nb3 Sn strain sensitivity and irreversible performance degradation. FEMCAM combines the thermal bending effect during cool down and the EM bending effect due to locally accumulating Lorentz force during magnet operation. It also includes strand filament fracture and related local current sharing for the calculation of cable n value. In this paper, we model continuous performance degradation under EM cyclic loading based on strain relaxation and the transition broadening upon cyclic loading to the extreme cases seen in SULTAN test data to better quantify conductor performance degradation.
ITER is incorporating two types of In Vessel Coils (IVCs): ELM Coils to mitigate Edge Localized Modes and VS Coils to provide Vertical Stabilization of the plasma. Strong coupling with the plasma is required so that the ELM and VS Coils can meet their performance requirements. Accordingly, the IVCs are in close proximity to the plasma, mounted just behind the Blanket Shield Modules. This location results in a radiation and temperature environment that is severe necessitating new solutions for material selection as well as challenging analysis and design solutions. Fitting the coil systems in between the blanket shield modules and the vacuum vessel leads to difficult integration with diagnostic cabling and cooling water manifolds.
Gyro kinetic simulations of turbulence capture some of the features observed in transport, fluctuations, and correlations measured in tokamak plasmas. These codes calculations are CPU intensive, and are not practical for incorporation in present time-dependant transport codes, so reduced models based on these gyro kinetic codes are being used. An example is the TGLF model [1] which is a quasilinear gyrofluid model calibrated to nonlinear results from the GYRO code [2]. Recently TGLF has been incorporated into TRANSP. Analysis of experimental data using TRANSP with such models provides fundamental understanding of turbulent transport. Predictions of ITER performance with various plasma scenarios using such models are useful for optimizing design and for exposing issues that can be addressed in present experiments and theory. For instance, which combinations of heating, torquing, and current drive are optimal. Another application is for nuclear licensing (e.g. system integrity, neutron rates). Others are generating inputs for design of diagnostic systems and for theoretical studies. An example of the later is Alfv´en Eigenmode and AE-induced loss of fast ions. The beam ion distribution can either enhance or reduce the alpha pressure drive of the AE instability. The AE instability can cause dangerous amounts of fast ion losses, as was seen in TFTR.
A low-synchronization MGS-GMRES Krylov solver employing a truncated Neumann series for the inverse compact WY MGS correction matrix T is presented. A corollary to the backward stability result of Paige et al. [1] establishes that T = I - Lk is sufficient for convergence of GMRES when kLkp F = O("p)_p F (B), where the strictly lower triangular matrix L is defined by the inner products of Krylov vectors V T 1:k-2 vk-1. The preconditioner is the classical Ruge-Stuben AMG algorithm with compatible relaxation and inner-outer Gauss-Seidel smoother. This smoother may also be expressed as a truncated Neumann series. Drop tolerances are applied to the lower triangular matrices arising in the smoother in order to reduce the number of non-zeros and accelerate the time to solution. The number of small matrix elements are found to increase from fine to coarse levels and thus the effciency gains are greater for large problems with many levels in the V -cycle. The solver is applied to the pressure continuity equation for the incompressible Navier-Stokes equations. Unlike the inner-outer iteration, the solver convergence rate with the standard Gauss-Seidel smoother deteriorates with dropping. The solver compute time is reduced by up to 50% without a change in the convergence rate.
In this paper, the overlapping local/global (OLG) iteration method based on Monte Carlo/p-CMFD calculations is refined in two aspects. One is the consistent use of estimators to generate homogenized scattering cross sections. Another is that the incident or exiting angular interval is divided into multi-angular bins to modulate albedo boundary conditions for local problems. Numerical tests show that, compared to the one angle bin case in a previous study, the four angle bin case shows significantly improved results. (authors)
As radiation transport models for ITER become increasingly complex, the use of traditional constructive solid geometry (CSG) modelling approaches such as MCWNP presents significant disadvantages during model creation and integration. Studies were performed to assess the capabilities of alternative mesh-based neutronics workflows offered by the MCNP, DAG-MCNP and Serpent-2 codes.
Deep neural network (DNN) surrogates of expensive physics simulations are enabling a rapid change in the way that common experimental design and analysis tasks are approached. Surrogate models allow simulations to be performed in parallel and separately from downstream tasks, thereby enabling analyses that would be impossible with the simulation in-the-loop; surrogates based on DNNs can effectively emulate diverse non-scalar data of the types collected in fusion and laboratory-astrophysics experiments. The challenge is in training the surrogate model, for which large ensembles of physics simulations must be run, preferably without wasting computational effort on uninteresting simulations. Here, in this paper, we present an iterative sampling scheme that can preferentially propose simulations in interesting regions of parameter space without neglecting unexplored regions, allowing high-quality and wide-ranging surrogate models to be trained using 2–3 times fewer simulations compare to space-filling designs. Our approach uses an explicit importance function defined on the simulation output space, balanced against a measure of simulation density which serves as a proxy for surrogate accuracy. It is easy to implement and can be tuned to find interesting simulations early in the study, allowing surrogates to be trained quickly and refined as new simulations become available; this represents an important step towards the routine generation of deep surrogate models quickly enough to be truly relevant to experimental work.
Abstract Efficient handling of high heat flux on the plasma‐facing components, particularly the divertor targets, poses a significant challenge for the Chinese Fusion Engineering Testing Reactor (CFETR) with fusion power of Gigawatt. This work investigates the divertor plasma detachment of CFETR with a standard ITER‐like divertor geometry by neon (Ne) or argon (Ar) impurity seeding using UEDGE code. The cross‐field drifts terms are switched off, and fluid neutral models and a “fixed‐fraction” impurity model are applied to enable efficient simulations for the study of CFETR detachment. In order to reduce the heat load on the divertor targets below the acceptable level (<10 MW/m 2 ), the impurity fraction ( f ), pumping speed ( S ), and upstream density are varied to identify the suitable operations window during Ne seeding. The effects of Ne and Ar impurities on the plasma detachment are compared. It is found that with the power across the core‐edge interface P SOL = 200 MW and separatrix density of 2.8 10 19 , Ne impurity fraction ≥1.7%, and Ar impurity fraction ≥0.24% can achieve the partial detachment. Achieving similar total radiation power (˜148 MW), the Ne fraction is 2.3% and the Ar fraction is 0.24%. Moreover, the simulation results indicate that Ar exhibits better power radiation efficiency and core compatibility compared with Ne.
New algorithms for iterative diagonalization procedures that solve for a small set of eigen‐states of a large matrix are described. The performance of the algorithms is illustrated by calculations of low and high‐lying ionized and electronically excited states using equation‐of‐motion coupled‐cluster methods with single and double substitutions (EOM‐IP‐CCSD and EOM‐EE‐CCSD). We present two algorithms suitable for calculating excited states that are close to a specified energy shift (interior eigenvalues). One solver is based on the Davidson algorithm, a diagonalization procedure commonly used in quantum‐chemical calculations. The second is a recently developed solver, called the “Generalized Preconditioned Locally Harmonic Residual (GPLHR) method.” We also present a modification of the Davidson procedure that allows one to solve for a specific transition. The details of the algorithms, their computational scaling, and memory requirements are described. The new algorithms are implemented within the EOM‐CC suite of methods in the Q‐Chem electronic structure program. © 2014 Wiley Periodicals, Inc.
In this paper we develop further and refine the method of differential equations for computing Feynman integrals. In particular, we show that an additional iterative structure emerges for finite loop integrals. As a concrete non-trivial example we study planar master integrals of light-by-light scattering to three loops, and derive analytic results for all values of the Mandelstam variables s and t and the mass m. We start with a recent proposal for defining a basis of loop integrals having uniform transcendental weight properties and use this approach to compute all planar two-loop master integrals in dimensional regularization. We then show how this approach can be further simplified when computing finite loop integrals. This allows us to discuss precisely the subset of integrals that are relevant to the problem. We find that this leads to a block triangular structure of the differential equations, where the blocks correspond to integrals of different weight. We explain how this block triangular form is found in an algorithmic way. Another advantage of working in four dimensions is that integrals of different loop orders are interconnected and can be seamlessly discussed within the same formalism. We use this method to compute all finite master integrals needed up to three loops. Finally, we remark that all integrals have simple Mandelstam representations.
An iterative method is developed to obtain vibrational spectra of laser organic dyes from their secondary radiation spectra in multiple-scattering media, which manifests as a result of coupled process of chaotic generation (CG) and stimulated Raman scattering (SRS). The developed method increases significantly the capability to detect weak Raman lines by using batch processing of a set of experimental SRS-CG spectra, which makes it possible to optimize the deconvolution of these spectra and to average vibrational spectra obtained from the set of experimental SRS-CG spectra. The method is tested on spectra of the SRS-CG laser dye pyrromethene 597 in a vesicular film. The obtained results agree well with Raman spectra calculated by the Hartree–Fock method.
In this work, a pulsed magnetic field of 10 T with a duration of 1.5 ms is produced by a resistor-inductor-capacitor (RLC) discharge system. A carbon nanotube-polypyrrole (CNT-PPy) composite (9 wt%) is prepared. The influence of the pulsed magnetic field iteration on the alignment of CNTs embedded in polymer matrix is observed (up to 60 pulses). The microstructure of the magnetically aligned composites is probed by scanning probe microscopy technique. The behavior of a CNT in a magnetic field is theoretically studied, and the equivalent magnetic susceptibility for an anisotropic CNT is calculated. The theory of CNT alignment in a magnetic field is discussed. We found that the perpendicular diamagnetism of a CNT results in its alignment in a magnetic field. We showed that the magnetic torque, which is applied to a CNT, depends on the perpendicular and parallel susceptibilities of the CNT as well as on its initial orientation with respect to the magnetic direction. After exposure to magnetic pulses, the electrical property of the composites is enhanced. The results show that there is a positive correlation between the electrical conductance of CNTs and the number of applied pulses (for 30 pulses). Fourier transform infrared spectroscopy technique is used to control the polymer structure during the experiment. Our theoretical finding reveals the limited capacity of CNT’s alignment in magnetic fields.
MFiX, a general-purpose Fortran-based suite, simulates the complex flow in fluidized bed applications via BiCGStab and GMRES methods along with plane relaxation preconditioners. Trilinos, an object-oriented framework, contains various first- and second-generation Krylov subspace solvers and preconditioners. We developed a framework to integrate MFiX with Trilinos as MFiX does not possess advanced linear methods. The framework allows MFiX to access advanced linear solvers and preconditioners in Trilinos. The integrated solver is called MFiX–Trilinos, here after. In the present work, we study the performance of variants of GMRES and CGS methods in MFiX–Trilinos and BiCGStab and GMRES solvers in MFiX for a 3D gas–solid fluidized bed problem. Two right preconditioners employed along with various solvers in MFiX–Trilinos are Jacobi and smoothed aggregation. The flow from MFiX–Trilinos is validated against the same from MFiX for BiCGStab and GMRES methods. And, the effect of the preconditioning on the iterative solvers in MFiX–Trilinos is also analyzed. In addition, the effect of left and right smoothed aggregation preconditioning on the solvers is studied. Finally, the performance of the first- and second-generation solver stacks in MFiX–Trilinos is studied as well for two different problem sizes.