Numerical solutions to the continuity equation in the negative-glow-Faraday-dark-space transition
One dimensional charged particle continuity equation solution in low energy neutral plasma with current flows
SEARCH · Engineering Papers
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
One dimensional charged particle continuity equation solution in low energy neutral plasma with current flows
Under compressive creep, viscoplastic solids experiencing internal mass transfer processes can accommodate singular cnoidal wave solutions as material instabilities at the stationary wave limit. These instabilities appear when the loading rate is significantly faster than the material's capacity to diffusive internal perturbations, leading to localized failure features (e.g., cracks and compaction bands). These cnoidal waves, generally found in fluids, have strong nonlinearities that produce periodic patterns. Due to the singular nature of the solutions, the applicability of the theory is currently limited. Additionally, practical simulation tools require proper regularization to overcome the challenges that singularity induces. We focus on the numerical treatment of the governing equation using a nonlinear approach building on a recent adaptive stabilized finite element method. This automatic refinement method provides an error estimate that drives mesh adaptivity, a crucial feature for the problem at hand. We compare the performance of this adaptive strategy against analytical and standard finite element solutions. We then investigate the sensitivity of the diffusivity ratio, the parameter controlling the process, and identify multiple possible solutions with several stress peaks. We also show the evolution of the spacing between peaks for all solutions as a function of that parameter.
In this paper we present a technique based on deep reinforcement learning that allows for numerical analytic continuation of integrals that are often encountered in one-loop diagrams in quantum field theory. To extract certain quantities of two-point functions, such as spectral densities, mass poles or multiparticle thresholds, it is necessary to perform an analytic continuation of the correlator in question. At one-loop level in Euclidean space, this results in the necessity to deform the integration contour of the loop integral in the complex plane of the square of the loop momentum, to avoid nonanalyticities in the integration plane. Using a toy model for which an exact solution is known, we train a reinforcement learning agent to perform the required contour deformations. We report our study shows great promise for an agent to be deployed in iterative numerical approaches used to compute nonperturbative two-point functions, such as the quark propagator Dyson-Schwinger equation, or more generally, Fredholm equations of the second kind, in the complex domain.
A significant body of work exists showing that providing a nonlinear programming (NLP) solver with expressions for the problem constraint gradient substantially increases the speed of program execution and can also improve the robustness of convergence, especially for local optimizers. Calculation of these derivatives is often accomplished through the computation of spacecraft's state transition matrix (STM). If the two-body gravitational model is employed as is often done in the context of preliminary design, closed form expressions for these derivatives may be provided. If a high fidelity dynamics model, that might include perturbing forces such as the gravitational effect from multiple third bodies and solar radiation pressure is used then these STM's must be computed numerically. We present a method for the power hardward model and a full ephemeris model. An adaptive-step embedded eight order Dormand-Prince numerical integrator is discussed and a method for the computation of the time of flight derivatives in this framework is presented. The use of these numerically calculated derivatieves offer a substantial improvement over finite differencing in the context of a global optimizer. Specifically the inclusion of these STM's into the low thrust missiondesign tool chain in use at NASA Goddard Spaceflight Center allows for an increased preliminary mission design cadence.
Experimental and theoretical studies on the Variable Specific Impulse Magnetoplasma Rocket (VASIMR) have continued through a NASA led collaborative program involving several research groups. In the experimental area, performance characterization of the VASIMR helicon plasma source has been obtained over a portion of the parameter space, with helium and hydrogen propellant. Density (10(exp 18) - 10(exp 19)/ cubic meter) and temperature (5 eV) were measured at moderate degree of ionization in two separate experimental devices. Helicon design improvement and optimization will be discussed. Experiments with the ion cyclotron resonance heating (ICRH) subsection have begun and preliminary results will be discussed. Theoretical picture and integrated numerical simulation continue to be refined to account for the main physics elements of the VASIMR, including RF absorption and particle acceleration with subsequent detachment in the magnetic nozzle.
Borrowing from techniques developed for conservation law equations, numerical schemes which discretize the Hamilton-Jacobi (H-J), level set, and Eikonal equations on triangulated domains are presented. The first scheme is a provably monotone discretization for certain forms of the H-J equations. Unfortunately, the basic scheme lacks proper Lipschitz continuity of the numerical Hamiltonian. By employing a virtual edge flipping technique, Lipschitz continuity of the numerical flux is restored on acute triangulations. Next, schemes are introduced and developed based on the weaker concept of positive coefficient approximations for homogeneous Hamiltonians. These schemes possess a discrete maximum principle on arbitrary triangulations and naturally exhibit proper Lipschitz continuity of the numerical Hamiltonian. Finally, a class of Petrov-Galerkin approximations are considered. These schemes are stabilized via a least-squares bilinear form. The Petrov-Galerkin schemes do not possess a discrete maximum principle but generalize to high order accuracy.
Abstract Convectively coupled equatorial waves are a significant source of atmospheric variability in the tropics. Current numerical models continue to struggle in simulating the coupled diabatic heating fields that are responsible for the development and maintenance of these waves. This study investigates how the diabatic fields associated with Mixed Rossby–Gravity waves (MRGs) are represented in four reanalysis products by using a unique observational dataset from the TRMM‐KWAJEX (Tropical Rainfall Measuring Mission‐Kwajalein Experiment) field campaign. These reanalyses include ERA5, Japanese 55‐year Reanalysis (JRA‐55), Climate Forecast System Reanalysis (CFSR), and Modern‐Era Retrospective Analysis for Research and Applications (MERRA). We found that all four reanalyses captured the MRG structures in winds and temperature, and to a lesser degree in the humidity field except in the boundary layer. However, only the ERA5 and MERRA reanalyses captured the gradual rise and succession of the diabatic heating from boundary layer turbulence, shallow convection, cumulus congestus, and deep convection within the waves. ERA5 is the only product that also captured the gradual rise of the subgrid‐scale vertical transport of moist static energy. All reanalysis products underestimated the diabatic heating from cumulus congestus. Results provide observational basis on what aspects of MRG can be trusted and what cannot in the reanalysis products.
A high-order hybrid continuous-Galerkin numerical method, designed for the simulation of non-linear, non -hydrostatic internal waves and turbulence in long computational domains with complex bathymetry, is presented. The spatial discretization in the non-periodic wave-propagating directions, utilizes the nodal spectral element method. Such a high-order element-based discretization allows the highly accurate representation of complex domain geometry along with the flexibility of concentrating resolution in areas of interest. Under the assumption of the normal-to-isobath propagation of non-linear internal waves, a third periodic direction is incorporated via a Fourier-Galerkin discretization. The distinct non-hydrostatic nature of non-linear internal waves and, any instabilities and turbulence therein, necessitates the numerically challenging solution of the pressure Poisson problem. A defining feature of this work is the application of a domain decomposition approach, combined with block-Jacobi/deflation-based preconditioning to the pressure Poisson problem. Such a combined approach is particularly suitable for the long high aspect-ratio complex domains of interest and enables the efficient high-accuracy reproduction of the non-hydrostatic dynamics of non-linear internal waves. Implementation details are also described in the context of the stability of the solver and its parallelization strategy. A series of benchmarks of increasing complexity demonstrate the robustness of the flow solver. The benchmarks culminate with the three-dimensional simulation of a convectively breaking mode-one non-linear internal wave over a realistic South-China-Sea bathymetric transect and background current/stratification profiles.
In the two-component Fermi gas with a contact interaction, a pseudogap regime can exist at temperatures between the superfluid critical temperature $T_c$ and a temperature $T^\ast > T_c$. This regime is characterized by pairing correlations without superfluidity. However, in the unitary limit of infinite scattering length, the existence of this regime is still debated. To help address this, we have applied finite-temperature auxiliary-field quantum Monte Carlo (AFMC) methods to study the thermodynamics of the superfluid phase transition and signatures of the pseudogap in the spin-balanced homogeneous unitary Fermi gas. We present results at finite filling factor $\textit{ν}$ ≃ 0.06 for the condensate fraction, an energy-staggering pairing gap, the spin susceptibility, and the heat capacity, and compare them to experimental data when available. In contrast to previous AFMC simulations, our model space consists of the complete first Brillouin zone of the lattice, and our calculations are performed in the canonical ensemble of fixed particle number. The canonical ensemble AFMC framework enables the calculation of a model-independent gap, providing direct information on pairing correlations without the need for numerical analytic continuation. We use finite-size scaling to estimate $T_c$ at the corresponding filling factor. In this work, we find that the energy-staggering pairing gap vanishes above $T_c$, showing no pseudogap effects, and that the spin susceptibility shows a substantially reduced signature of a spin gap compared to previously reported AFMC simulations.
Building on previous developments [A. Taheridehkordi, S. H. Curnoe, and J. P. F. LeBlanc, Phys. Rev. B 99, 035120 (2019); A. Taheridehkordi, S. H. Curnoe, and J. P. F. LeBlancPhys. Rev. B101, 125109 (2020); A. Taheridehkordi, S. H. Curnoe, and J. P. F. LeBlancPhys. Rev. B102, 045115 (2020), B. Holm and U. von Barth, Phys. Rev. B 57, 2108 (1998), J. Vičičevic and M. Ferrero, Phys. Rev. B 101, 075113 (2020)], we show that the diagrammatic Monte Carlo technique allows us to compute finite-temperature response functions directly on the real-frequency axis within any field-theoretical formulation of the interacting fermion problem. There are no limitations on the type and nature of the system’s action or whether partial summation and self-consistent treatment of certain diagram classes are used. In particular, by eliminating the need for numerical analytic continuation from a Matsubara representation, our scheme allows us to study spectral densities of arbitrary complexity with controlled accuracy in models with frequency-dependent effective interactions. Finally, for illustrative purposes we consider the problem of the plasmon linewidth in a homogeneous electron gas (jellium).
Distributed energy resources (DERs), such as solar PVs and energy storage, can be used to restore distribution system critical loads after the extreme weather events to increase grid resilience. However, coordinating multiple DERs together with tie-switches for multi-step restoration process under renewable uncertainty is challenging. This paper proposes a deep reinforcement learning to control discrete actions of switching on/off tie switches and DERs for critical load restoration. The restoration problem is first cast into the Markov decision process suitable for DRL. Then, the original soft actor critic (SAC) method for continuous actions has been extended to handle discrete and continuous actions. Numerical comparison results with other stochastic optimization-based approaches on the modified IEEE 33-bus system show that the proposed method can achieve fast critical load restoration in the presence of substation power outage while maintaining system voltage limit throughout the restoration process.
We explored a novel framework for simulating the small-scale processes that drive the evolution of aerosol, cloud, and precipitation particles, which are a critical gap in the predictive understanding of weather and climate. Particle-based methods have emerged as an effective tool for modeling aerosol-cloud-precipitation interactions, but existing particle-based models are computationally too expensive to simulate the large domains relevant for the atmosphere or to represent the full suite of relevant processes. The lack of a comprehensive and efficient reference model is a critical bottleneck in our understanding of cloud and precipitation processes and our ability to parameterize these processes for regional- and global-scale simulations. To address this need, we explored an approach to accelerate and expand particle-based models using a new machine learning approach, graph network-based simulators (GNS). Rather than modeling the evolution of the system by numerically integrating continuity equations, the GNS represents dynamics through learned message passing. Our aim was to develop fast and accurate surrogate models for particle-based simulations. We explored applying GNS to simulate cloud droplet transport, growth, and evaporation under turbulent conditions, but we found the GNS over-smoothed the simulations. We then applied the GNS to simulate aerosol dynamics through gas condensation and found the GNS was able to reproduce the benchmark, physics-based simulation with high accuracy.
Two body and two channel nonrelativistic scattering amplitudes calculation method using numerical analytic continuation by rational fractions
The problem of obtaining an optimal control law, which is constrained to be a linear feedback of the available measurements, for both continuous and discrete time linear systems subjected to additive white process noise and measurement noise was Necessary conditions are obtained for minimizing a quadratic performance function for both finite and infinite terminal time cases. The feedback gains are constrained to be time invariant for the infinite terminal time cases. For all the cases considered, algorithms are derived for generating sequences of feedback gain matrices which successively improve the performance function. A continuous time numerical example is included for the purpose of demonstration.
A finite difference scheme for three-dimensional steady laminar incompressible flows is presented. The Navier-Stokes equations are expressed conservatively in terms of velocity and pressure increments (delta form). First order upwind differences are used for first order partial derivatives of velocity increments resulting in a diagonally dominant matrix system. Central differences are applied to all other terms for second order accuracy. The SIMPLE pressure correction algorithm is used to satisfy the continuity equation. Numerical results are presented for cubic cavity flow problems for Reynolds numbers up to 2000 and are in good agreement with other numerical results.
A finite difference scheme for three-dimensional steady laminar incompressible flows is presented. The Navier-Stokes equations are expressed conservatively in terms of velocity and pressure increments (delta form). First order upwind differences are used for first order partial derivatives of velocity increments resulting in a diagonally dominant matrix system. Central differences are applied to all other terms for second order accuracy. The SIMPLE pressure correction algorithm is used to satisfy the continuity equation. Numerical results are presented for cubic cavity flow problems for Reynolds numbers up to 2000 and are in good agreement with other numerical results.
An analysis of the single-blow transient testing technique for heat exchanger surfaces is made for perforated plate and similar discontinuous surfaces. The model assumes that there is no temperature variation across each plate, and allows for axial conduction in spacers: the resulting axial fluid temperature profile is discontinuous, rather than the usual continuous profile. Numerical solutions are obtained to the resulting set of coupled first-order differential equations for a step change in inlet fluid temperature. Results are presented in tabular form, which allow the heat transfer coefficients to be calculated from test data using the maximum slope technique.
Pickup ions formed from ionized neutral exospheres in flowing plasmas have phase space distributions that reflect their source's spatial distributions. Phase space distributions of the ions are derived from the Vlasov equation with a delta function source using three.dimensional neutral exospheres. The ExB drift produced by plasma motion picks up the ions while the effects of magnetic field draping, mass loading, wave particle scattering, and Coulomb collisions near a planetary body are ignored. Previously, one.dimensional exospheres were treated, resulting in closed form pickup ion distributions that explicitly depend on the ratio rg/H, where rg is the ion gyroradius and H is the neutral scale height at the exobase. In general, the pickup ion distributions, based on three.dimensional neutral exospheres, cannot be written in closed form, but can be computed numerically. They continue to reflect their source's spatial distributions in an implicit way. These ion distributions and their moments are applied to several bodies, including He(+) and Na(+) at the Moon, H(+2) and CH(+4) at Titan, and H+ at Venus. The best places to use these distributions are upstream of the Moon's surface, the ionopause of Titan, and the bow shock of Venus.