Simulation of a GOx-GCH4 Rocket Combustor and the Effect of the GEKO Turbulence Model Coefficients

In this study, a single injector methane-oxygen rocket combustor is numerically studied. The simulations included in this study are based on the hardware and experimental data from the Technical University of Munich. The focus is on the recently developed generalized k–ω turbulence model (GEKO) and the effect of its adjustable coefficients on the pressure and on wall heat flux profiles, which are compared with the experimental data. It was found that the coefficients of ‘jet’, ‘near-wall’, and ‘mixing’ have a major impact, whereas the opposite can be deduced about the ‘separation’ parameter Csep, which highly influences the pressure and wall heat flux distributions due to the changes in the eddy-viscosity field. The simulation results are compared with the standard k–ε model, displaying a qualitatively and quantitatively similar behavior to the GEKO model at a Csep equal to unity. The default GEKO model shows a stable performance for three oxidizer-to-fuel ratios, enhancing the reliability of its use. The simulations are conducted using two chemical kinetic mechanisms: Zhukov and Kong and the more detailed RAMEC. The influence of the combustion model is of the same order as the influence of the turbulence model. In general, the numerical results present a good or satisfactory agreement with the experiment, and both GEKO at Csep = 1 or the standard k–ε model can be recommended for usage in the CFD simulations of rocket combustion chambers, as well as the Zhukov–Kong mechanism in conjunction with the flamelet approach.

The Theory of the Hydrogen Molecule Ion, Scalar Beams, and Scattering by Spheroids

<p>Schrodinger's equation for the hydrogen molecule ion and the Helmholtz equation are separable in prolate and oblate spheroidal coordinates respectively. They share the same form of the angular equation. The first task in deriving the ground state energy of the hydrogen molecule ion, and in obtaining finite solutions of the Helmholtz equation, is to obtain the physically allowed values of the separation of variables parameter. The separation parameter is not known analytically, and since it can only have certain values, it is an important parameter to quantify. Chapter 2 of this thesis investigates an exact method of obtaining the separation parameter. By showing that the angular equation is solvable in terms of confluent Heun functions, a new method to obtain the separation parameter was obtained. We showed that the physically allowed values of the separation of variables parameter are given by the zeros of the Wronskian of two linearly dependent solutions to the angular equation. Since the Heun functions are implemented in Maple, this new method allows the separation parameter to be calculated to unlimited precision. As Schrodinger's equation for the hydrogen molecule ion is related to Helmholtz's equation, this warranted investigation of scalar beams. Tightly focused optical and quantum particle beams are described by exact solutions of the Helmholtz equation. In Chapter 3 of this thesis we investigate the applicability of the separable spheroidal solutions of the scalar Helmholtz equation as physical beam solutions. By requiring a scalar beam solution to satisfy certain physical constraints, we showed that the oblate spheroidal wave functions can only represent nonparaxial scalar beams when the angular function is odd, in terms of the angular variable. This condition ensures the convergence of integrals of physical quantities over a cross-section of the beam and allows for the physically necessary discontinuity in phase at z = 0 on the ellipsoidal surfaces of otherwise constant phase. However, these solutions were shown to have a discontinuous longitudinal derivative. Finally, we investigated the scattering of scalar waves by oblate and prolate spheroids whose symmetry axis is coincident with the direction of the incident plane wave. We developed a phase shift formulation of scattering by oblate and prolate spheroids, in parallel with the partial wave theory of scattering by spherical obstacles. The crucial step was application of a finite Legendre transform to the Helmholtz equation in spheroidal coordinates. Analytical results were readily obtained for scattering of Schrodinger particle waves by impenetrable spheroids and for scattering of sound waves by acoustically soft spheroids. The advantage of this theory is that it enables all that can be done for scattering by spherical obstacles to be carried over to the scattering by spheroids, provided the radial eigenfunctions are known.</p>

The Theory of the Hydrogen Molecule Ion, Scalar Beams, and Scattering by Spheroids

<p>Schrodinger's equation for the hydrogen molecule ion and the Helmholtz equation are separable in prolate and oblate spheroidal coordinates respectively. They share the same form of the angular equation. The first task in deriving the ground state energy of the hydrogen molecule ion, and in obtaining finite solutions of the Helmholtz equation, is to obtain the physically allowed values of the separation of variables parameter. The separation parameter is not known analytically, and since it can only have certain values, it is an important parameter to quantify. Chapter 2 of this thesis investigates an exact method of obtaining the separation parameter. By showing that the angular equation is solvable in terms of confluent Heun functions, a new method to obtain the separation parameter was obtained. We showed that the physically allowed values of the separation of variables parameter are given by the zeros of the Wronskian of two linearly dependent solutions to the angular equation. Since the Heun functions are implemented in Maple, this new method allows the separation parameter to be calculated to unlimited precision. As Schrodinger's equation for the hydrogen molecule ion is related to Helmholtz's equation, this warranted investigation of scalar beams. Tightly focused optical and quantum particle beams are described by exact solutions of the Helmholtz equation. In Chapter 3 of this thesis we investigate the applicability of the separable spheroidal solutions of the scalar Helmholtz equation as physical beam solutions. By requiring a scalar beam solution to satisfy certain physical constraints, we showed that the oblate spheroidal wave functions can only represent nonparaxial scalar beams when the angular function is odd, in terms of the angular variable. This condition ensures the convergence of integrals of physical quantities over a cross-section of the beam and allows for the physically necessary discontinuity in phase at z = 0 on the ellipsoidal surfaces of otherwise constant phase. However, these solutions were shown to have a discontinuous longitudinal derivative. Finally, we investigated the scattering of scalar waves by oblate and prolate spheroids whose symmetry axis is coincident with the direction of the incident plane wave. We developed a phase shift formulation of scattering by oblate and prolate spheroids, in parallel with the partial wave theory of scattering by spherical obstacles. The crucial step was application of a finite Legendre transform to the Helmholtz equation in spheroidal coordinates. Analytical results were readily obtained for scattering of Schrodinger particle waves by impenetrable spheroids and for scattering of sound waves by acoustically soft spheroids. The advantage of this theory is that it enables all that can be done for scattering by spherical obstacles to be carried over to the scattering by spheroids, provided the radial eigenfunctions are known.</p>

Stacked Ensemble Machine Learning for Range-Separation Parameters

High-throughput virtual materials and drug discovery based on density functional theory has achieved tremendous success in recent decades, but its power on organic semiconducting molecules suffered catastrophically from the self-interaction error until the optimally tuned range-separated hybrid (OT-RSH) exchange-correlation functionals were developed. The accurate but expensive �first-principles OT-RSH transitions from a short-range (semi-)local functional to a long-range Hartree-Fock exchange at a distance characterized by the inverse of a molecule-specific, non-empirically-determined range-separation parameter (ω). In the present study, we proposed a promising stacked ensemble machine learning (SEML) model that provides an accelerated alternative of OT-RSH based on system-dependent structural and electronic configurations. We trained ML-ωPBE, the first functional in our series, using a database of 1,970 organic semiconducting molecules with sufficient structural diversity, and assessed its accuracy and efficiency using another 1,956 molecules. Compared with the �first-principles OT-ωPBE, our ML-ωPBE reached a mean absolute error of 0:00504a_0^{-1} for the optimal value of ω, reduced the computational cost for the test set by 2.66 orders of magnitude, and achieved comparable predictive powers in various optical properties.

Homogenization of Coupled Fast-Slow Systems via Intermediate Stochastic Regularization

In this paper we study coupled fast-slow ordinary differential equations (ODEs) with small time scale separation parameter $$\varepsilon $$ ε such that, for every fixed value of the slow variable, the fast dynamics are sufficiently chaotic with ergodic invariant measure. Convergence of the slow process to the solution of a homogenized stochastic differential equation (SDE) in the limit $$\varepsilon $$ ε to zero, with explicit formulas for drift and diffusion coefficients, has so far only been obtained for the case that the fast dynamics evolve independently. In this paper we give sufficient conditions for the convergence of the first moments of the slow variable in the coupled case. Our proof is based upon a new method of stochastic regularization and functional-analytical techniques combined via a double limit procedure involving a zero-noise limit as well as considering $$\varepsilon $$ ε to zero. We also give exact formulas for the drift and diffusion coefficients for the limiting SDE. As a main application of our theory, we study weakly-coupled systems, where the coupling only occurs in lower time scales.

Renewal model for anomalous traffic in Internet2 links

We propose and estimate an alternating renewal model describing the propagation of anomalies in a backbone internet network in the United States. Internet anomalies, either caused by equipment malfunction, news events or malicious attacks, have been a focus of research in network engineering since the advent of the internet over 30 years ago. This article contributes to the understanding of statistical properties of the times between the arrivals of the anomalies, their duration and stochastic structure. Anomalous, or active, time periods are modelled as periods containing clusters or 1s, where 1 indicates a presence of an anomaly. The inactive periods consisting entirely of 0s dominate the 0–1 time series in every link. Since the active periods contain 0s, a separation parameter is introduced and estimated jointly with all other parameters of the model. Our statistical analysis shows that the integer-valued separation parameter and five other non-negative, scalar parameters satisfactorily describe all statistical properties of the observed 0–1 series.

Renewal model for anomalous traffic in Internet2 links

We propose and estimate an alternating renewal model describing the propagation of anomalies in a backbone internet network in the United States. Internet anomalies, either caused by equipment malfunction, news events or malicious attacks, have been a focus of research in network engineering since the advent of the internet over 30 years ago. This article contributes to the understanding of statistical properties of the times between the arrivals of the anomalies, their duration and stochastic structure. Anomalous, or active, time periods are modelled as periods containing clusters or 1s, where 1 indicates a presence of an anomaly. The inactive periods consisting entirely of 0s dominate the 0–1 time series in every link. Since the active periods contain 0s, a separation parameter is introduced and estimated jointly with all other parameters of the model. Our statistical analysis shows that the integer-valued separation parameter and five other non-negative, scalar parameters satisfactorily describe all statistical properties of the observed 0–1 series.

Testing and Validating Two Morphological Flare Predictors by Logistic Regression Machine Learning

Whilst the most dynamic solar active regions (ARs) are known to flare frequently, predicting the occurrence of individual flares and their magnitude, is very much a developing field with strong potentials for machine learning applications. The present work is based on a method which is developed to define numerical measures of the mixed states of ARs with opposite polarities. The method yields compelling evidence for the assumed connection between the level of mixed states of a given AR and the level of the solar eruptive probability of this AR by employing two morphological parameters: 1) the separation parameter Sl−f and 2) the sum of the horizontal magnetic gradient GS. In this work, we study the efficiency of Sl−f and GS as flare predictors on a representative sample of ARs, based on the SOHO/MDI-Debrecen Data (SDD) and the SDO/HMI - Debrecen Data (HMIDD) sunspot catalogues. In particular, we investigate about 1,000 ARs in order to test and validate the joint prediction capabilities of the two morphological parameters by applying the logistic regression machine learning method. Here, we confirm that the two parameters with their threshold values are, when applied together, good complementary predictors. Furthermore, the prediction probability of these predictor parameters is given at least 70% a day before.