Algorithm for computational and experimental determination of the acoustic characteristics of solid propulsion engine

Combustion instability in rocket engines is accompanied by large-amplitude pressure fluctuations in the combustion chamber and (or) intense vibration of the load-bearing structural elements. Unstable operation leads to a decrease in thrust, specific impulse, a decrease in engine life, a violation of the normal operation of vibration-sensitive flight control system equipment. The study considers a method for determining the frequencies of the first and second tone natural resonances of the longitudinal mode of acoustic vibrations in the combustion chambers of solid propulsion engines. The gas path of the combustion chamber is divided into homogeneous sections, for which solutions of the wave equation are presented. To determine the natural frequencies and the distribution of vibrational pressures and velocities, the method of "stitching" acoustic fields at the boundaries of cavities was applied. In the course of the study, to determine the decrement from natural perturbations, the following methods were used: spectral, correlation, amplitude, and instantaneous period method. In the study, vibrations of a certain frequency in a given range were excited using an electrodynamic emitter. To obtain the acoustic characteristics of the camera at various moments of engine operation, experiments were carried out with several charge models having different sizes. The solution of the wave equation in the form of standing waves was considered. In addition, the study results present a description of the experimental setup, in particular, the distribution of the oscillatory pressure in the chamber gas cavity (according to the calculated data). In the course of the study, an algorithm was developed for calculating and experimentally determining the acoustic characteristics of the combustion chambers of solid propulsion engines

Independent components in spectroscopic analysis of complex mixtures

We applied two methods of "blind" spectral decomposition (MILCA and SNICA) to quantitative and qualitative analysis of UV absorption spectra of several non-trivial mixture types. Both methods use the concept of statistical independence and aim at the reconstruction of minimally dependent components from a linear mixture. We examined mixtures of major ecotoxicants (aromatic and polyaromatic hydrocarbons), amino acids and complex mixtures of vitamins in a veterinary drug. Both MICLA and SNICA were able to recover concentrations and individual spectra with minimal errors comparable with instrumental noise. In most cases their performance was similar to or better than that of other chemometric methods such as MCR-ALS, SIMPLISMA, RADICAL, JADE and FastICA. These results suggest that the ICA methods used in this study are suitable for real life applications. Data used in this paper along with simple matlab codes to reproduce paper figures can be found at http://www.klab.caltech.edu/~kraskov/MILCA/spectraComment: 22 pages, 4 tables, 6 figure

Least Dependent Component Analysis Based on Mutual Information

We propose to use precise estimators of mutual information (MI) to find least dependent components in a linearly mixed signal. On the one hand this seems to lead to better blind source separation than with any other presently available algorithm. On the other hand it has the advantage, compared to other implementations of `independent' component analysis (ICA) some of which are based on crude approximations for MI, that the numerical values of the MI can be used for: (i) estimating residual dependencies between the output components; (ii) estimating the reliability of the output, by comparing the pairwise MIs with those of re-mixed components; (iii) clustering the output according to the residual interdependencies. For the MI estimator we use a recently proposed k-nearest neighbor based algorithm. For time sequences we combine this with delay embedding, in order to take into account non-trivial time correlations. After several tests with artificial data, we apply the resulting MILCA (Mutual Information based Least dependent Component Analysis) algorithm to a real-world dataset, the ECG of a pregnant woman. The software implementation of the MILCA algorithm is freely available at http://www.fz-juelich.de/nic/cs/softwareComment: 18 pages, 20 figures, Phys. Rev. E (in press

Milliwatt terahertz harmonic generation from topological insulator metamaterials

Achieving efficient, high-power harmonic generation in the terahertz spectral domain has technological applications, for example in sixth generation (6G) communication networks. Massless Dirac fermions possess extremely large terahertz nonlinear susceptibilities and harmonic conversion efficiencies. However, the observed maximum generated harmonic power is limited, because of saturation effects at increasing incident powers, as shown recently for graphene. Here, we demonstrate room-temperature terahertz harmonic generation in a Bi$_2$Se$_3$ topological insulator and topological-insulator-grating metamaterial structures with surface-selective terahertz field enhancement. We obtain a third-harmonic power approaching the milliwatt range for an incident power of 75 mW - an improvement by two orders of magnitude compared to a benchmarked graphene sample. We establish a framework in which this exceptional performance is the result of thermodynamic harmonic generation by the massless topological surface states, benefiting from ultrafast dissipation of electronic heat via surface-bulk Coulomb interactions. These results are an important step towards on-chip terahertz (opto)electronic applications

Capture and escape in the elliptic restricted three-body problem

While the large regular moons of the giant planets follow almost circular, low inclination, prograde orbits, the aptly named irregular moons tend to do the opposite: i.e. they often have highly eccentric, high-inclination orbits, which may be retrograde or prograde. Thes