A novel approach to determine upper tolerance limit of non-stationary vibrations during rocket launch

This paper firstly introduces a locally stationary model to analyze non-stationary environmental vibrations during a rocket launch. Then based on this model, a novel method is proposed to estimate the upper tolerance limit of expected non-stationary environmental vibrations, which can be used to evaluate whether equipments on rocket can experience environmental vibrations in safe. Compared with available method, the proposed method can characterize non-stationary vibration better

Channel Adaptive DL based Joint Source-Channel Coding without A Prior Knowledge

Significant progress has been made in wireless Joint Source-Channel Coding (JSCC) using deep learning techniques. The latest DL-based image JSCC methods have demonstrated exceptional performance across various signal-to-noise ratio (SNR) levels during transmission, while also avoiding cliff effects. However, current channel adaptive JSCC methods rely heavily on channel prior knowledge, which can lead to performance degradation in practical applications due to channel mismatch effects. This paper proposes a novel approach for image transmission, called Channel Blind Joint Source-Channel Coding (CBJSCC). CBJSCC utilizes Deep Learning techniques to achieve exceptional performance across various signal-to-noise ratio (SNR) levels during transmission, without relying on channel prior information. We have designed an Inverted Residual Attention Bottleneck (IRAB) module for the model, which can effectively reduce the number of parameters while expanding the receptive field. In addition, we have incorporated a convolution and self-attention mixed encoding module to establish long-range dependency relationships between channel symbols. Our experiments have shown that CBJSCC outperforms existing channel adaptive DL-based JSCC methods that rely on feedback information. Furthermore, we found that channel estimation does not significantly benefit CBJSCC, which provides insights for the future design of DL-based JSCC methods. The reliability of the proposed method is further demonstrated through an analysis of the model bottleneck and its adaptability to different domains, as shown by our experiments

A High Efficiency Aluminum-Ion Battery Using an AlCl3-Urea Ionic Liquid Analogue Electrolyte

In recent years, impressive advances in harvesting renewable energy have led to pressing demand for the complimentary energy storage technology. Here, a high coulombic efficiency (~ 99.7%) Al battery is developed using earth-abundant aluminum as the anode, graphite as the cathode, and a cheap ionic liquid analogue electrolyte made from a mixture of AlCl3 and urea in 1.3 : 1 molar ratio. The battery displays discharge voltage plateaus around 1.9 V and 1.5 V (average discharge = 1.73 V) and yielded a specific cathode capacity of ~73 mAh g-1 at a current density of 100 mA g-1 (~ 1.4 C). High coulombic efficiency over a range of charge-discharge rates and stability over ~150-200 cycles was easily demonstrated. In-situ Raman spectroscopy clearly showed chloroaluminate anion intercalation/deintercalation of graphite in the cathode side during charge/discharge and suggested the formation of a stage 2 graphite intercalation compound when fully charged. Raman spectroscopy and nuclear magnetic resonance suggested the existence of AlCl4-, Al2Cl7- anions, and [AlCl2. (urea)n]+ cations in the urea/AlCl3 electrolyte when an excess of AlCl3 was present. Aluminum deposition therefore proceeded through two pathways, one involving Al2Cl7- anions and the other involving [AlCl2.(urea)n]+ cations. This battery is a promising prospect for a future high performance, low cost energy storage device

Jacobian determinants for (nonlinear) gradient of planar ∞\infty-harmonic functions and applications

In dimension 2, we introduce a distributional Jacobian determinant $\det DV_\beta(Dv)$ for the nonlinear complex gradient $(x_1,x_2)\mapsto |Dv|^\beta(v_{x_1},-v_{x_2})$ for any $\beta>-1$, whenever $v\in W^{1,2 }_{\text{loc}}$ and $\beta |Dv|^{1+\beta}\in W^{1,2}_{\text{loc}}$. Then for any planar $\infty$-harmonic function $u$, we show that such distributional Jacobian determinant is a nonnegative Radon measure with some quantitative local lower and upper bounds. We also give the following two applications. (i) Applying this result with $\beta=0$, we develop an approach to build up a Liouville theorem, which improves that of Savin [33]. Precisely, if $u$ is $\infty$-harmonic functions in whole ${\mathbb R}^2$ with $$\liminf_{R\to\infty}\inf_{c\in\mathbb R}\frac1 {R^3}\int_{B(0,R)}|u(x)-c|\,dx<\infty,$$ then $u=b+a\cdot x$ for some $b\in{\mathbb R}$ and $a\in{\mathbb R}^2$. (ii) Denoting by $u_p$ the $p$-harmonic function having the same nonconstant boundary condition as $u$, we show that $\det DV_\beta(Du_p) \to \det DV_\beta(Du)$ as $p\to\infty$ in the weak-$\star$ sense in the space of Radon measure. Recall that $V_\beta(Du_p)$ is always quasiregular mappings, but $V_\beta(Du)$ is not in general.Comment: 31 pages, some minor changes, submitte

On-line Partial Discharge Localization of 10-kV Covered Conductor Lines

This paper proposes an innovative partial discharge (PD) location technique for overhead electrical power distribution networks. It is aimed at improving the condition-based maintenance of the network. PD localization is carried out via an improved double-sided traveling-wave method. The method is driven by a hybrid detection technique, which integrates a pulse-based synchronization mechanism and a global positioning system (GPS). The proposed solution offers a number of benefits. It has the nice inherent feature of being immune to varying physical parameters of the transmission line, and it has been proven be offer improved accuracy with respect of the conventional GPS-based location methods. Also, an in-house designed portable and non-invasive test setup is presented and thoroughly discussed, thus demonstrating the feasibility of the proposed method. Moreover, an enhanced algorithm is embedded into the PD location system to improve robustness to high-level noise. Finally, the proposed tool relies on a well-established automatic procedure which requires neither parameter tuning nor any expert intervention. The features and strengths of the method are validated on a real case consisting of a 2125-m long 10-kV overhead covered conductor line

An Automatic Tool for Partial Discharge De-noising via Short Time Fourier Transform and Matrix Factorization

This paper develops a fully automatic tool for the denoising of partial discharge (PD) signals occurring in electrical power networks and recorded in on-site measurements. The proposed method is based on the spectral decomposition of the PD measured signal via the joint application of the short-time Fourier transform and the singular value decomposition. The estimated noiseless signal is reconstructed via a clever selection of the dominant contributions, which allows us to filter out the different spurious components, including the white noise and the discrete spectrum noise. The method offers a viable solution which can be easily integrated within the measurement apparatus, with unavoidable beneficial effects in the detection of important parameters of the signal for PD localization. The performance of the proposed tool is first demonstrated on a synthetic test signal and then it is applied to real measured data. A cross comparison of the proposed method and other state-of-the-art alternatives is included in the study

A Compact Detector for Flexible Partial Discharge Monitoring of 10-kV Overhead Covered Conductor Lines

The availability of accurate and cost-effective solutions for the real-time monitoring of overhead covered conductors (CC) is now becoming an important tool for the reliability and condition assessments of this class of electrical lines. This is even more crucial due to the possibly large number of conductors and the wide geographical spread of the electrical network. This letter proposes a smart and compact detector for partial discharge (PD) based monitoring, matching the above needs and offering a flexible and cost-effective solution with some important features, including a non-invasive sensing, a field energy harvesting function, and a low-power working operation. The detector has been designed and implemented, proving its effectiveness on real cases involving PD-affected 10 kV CC lines

Multi-Scale Simulation of Complex Systems: A Perspective of Integrating Knowledge and Data

Complex system simulation has been playing an irreplaceable role in understanding, predicting, and controlling diverse complex systems. In the past few decades, the multi-scale simulation technique has drawn increasing attention for its remarkable ability to overcome the challenges of complex system simulation with unknown mechanisms and expensive computational costs. In this survey, we will systematically review the literature on multi-scale simulation of complex systems from the perspective of knowledge and data. Firstly, we will present background knowledge about simulating complex system simulation and the scales in complex systems. Then, we divide the main objectives of multi-scale modeling and simulation into five categories by considering scenarios with clear scale and scenarios with unclear scale, respectively. After summarizing the general methods for multi-scale simulation based on the clues of knowledge and data, we introduce the adopted methods to achieve different objectives. Finally, we introduce the applications of multi-scale simulation in typical matter systems and social systems