In this study, the capability of using a C-band polarimetric Doppler radar and a two-dimensional video disdrometer (2DVD) to estimate monsoon-influenced summer rainfall during the Observation, Prediction and Analysis of Severe Convection of China (OPACC) field campaign in 2014 and 2015 in eastern China is investigated. Three different rainfall R estimators, for reflectivity at horizontal polarization [R(Zh)], for reflectivity at horizontal polarization and differential reflectivity factor [R(Zh, Zdr)], and for specific differential phase [R(KDP)], are derived from 2-yr 2DVD observations of summer precipitation systems. The radar-estimated rainfall is compared to gauge observations from eight rainfall episodes. Results show that the two polarimetric estimators, R(Zh, Zdr) and R(KDP), perform better than the traditional Zh–R relation [i.e., R(Zh)]. The KDP-based estimator [i.e., R(KDP)] produces the best rainfall accumulations. The radar rainfall estimators perform differently across the three organized convective systems (mei-yu rainband, typhoon rainband, and squall line). Estimator R(Zh) overestimates rainfall in the mei-yu rainband and squall line, and R(Zh, Zdr) mitigates the overestimation in the mei-yu rainband but has a large bias in the squall line. QPE from R(KDP) is the most accurate among the three estimators, but it possesses a relatively large bias for the squall line compared to the mei-yu case. The high variability of drop size distribution (DSD) related to the precipitation microphysics in different types of rain is largely responsible for the case-dependent QPE performance using any single radar rainfall estimator. The squall line has a distinct ice-phase process with a large mean size of raindrops, while the mei-yu rainband and typhoon rainband are composed of smaller raindrops. Based on the statistical QPE error in the ZH–ZDR space, a new composite rainfall estimator is constructed by combining R(Zh), R(Zh, Zdr), and R(KDP) and is proven to outperform any single rainfall estimator.
We propose a model-free time delay signature (TDS) extraction method for optical chaos systems. The TDS can be identified from time series without prior knowledge of the actual physical processes. In optical chaos secure communication systems, the chaos carrier is usually generated by a laser diode subject to opto-electronic/all-optical time delayed feedback. One of the most important factors to security considerations is the concealment of the TDS. So far, statistical analysis methods such as autocorrelation function (ACF) and delayed mutual information (DMI) are usually used to unveil the TDS. However, the effectiveness of these methods will be reduced when increasing the nonlinearity of chaos systems. Meanwhile, certain TDS concealment strategies have been designed against statistical analysis. In our previous work, convolutional neural network shows its effectiveness on TDS extraction of chaos systems with high loop nonlinearity. However, this method relies on the knowledge of detailed structure of the chaos systems. In this work, we formulate a blind identification method based on long short-term memory neural network (LSTM-NN) model. The method is validated against the two major types of optical chaos systems, i.e. opto-electronic oscillator (OEO) chaos system and laser chaos system based on internal nonlinearity. Moreover, some security enhanced chaotic systems are also studied. The results show that the proposed method has high tolerance to additive noise. Meanwhile, the data amount needed is less than existing methods.
Purpose The purpose of this paper is to develop an improved adhesion model to better reproduce the low adhesion condition of the anti-skid control for rail vehicles under braking condition. Design/methodology/approach In view of the low adhesion characteristics for rail vehicles under braking conditions, the Polach adhesion model was improved based on the sliding power and sliding energy. The wheel–rail low adhesion model suitable for braking condition was given. The analysis of braking anti-skid control under emergency braking condition was carried out through the co-simulation, and compared with the test data; the effectiveness and practicability of the improved low adhesion model were verified. Findings The results showed that the improved adhesion model is simple and efficient and the parameters involved are less, and it can be directly applied to the real-time simulation of anti-skid control in the process of train braking. Originality/value This paper can provide a theoretical reference for the reasons of change and improvement of adhesion between wheel and rail caused by the adjustment of braking force under anti-skid control, which can fulfill a need to the study of sliding energy on the contact surface, the removal effect of pollutants on the wheel–rail surface and the improvement and recovery of adhesion caused. Peer review The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-07-2020-0244/
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