Effect of thermal noise on random lasers in diffusion regime

In this paper, we study the effects of thermal noise on the time evolution of a weak light pulse (probe) in the presence of a strong light pulse (pump) within a gain medium which includes random scatterer particles. Suitable thermal noise term is added to a set of four coupled equations including three diffusion equations for energy densities and a rate equation for the upper level population in a four-level gain medium. These equations have been solved simultaneously by Crank–Nicholson numerical method. The main result is that the back-scattered output probe light is increased as the thermal noise strength is increased and simultaneously, with the same rate, the amplified spontaneous emission is decreased. Therefore, the amplified response of the random laser in diffusion regime for the input probe pulse is enhanced due to effect of the thermal noise.     

Micro-structural study of Yaozhou celadons (Tang to Yuan Dynasty): probing crystalline and glassy phases

The Yaozhou kiln complex is a representative production center of ancient northern China, famous for the celadon production. In this work, bubbles, glassy matrix and residual crystals of celadon glazes produced from the Tang to Yuan Dynasty were analyzed by using optical microscopy, Raman spectroscopy and scanning electron microscopy-energy dispersive X-ray spectroscopy (SEM-EDS). The results revealed that the Song, Jin and Yuan productions present bigger bubble and higher area ratios of the Si-O bending over stretching modes than the Tang and Wudai productions. This is consistent with firings at higher temperatures during Song, Jin and Yuan Dynasties. It is also in agreement with the historical studies, which revealed the change from wood-firing to coal-firing during Song Dynasty. The observation of calcium phosphate in Yaozhou productions indicated that the glaze ash had been used. No iron-based particle was identified by Raman spectroscopy in the glazes of all periods. The green color is certainly due to iron ion dispersed in the glassy matrix. Our study also confirmed no significant change in glaze raw materials used for Yaozhou productions from Tang to Yuan Dynasty.     

基于语义分割的DWTT断口图像识别和评定方法研究

对石油管材落锤撕裂断口进行评定,目前采用的方法主要通过游标卡尺等测量工具进行测量和计算,存在对工作人员经验要求高、主观因素影响大、不规则形貌判别困难和效率低等缺点。针对以上问题提出了一种具有空洞卷积的编解码器模型的管材断口图像语义分割方法,首先对采集好的试样断口进行脆性区域的数据集标记,然后利用标记好的数据集对DeepLabV3+网络模型进行训练,该模型可以有效地分割试样断口中的脆性区域。最后对管材试样断口评定的计算方法进行了基于像素级别的改进,在对实验结果进行分析和对比后表明,所提出的方法具有更高稳定性、高准确率和良好分割效果。     

Rate-distortion-complexity optimization for x265

Rate-distortion optimization (RDO) is conventionally based on the analysis of rate-distortion (R-D) curve to minimize the coding distortion under the coding bits constraint. However, it is necessary to consider the computational complexity in the RDO process. In this paper, we obtain the Confidence LEvel - Computational complexity (CLEC) curves which indicate the characteristics of coding tree units (CTUs). Based on the CLEC curves, a rate-distortion-complexity optimization (RDCO) algorithm is proposed to optimize R-D under given computational complexity and achieve the optimal coding performance for x265. Experimental results demonstrate that the proposed algorithm can achieve a wide range of encoding speed under a given quantization parameter (QP) whereas the original x265 can only achieve a few fixed encoding speeds, and the proposed algorithm can reduce the BD-rate and increase the BD-PSNR by 6.59% and 0.13 dB on average under the same requirements of encoding speeds as the original x265.     

厄瓜多尔Sacha油田砾石层安全钻进钻井液技术

厄瓜多尔Sacha油田TIYUYACU层存在上下2个砾石层,上砾石层厚度约为61 m,下砾石层厚度超过200 m。该地层研磨性强、渗透性强,对压力敏感,是钻井过程中出现复杂甚至事故的高发地层。本文通过分析Sacha 44MD井在砾石层出现的问题,从钻井液的角度找出问题出现的原因,提出优化方案。通过降低体系密度,加强封堵性等措施,实现了砾石层的安全快速钻进,自Sacha 44XD井以后,在砾石层钻进顺利,起下钻、下套管等也未出现遇阻等复杂情况,为解决砾石层钻进难题积累了宝贵的经验。     

Fault handling in large water networks with online dictionary learning

Fault detection and isolation in water distribution networks is an active topic due to the nonlinearities of flow propagation and recent increases in data availability due to sensor deployment. Here, we propose an efficient two-step data driven alternative: first, we perform sensor placement taking the network topology into account; second, we use incoming sensor data to build a network model through online dictionary learning. Online learning is fast and allows tackling large networks as it processes small batches of signals at a time. This brings the benefit of continuous integration of new data into the existing network model, either in the beginning for training or in production when new data samples are gathered. The proposed algorithms show good performance in our simulations on both small and large-scale networks.     

Risk-involved stochastic performance of hydrogen storage based intelligent parking lots of electric vehicles using downside risk constraints method

Today, the utilizations of hydrogen storage systems (HSS), renewable generation units (PV and wind generation) and distributed energy units are increased in the intelligent parking lots (IPL) in order to charge the electric vehicles (EVs) with clean energy sources. In this work, the uncertainties of upstream grid price, the demand of IPL, wind speed, solar irradiation and temperature are modeled via scenario approach based on stochastic programing. Furthermore, the downside risk constraints method (DRCM) is applied to consider risk related to uncertainties to get risk-involved stochastic performance of hydrogen storage based intelligent parking lots of electric vehicles. The proposed risk-based formulation is modeled using mixed-integer linear programming (MIP) which is implemented under GAMS software and solved via CPLEX solver. Two cases namely risk-averse and risk-neutral strategies are studied and compared to show the effects of DRCM implementation. The obtained results demonstrate the expected performance cost (EPC) of IPL is slowly raised while risk-in-cost (RIC) is significantly reduced due to model of risk related to uncertainties.     

Large scale production of nanoporous graphene sheets and their application in lithium ion battery

Nanoporous graphene sheets were generated through a simple thermal annealing procedure using composites of ferrocene nanoparticles and graphene oxide sheets as precursors in a large scale. The morphology, composition, and formation mechanism of the as-obtained nanoporous graphene sheets were studied complementarily with scanning electron microscopy, transmission electron microscopy, X-ray powder diffraction, and other spectroscopy techniques. We found that the density of nanopores on the graphene sheet was determined by the surface distribution of oxygen-containing groups on the original graphene oxide sheets. The coin cells using nanoporous graphene sheets as anode materials showed higher specific lithium ion storage capacity, better discharge/charge rate capability and higher cycling stability when compared to the coin cells with graphene or chemically reduced graphene sheets as anodes.     

Influence of modified fiber–MHSH hybrids on fire hazards,combustion dynamics,and mechanical properties of flame-retarded poly(butylene succinate) composites

Environmental problems caused by polymers and polymers have historically dominated both academic and industrial attention. Sustainable biodegradable wood-plastic composites (WPCs) as an optimum can solve the environmentally critical problems caused by petroleum-based polymers. However, they are flammable, prone to fire accidents, and often have a contradiction between mechanical performance and flame-retardant properties, which limits their range of applications. Here, we reported a flame-retarded poly(butylene succinate) (PBS) WPC prepared with modified natural fiber-magnesium hydroxide sulfate whisker (MHSH) hybrids and intumescent flame retardant s (IFRs). The mechanical performance, flame-retardant properties , thermal stability, and actual fire simulation parameters of composites were investigated. Owing to the unique composition characteristics of modified cassava dregs-MHSH hybrids, the mechanical properties (70P/23I/5C/2M, flexural strength was 39.2 ± 1.960/MPa, impact strength was 7.95 ± 0.3975/ [KJ/m²]), flame retardant properties (70P/23I/5C/2M, the limiting oxygen index value was 39.6%, UL-94 was V0) and thermal stability of WPC have been improved. Thereby, the balance between mechanical performance and flame retardant properties of biocomposites has been achieved in the practical engineering requirements. Furthermore, cone calorimeter data indicated that modified cassava dregs–MHSH hybrids played a role in improving the fire safety of composites. The total heat release, total smoke produce, toxic gas release, and total oxygen consumed of 70P/23I/5C/2M were lowered compared with those of 70P/25I/5C. Dynamics analysis indicated that the addition of modified cassava dregs–MHSH hybrids increased the activation energy of composites. Based on the experimental and analyses data, especially the morphological characterization of char residue analysis, it illustrated that modified cassava dregs–MHSH hybrids have a reinforcement and flame-retardant effect. The combusted residue of the incorporated modified cassava dregs–MHSH hybrids could support the three-dimensional charred layer formed by the combustion products of the IFR and the PBS. Thus, the more stable three-dimensional charred layer could not only effectively reduce thermal conductivity of composites but also hinder the propagation of heat into the interior substrate, thereby improving the flame-retardant properties of the WPC. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2020 , 137, 48490.