基于GA-BP的汽车风振噪声声品质预测模型

目前对于汽车风振噪声的优化研究主要以声压级（Sound pressure level，SPL）作为单一评价指标，既不能全面反映噪声的物理属性，也无法考虑人耳对噪声的主观认知过程。为准确评价风振噪声，引入声品质，运用大涡模拟（Large eddy simulation，LES）对风振噪声进行数值仿真，根据实车道路试验判断仿真的准确性；对仿真结果进行声品质客观评价与主观评价，综合声品质客观评价参数与声品质主观评价试验结果建立BP神经网络预测模型；利用遗传算法（Genetic algorithm，GA），进一步对BP神经网络的结构参数进行优化，建立GA-BP声品质预测模型。研究结果表明，GA-BP声品质预测模型在训练速度和预测精度上都优于BP神经网络预测模型。预测模型基于声品质主客观评价结果，其预测值可以代替传统的声压级评价指标，为风振噪声提供更为准确合理的评价。     

Surface treatment of titanium dioxide nanopowder using rotary electrode dielectric barrier discharge reactor

Titanium dioxide (TiO2) nanopowder (P-25;Degussa AG) was treated using dielectric barrier discharge (DBD) in a rotary electrode DBD (RE-DBD) reactor.Its electrical and optical characteristics were investigated during RE-DBD generation.The treated TiO2 nanopowder properties and structures were analyzed using x-ray diffraction (XRD) and Fourier-transform infrared spectroscopy (FTIR).After RE-DBD treatment,XRD measurements indicated that the anatase peak theta positions shifted from 25.3° to 25.1°,which can be attributed to the substitution of new functional groups in the TiO2 lattice.The FTIR results show that hydroxyl groups (OH) at 3400 cm-1 increased considerably.The mechanism used to modify the TiO2 nanopowder surface by air DBD treatment was confirmed from optical emission spectrum measurements.Reactive species,such as OH radical,ozone and atomic oxygen can play key roles in hydroxyl formation on the TiO2 nanopowder surface.     

基于PBFT区块链技术的电网企业仓储系统

提出了一种基于实用拜占庭容错(PBFT)算法的区块链技术,首先对传统的实用拜占庭容错算法原理进行了阐述,该传统算法包含前期、需求、预准备、准备、确认、答复6个阶段,但传统算法具有实时性差、缺乏惩罚机制、带宽高的缺点。针对出现的这些问题,又对传统算法进行了改进,具体涉及记账节点、共识过程以及视图切换过程。通过测试进一步证明了该改进算法的实用性,并将该算法应用于电网企业中,构建的虚拟仓库实现了联储联备,降低了库存资金的耗费,并且提高了电网企业库存管理的效率。     

Boosting discharge capability of α-Ni(OH)2 by cobalt doping based on robust spherical structure

α-Ni(OH)₂ is a promising candidate of the currently commercialized β-Ni(OH)₂ due to its higher theoretical discharge capacity in alkaline solution; however, its instability and poor conductivity plague the practical application. Herein, we propose α-Ni(OH)₂ with Co doping and spherical structure to strengthen the stability and enhance the conductivity and use it as the cathode for nickel-metal hydride batteries. Studies show that proper Co doping promotes the electrochemical reaction between the active materials and the electrolyte due to the spherical α-Ni(OH)₂ with enlarged interlayer distance and abundant hole channels, as well as high conductivity of Co, therefore, the obtained spherical α-Ni(OH)₂ with 7 mol% Co doping delivers significantly improved discharge capability, which is 384.6 mAh g^?1 at 70 mA g^?1 (0.2 C), increased by 54.3 mAh g^?1 compared with pure α-Ni(OH)₂, and at a high current of 5 C, it still gives 269.4 mAh g^?1, in contrast 218.5 mA g^?1 for the pure α-Ni(OH)₂. Besides, the cycling stability of the α-Ni(OH)₂ with 7 mol% Co doping maintains 340 cycles at a capacity retention of 80% (1C), which is extended 110 cycles in contrast to the pure α-Ni(OH)₂. These results provide the underpinning platform of α-Ni(OH)₂ for battery applications with high discharge ability and cycle life.     

Reproductive tract disease in Irish grazing dairy cows: Retrospective observational study examining its association with reproductive performance and accuracy of 2 diagnostic tests

The detection of reproductive tract disease (RTD) 3 wk postpartum is important because of its effect on subsequent reproductive outcomes. Numerous methods for the diagnosis of RTD are described, some of which are more practical and instantaneous in terms of diagnosis. Two of these methods involve identification of purulent vaginal discharge (PVD) and evidence of ultrasonographic uterine changes indicative of endometritis (UE). The objectives of our retrospective observational study were (1) to assess the association of PVD or UE score at the prebreeding examination (PBE) with the hazard of pregnancy within the subsequent breeding season; (2) to determine the test sensitivity (Se) and specificity (Sp) at the point of sampling of both tests using a Bayesian latent class model; and (3) to determine the effect of varying positivity thresholds on test accuracy. To achieve these objectives, we analyzed an initial data set of 5,049 PBE from 2,460 spring-calved cows in 8 herds between 2014 and 2018. Each PBE was conducted once between 25 and 86 d in milk. At each PBE, vaginal discharge was obtained with a Metricheck device (Simcro) whereas uterine contents were assessed using transrectal ultrasonography. Purulent vaginal discharge was scored on a scale of 0 to 3 depending on discharge character, and UE was scored on a scale of 0 to 4 depending on the presence and consistency of intraluminal fluid. Cows with scores of ≥2 in either test had received treatment. Fertility data were available from 4,756 PBE after data exclusion. The association between PVD or UE score at the PBE and subsequent hazard of pregnancy was analyzed using a Cox proportional hazards model. Cows with a PVD score of 2 or 3 were less likely to conceive than cows with a PVD score 0 [score 2 hazard ratio (HR) = 0.74; 95% confidence interval (CI): 0.59–0.94; score 3 HR = 0.65; 95% CI: 0.51–0.84]. Cows with a UE score of 1, 2, 3, or 4 were less likely to conceive than cows with a UE score of 0 (score 1 HR = 0.82; 95% CI: 0.73–0.93; score 2 HR = 0.79; 95% CI: 0.62–1.00; score 3 HR = 0.43; 95% CI: 0.43–0.90; score 4 HR = 0.39; 95% CI: 0.26–0.58). To determine the Se and Sp of PVD or UE score for diagnosis of RTD at the time of PBE, a Bayesian latent class model was fitted on 2,460 individual cow PBE. Flat priors were used for the Se and Sp of UE, whereas informative priors were used for PVD Se (mode = 65%, 5th percentile = 45%) and Sp (mode = 90%, 5th percentile = 80%) and RTD prevalence (mode = 20%, 5th percentile = 10%). Posterior estimates (median and 95% Bayesian probability intervals; BPI) were obtained using ‘rjags' (R Studio). The optimal test thresholds (PVD and UE score ≥1) were selected by assessing the effect of different thresholds on test estimates and using a misclassification cost analysis. Based on these, median (95% BPI) Se for PVD and UE score ≥1 were 44% (29–60%) and 67% (33–100%), respectively. Median Sp for PVD and UE score ≥1 were 90% (86–93%) and 91% (86–93%), respectively. Higher scores in both tests were associated with impaired fertility, and UE scoring with a threshold of ≥1 had the highest test Se and Sp estimates although test Se was conditional on days in milk when the PBE occurred.     

Microstructural refinement and mechanical response of Al2O3–ZrO2 eutectics fabricated by a novel pulse discharge plasma assisted melting method

In the present work, microstructural refinement and mechanical response of Al₂O₃–ZrO₂ eutectics fabricated by a pulse discharge plasma assisted melting (PDPAM) method were investigated. The solidified microstructure evolves from polygonal eutectic colonies into irregular cellular colonies with increasing the superheating temperature of the melt from 1820 °C to 1900 °C. The average eutectic spacing inside the colonies decreases from 1.80 ± 0.10 μm to 0.25 ± 0.06 μm, and the coarse inter-colonial structure is refined, which is attributed to the increase in undercooling temperature. High-temperature microstructural stability of Al₂O₃–ZrO₂ eutectics is improved significantly as contrasted with the as-sintered ceramics. Besides, the load dependence of Vickers hardness for Al₂O₃–ZrO₂ eutectics is investigated.     

Parameter characterization of HTPEMFC using numerical simulation and genetic algorithms

This paper develops a novel approach to the parameterisation of high temperature exchange membrane fuel cells (HTPEMFC) with limited and non-invasive measurements. The proposed method allows an effective identification of electrochemical parameters for three-dimensional fuel cell models by combining computational simulation tools and genetic algorithms. To avoid each evaluation undertaken by the optimisation method involving a complete computational simulation of the 3D model, a strategy has been designed that, thanks to an iterative process, makes it possible to decouple the fluid dynamic resolution from the electrochemistry one.Two electrochemical models have been incorporated into these tools to describe the behaviour of the catalyst layer, Butler-Volmer and spherical aggregate. For each one, a case study has been carried out to validate the results by comparing them with empirical data in the first model and with data generated by numerical simulation in the second. Results show that, from a set of measured operating conditions, it is possible to identify a unique set of electrochemical parameters that fits the 3D model to the target polarisation curve. The extension of this framework can be used to systematically estimate any model parameter in order to reduce the uncertainty in 3D simulation predictions.