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Although traditional fault diagnosis methods are proficient in extracting signal features, their diagnostic interpretability remains challenging. Consequently, this article proposes a conditionally interpretable generative adversarial network (C-InGAN) model for the interpretable feature fault diagnosis of bearings. Initially, the vibration signal is denoised and transformed into a frequency domain signal. The model consists of the two primary networks, each employing a convolutional layer and an attention module, generator (G) and discriminator (D), respectively. Latent code was incorporated into G to constrain the generated samples, and a discriminant layer was added to D to identify the interpretable features. During training, the two networks were alternately trained, and the feature mapping relationship of the pre-normalized encoder was learned by maximizing the information from the latent code and the discriminative result. The encoding that represents specific features in the vibration signal was extracted from the random noise. Ultimately, after completing adversarial learning, G is capable of generating a simulated signal of the specified feature, and D can assess the interpretable features in the vibration signal. The effectiveness of the model is validated through three typical experimental cases. This method effectively separates the discrete and continuous feature coding in the signal. [ABSTRACT FROM AUTHOR]

The influence of calcium carbonate (CaCO3) with different polymorphs (calcite and aragonite) and morphologies (granular and rod-like) on mechanical and crystallization properties of polypropylene (PP) was investigated. Meanwhile, these CaCO3 fillers coated with oleic acid were added in different contents to PP. The results indicate that the tensile strength, flexural strength, modulus, and crystallization property of the filler-treated samples are improved, but the impact strength decreased. The crystallinity of the composites is higher than that of neat PP. Moreover, in the rod shape filler-treated sample, in both whisker species, the mechanical properties of composites are superior to the particles filled. Differential scanning calorimetry, X-ray diffraction, and mechanical tests display that calcite whisker-reinforced composite has higher crystallization enthalpy, melting enthalpy, degree of crystallinity, and mechanical properties than aragonite whiskers and calcite particles filled composites.

As the power generation mode with the lowest carbon emissions, wind power generation plays an indispensable role in achieving the goal of carbon neutralization. To optimize the wind power density (WPD), forecasting is crucial to improve wind power utilization and power system stability. However, because near-surface wind is characterized by notable randomness, diversity, intermittence, and uncontrollability, accurately forecasting the WPD on wind farms remains a challenging task. In this study, we attempted to improve the WPD forecast in the middle- and high-latitude regions of China (wind energy resources are abundant there) by selecting the relatively optimal planetary boundary layer (PBL) scheme, as the PBL processes exert notable effects on the near-surface wind field directly. Based on a whole month in the summer (July 2021), seven PBL schemes were compared quantitatively by using the Weather Research and Forecasting (WRF) model for a total of 70 runs (for each run, the forecast period was 3 days). The results show that no PBL schemes could always show the best performance in forecasting all variables, and the forecast accuracy showed a notable dependence on the evolution of the weather systems. Among the seven PBL schemes, the Medium-Range Forecast (MRF) scheme showed the overall best performance in forecasting the 100 m wind speed, sea level pressure, and 2 m temperature, which ensured that it had the highest forecast skill for the WPD in the middle- and high-latitude regions of China. Further analyses indicate that the background conditions were also well forecasted by the MRF scheme (ranked first or second). This was a crucial reason why the WPD forecast was the best for the MRF scheme. [ABSTRACT FROM AUTHOR]

With the wide deployment of charging piles and the development of vehicle-to-grid technology, electric vehicles (EVs) will have more opportunities to participate in the operation and scheduling of electric power system through the EV aggregator (EVA), an intermediate agent between the power grid and EV users. Quantitatively evaluating the response capability (RC) of EVA, i.e., charging and discharging power ranges, is of fundamental importance for its trading with the operator of power grid. This article proposes a user-aware method to obtain a more accurate range of multitimescale RC considering the response willingness of EV users. First, a temporal RC evaluation model of a single EV considering charge-discharge state and state of charge (SOC) is established. Second, based on the user psychology model, which reflects the relationship between users' responsivity and incentive price, a multitimescale RC evaluation model of EVA considering users' willingness is built. The day-ahead RC of EVA is evaluated by the state prediction data of EVs. According to the control strategy which considers response time and SOC indicators comprehensively, the RC evaluation is updated intraday. Finally, using the statistical data from the EU MERGE project, the effectiveness of the proposed evaluation model is verified, and the impact of incentive price and scheduling time scale on the RC of EVA are analyzed. The results indicate that the proposed model can effectively track the scheduling goals of the system and realize the dynamic update of the RC of EVA. [ABSTRACT FROM AUTHOR]

Aragonite whiskers (AWs) were treated with several fatty acid surfactants and silane coupling agent in order to determine the optimal modifier by using contact angle measurements. The results revealed that the AWs modified by fatty acids showed more remarkable increase in the contact angle than by silane, suggesting the former were preferentially applied in modifying AWs. While the samples coated with fatty acids exhibited hydrophobicity with contact angles ranging from 104.08° to 137.87° with increasing of carbon chain length. Therefore, the highest contact angle of AWs treated by oleic acid was discussed in detail as an example, which was characterized by field emission scanning electron microscope (FESEM), transmission electron microscopy (TEM), thermo-gravimetry analyses (TGA), X-ray photoelectron spectroscopy (XPS) and Fourier transform infrared (FTIR). FESEM and TEM results showed a thin layer coated on the modified sample surface. Both the results of TGA and XPS confirmed organic groups existed in the sample of AWs treated by oleic acid. FTIR demonstrated that calcium dioleate was formed in the modification process. Further, modification mechanism was proposed based on the obtained results. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Wind energy is a type of renewable and clean energy which has attracted more and more attention all over the world. The Northwest China is a region with the most abundant wind energy not only in China, but also in the whole world. To achieve the goal of carbon neutralization, there is an urgent need to make full use of wind energy in Northwest China and to improve the efficiency of wind power generation systems in this region. As forecast accuracy of the near-surface wind is crucial to wind-generated electricity efficiency, improving the near-surface wind forecast is of great importance. This study conducted the first test to incorporate the subgrid surface drag into the near-surface wind forecast under the complex terrain conditions over Northwest China by using two TopoWind models added by newer versions of the Weather Research and Forecasting (WRF) model. Based on three groups (each group had 28 runs) of forecasts (i.e., Control run, Test 01 and Test 02) started at 12:00 UTC of each day (ran for 48 h) during the period of 1–28 October 2020, it was shown that, overall, both TopoWind models could improve the near-surface wind speed forecasts under the complex terrain conditions over Northwest China, particularly for reducing the errors associated with the forecast of the wind-speed's magnitude. In addition to wind forecast, the forecasts of sea level pressure and 2-m temperature were also improved. Different geographical features (wind-farm stations located south of the mountain tended to have more accurate forecast) and weather systems were found to be crucial to forecast accuracy. Good forecasts tended to appear when the simulation domain was mainly controlled by the high-pressure systems with the upper-level jet far from it. [ABSTRACT FROM AUTHOR]

The abnormal 2020 Meiyu season caused the worst disasters over the Yangtze River Valley in recent decades. Of these, the Sichuan Basin (SCB) and its surrounding regions were one of the most severely affected areas. Disastrous weather frequently occurs in these regions, with a large proportion of it closely related to the southwest vortices (SWVs). In order to further the understanding of SWV generation, this study investigated the formation mechanisms of a quasi-stationary SWV (by using two sets of vorticity budgets), which caused torrential rainfall (resulting in flash floods in Sichuan and Chongqing), lightning activities (causing tripping incidents of transmission lines in Sichuan) and strong winds (leading to shutting down of wind turbines in Hubei). Results showed that the SWV was generated in a favorable background environment, during which an upper-tropospheric divergence and a middle-tropospheric warm advection appeared over the SCB. Trajectory analyses and vorticity budget showed that the air particles that came from the lower troposphere of the regions south of the Tibetan Plateau dominated the SWV formation. These air particles experienced notable ascending during which an increase in their cyclonic vorticity occurred mainly due to convergence-related stretching, whereas, tilting mainly decelerated this increase. The air particles sourced from the areas within the key region of the SWV and areas northeast of the key region were the second dominant factor for the vortex formation. Overall, for the air particles that formed the SWV, their most rapid changes of vorticity and divergence appeared in the period 24 h before SWV formation, implying that this was the critical period for the SWV generation. [ABSTRACT FROM AUTHOR]