Pengya Fang's research while affiliated with Zhengzhou University and other places

... S12-S13) of the charge/discharge curves, which is largely associated with the ohmic resistance, appears to be the most significant source of overpotential growth. 52,53 The volumetric loading of conductive additive most directly plays a role in lowering ohmic and contact resistances, since it provides physical electronically conductive pathways throughout the electrode, lowering the electron resistance throughout the film. To observe the sources of internal cell resistance, electrochemical impedance spectroscopy (EIS) was conducted on cells discharged to a potential of 1.55 V Vs Li/Li + after formation cycling, with resulting Nyquist plots shown in Fig. S14. ...

... One of the most contributing factors behind the adoption of methanol is its less expensive nature which has been useful in producing sustainable compositions of ethanol fuel (Li et al., 2022). It can also result in cost savings for consumers and the automotive industry, resulting in better demand and supply balance performance. ...

... Data-driven models are appealing because they employ historical data and data-driven techniques, such as supervised or deep learning (DL). These models prove to be very efficient and robust with parameter uncertainty [21][22][23]. Data-driven methods have been commonly utilized in automotive applications for battery pack state-ofhealth evaluation and cycle life prediction [24]. Aykol et al. introduced novel frameworks for integrating physics-based and machine learning (ML) models in order to improve the accuracy of battery lifetime predictions, while considering the unique characteristics of battery data and the specific requirements of end-user applications [25]. ...

... In practical engineering, obtaining the exact probability distribution data of uncertain covariates is relatively difficult in comparison to obtaining the unknown magnitude or bounds of said covariates. In the fatigue problem, certain variables have been observed to follow random distributions based on numerous experimental studies, while other variables such as the equivalent force amplitude cannot be replicated in a laboratory setting and must be gathered through strain monitors to obtain measured data [6][7][8]. Therefore, this paper defines variables with significant data dispersion that cannot be represented by a probability density function as interval variables. ...

... Importantly, the central composite design (CCD) and the second-order approximation polynomial are used to model the flight load response. Fang (2020) [45] proposed a response surface method that is based on uniform design (UD) experiments and weighted least squares (WLSs) to improve the accuracy of the limit state function during a reliability analysis. Each approximate optimal point will be used for a new sample set to improve the accuracy of the response surface. ...

... To accurately quantify the impact of uncertain factors and take advantage of MDO simultaneously, the Reliability-based MDO (RBMDO) has received extensive attention and has become a research hotspot (Wang and Xiong, 2019;Zhang et al., 2020a, b;Li et al., 2019;Zhu et al., 2021a, b;Fu et al., 2020;Wang et al., 2018b;Fang and Wen, 2019;Gholinezhad and Torabi, 2022;Meng et al., 2021cMeng et al., , 2022Yao et al., 2011). If one RBMDO problem is solved directly, the reliability analysis, the multidisciplinary analysis, and the design optimization will be nested and coupled during the entire iteration process (As shown in Figure 3). ...