Grey Forecast Model with Aging Fractional Accumulation and Its Properties

A novel aging fractional accumulation operator is proposed. The aging accumulation operator can dynamically update the accumulation weight of data and flexibly change the forecast trend by adjusting the aging parameter. In addition, a new aging accumulated grey model is obtained by using the aging accumulation operator to improve the traditional grey model. In the analysis of four examples, the existing grey accumulation operator and prediction method are compared. The results show that the proposed aging accumulation operator and aging accumulation grey model have excellent performance.

Could Historical Mortality Data Predict Mortality Due to Unexpected Events?

Research efforts focused on developing a better understanding of the evolution of mortality over time are considered to be of significant interest—not just to the demographers. Mortality can be expressed with different parameters through multiparametric prediction models. Based on the Beta Gompertz generalized Makeham (BGGM) distribution, this study aims to evaluate and map four of such parameters for 22 countries of the European Union, over the period 1960–2045. The BGGM probabilistic distribution is a multidimensional model, which can predict using the corresponding probabilistic distribution with the following parameters: infant mortality (parameter θ), population aging (parameter ξ), and individual and population mortality due to unexpected exogenous factors/events (parameters κ and λ, respectively). This work focuses on the random risk factor (λ) that can affect the entire population, regardless of age and gender, with increasing mortality depicting developments and trends, both temporally (past–present–future) and spatially (22 countries). Moreover, this study could help policymakers in the field of health provide solutions in terms of mortality. Mathematical models like BGGM can be used to achieve and highlight probable cyclical repetitions of sudden events (such as Covid-19) in different time series for different geographical areas. GIS context is used to map the spatial patterns of this estimated parameter as well as these variations during the examined period for both men and women.

Electrochemical Model-Based Aging Characterization of Lithium-Ion Battery Cell in Electrified Vehicles

Lithium-ion battery cycle- and calendar-life remain to be one of the greatest uncertainties for the advanced energy storage systems. Accurate characterization of battery aging has been crucial for battery state-of-health (SOH) estimation and the remaining useful life (RUL) prediction. The formation-and-growth of the solid-electrolyte interphase (SEI) has been widely recognized as one of the most prominent battery degradation mechanisms. It consumes the cyclable lithium within the cell and ultimately leads to the capacity fade which cannot be measured directly onboard. This study evaluates the multi-scale multi-physics battery models and their respective aging mechanisms as well as the corresponding characterization metrics. Then the reduced order single particle model (SPM) is selected in this study, given its parametric dependence on both electrochemical and physical parameters as well as its compatibility to the available measurements in vehicle for aging characterization. nLi, the total moles of cyclable lithium within the cell, is identified as a valid aging parameter that can effectively characterize the capacity fade through the interpretation of experimental aging data. This study also investigates into the potentially optimal testing profile and the sufficient amount of data required for the accurate aging characterization. Then the method of brute force nearest neighbor search (NNS) is applied to derive the long-term evolution trend of the aging parameter nLi, which can serve as a key benchmark for validating the in-vehicle implementable algorithms for battery state-of-health (SOH) estimation and as an important foundation for predicting the remaining useful life (RUL) of battery.

Transverse Strain Aging Behaviour of Uncoated Thick Walled X70 UOE Microalloyed Steel Pipes

Transverse tensile samples were extracted from the centreline position of three different compositions of uncoated thick walled microalloyed X70 UOE pipe at a location 180° from the weld. Aging heat treatments of 5, 15, and 25 minutes and temperatures of 175, 215, and 255°C were applied. Tensile tests were conducted on both the original pipe and on pre-strained samples. Microstructural analysis was undertaken using optical microscopy and scanning electron microscopy (SEM). The effects of a combined time and temperature aging parameter, pre-strain, microstructure and tensile work hardening behaviour on the pipe yield stress and yield to tensile strength ratio, is presented.