Prediction of two-phase flow patterns in upward inclined pipes via deep learning

The industrial process involving gas liquid flows is one of the most frequently encountered phenomena in the energy sectors. However, traditional methods are practically unable to reliably identify flow patterns if additional independent variables/parameters are to be considered rather than gas and liquid superficial velocities. In this paper, we reported an approach to predict flow pattern along upward inclined pipes (0–90°) via deep learning neural networks, using accessible parameters as inputs, namely, superficial velocities of individual phase and inclination angles. The developed approach is equipped with deep learning neural network for flow pattern identification by experimental datasets that were reported in the literature. The predictive model was further validated by comparing its performance with well-established flow regime forecasting methods based on conventional flow regime maps. Besides, the intensity of key features in flow pattern prediction was identified by the deep learning algorithm, which is difficult to be captured by commonly used correlation approache

Lagrangian actuator model for wind turbine wake aerodynamics

As a continuation of authors’ previous work, this work extends and hackles the numerical method for wind turbine wakes based on the vortex method, and proposes the Lagrangian actuator model (LAM) which is used for the representation of the wind turbine rotor under the Lagarangian framework. This paper provides two examples of the LAM, the Lagrangian actuator line (LAL) model and the Lagrangian actuator disc (LAD) model, and constructs matching numerical methods for wake predictions respectively. Those methods have high computation efficiency, and the results coincide with the wind tunnel test data well. Moreover, based on that, a vorticity description framework centered on vortex geometric structures is established to illustrate wind turbine wake phenomena and explore the wake evolution mechanism

Can physical activity counteract the negative effects of sedentary behavior on the physical and mental health of children and adolescents? A narrative review

BackgroundThe increase in sedentary behavior (SB) in children and adolescents is one of the major threats to global public health, and the relationship between physical activity (PA) and SB has always been a key topic.MethodsThe literature search was conducted through PubMed, Web of Science, CNKI, Wanfang, and Scopus, and 121 pieces of literature were included in this study after screening and evaluation.Results(1) SB caused by screen time such as mobile phones and TVs has varying degrees of negative impact on obesity, cardiovascular metabolism, skeletal muscle development, and cognitive, and psychological disorders in children and adolescents. (2) Regular physical activity could effectively prevent, offset, or improve the harm of SB to the physical and mental health of children and adolescents, mainly by reducing the incidence of obesity, and cardiovascular and metabolic risks, promoting skeletal muscle development, and improving cognitive function and mental health. (3) The mechanism of physical activity to prevent or ameliorate the harm of SB was relatively complex, mainly involving the inhibition or activation of neurobiomolecules, the improvement of blood and cell metabolic factors, and the enhancement of brain functional connectivity.ConclusionsChildren and adolescents should avoid excessive SB, and through a variety of moderate to vigorous physical activity (MVPA) to replace or intermittent SB, which could effectively prevent or improve the harm of SB to physical and mental health

Research status and hotspots of social frailty in older adults: a bibliometric analysis from 2003 to 2022

BackgroundSocial Frailty is a significant public health concern affecting the elderly, particularly with the global population aging rapidly. Older adults with social frailty are at significantly higher risk of adverse outcomes such as disability, cognitive impairment, depression, and even death. In recent years, there have been more and more studies on social frailty, but no bibliometrics has been used to analyze and understand the general situation in this field. Therefore, by using CiteSpace, VOSviewer, and Bilioshiny software programs, this study aims to analyze the general situation of the research on social frailties of the older adults and determine the research trends and hot spots.MethodsA bibliometric analysis was conducted by searching relevant literature on the social frailty of the older adults from 2003 to 2022 in the Web of Science core database, using visualization software to map publication volume, country and author cooperation networks, keyword co-occurrences, and word emergence.ResultsWe analyzed 415 articles from 2003 to 2022. Brazil has the highest number of articles in the field of social frailty of the older adults, and the United States has the highest number of cooperative publications. Andrew MK, from Canada, is the most published and co-cited author, with primary research interests in geriatric assessment, epidemiology, and public health. “Social Vulnerability,” “Health,” “Frailty,” “Mortality,” and “Older Adult” are among the research hotspots in this field. “Dementia,” “Alzheimer’s disease,” “Population,” and “Covid-19” are emerging research trends in social frailty among the older adults.ConclusionThis scientometric study maps the research hotspots and trends for the past 20 years in social frailty among the older adults. Our findings will enable researchers to better understand trends in this field and find suitable directions and partners for future research

Safety analysis of Railway Transportation of Dangerous goods

In the past decade, the demand for dangerous goods (DG) that can be used forindustrial, farming, mining, manufacturing, and pharmaceutical products has surgedwith the rapid development of industrialization. Almost 55,000 billion tonnekilometersof Dangerous Goods (DG) are transported annually by the railroad,accounting for approximately 51% of the total DG traffic volume in Europe. However,the increase in DG rail traffic has led to double the number of accidents involving DGin the last decade. Therefore, due to the increase in the volume of DG shipment andits impact on the environment, the safety of transporting DG has become more of aconcern to the public. The thesis analyzes the current situation of DG railroad transportation in Europe,including the shipment volume and accident/release rate. Fault tree analysismethodology was used to identify and assess the events contributing to DG involvedrelease accidents. Then lastly, recommendations based on the probability analysiswere proposed for improving DG rail transportation safety. The main result fromthis study is that more than half of the DG is transported by railway, and the DGtransported in Europe are mainly flammable liquids and compressed/liquefied gases,which are mainly transported by tank wagons. Due to the increase in the traffic volumeof DG transported since 2007, the trend of DG involved accidents in EU countriesbetween 2011 and 2020 presents an overall increasing trend. The same trend can alsobe observed in the tank wagon derailment/ collision-caused release rate at the sameperiod