The State of the Art of Data Science and Engineering in Structural Health Monitoring

Structural health monitoring (SHM) is a multi-discipline field that involves the automatic sensing of structural loads and response by means of a large number of sensors and instruments, followed by a diagnosis of the structural health based on the collected data. Because an SHM system implemented into a structure automatically senses, evaluates, and warns about structural conditions in real time, massive data are a significant feature of SHM. The techniques related to massive data are referred to as data science and engineering, and include acquisition techniques, transition techniques, management techniques, and processing and mining algorithms for massive data. This paper provides a brief review of the state of the art of data science and engineering in SHM as investigated by these authors, and covers the compressive sampling-based data-acquisition algorithm, the anomaly data diagnosis approach using a deep learning algorithm, crack identification approaches using computer vision techniques, and condition assessment approaches for bridges using machine learning algorithms. Future trends are discussed in the conclusion.

Strength analysis of molten salt tanks for concentrating solar power plants

Promoting the development of concentrating solar power(CSP)is critical to achieve carbon peaking and carbon neutrality.Molten salt tanks are important thermal energy storage components in CSP systems.In this study,the cold and hot tanks of a 100 MW CSP plant in China were used as modeling prototypes.The materials and geometric models were determined based on related specifications and engineering experience.Mechanical characteristics of the tanks under steady condition,including the deformation,stress distribution,and stress concentration,were simulated and calculated.Furthermore,the strength of the tank walls was evaluated.The findings can be used as a reference for designing the molten salt storage tank and reducing the risk during the operation.

Dietary ferulic acid and vanillic acid on inflammation,gut barrier function and growth performance in lipopolysaccharide-challenged piglets

Ferulic acid(FA)and vanillic acid(VA)are considered as major phenolic metabolites of cyanidin 3-glucoside,a polyphenol that widely exists in plants that possess a protective effect against oxidative stress and inflammation in our previous study.This study aimed to investigate the effect of FA and VA on inflammation,gut barrier function,and growth performance in a weaned piglet model challenged with lipopolysaccharide(LPS).Thirty-six piglets(PIC 337×C48,28 d of age)were randomly allocated into 3 treatments with 6 replicate pens(2 piglets per pen).They were fed with a basal diet or a diet containing 4,000 mg/kg of FA or VA.Dietary supplementation of VA significantly increased average daily gain(ADG)(P<0.05).Both FA and VA decreased serum levels of thiobarbituric acid reactive substances(TBARS),interlukin(IL)-1β,IL-2,IL-6,and tumor necrosis factor(TNF)-α(P<0.05),and enhanced the expression of tight junction protein oclaudin(P<0.05).Analysis of gut microbiota indicated that both FA and VA increased the Firmicutes/Bacteroidetes ratio alongside reducing the relative abundance of the Prevotellaceae family including Prevotella 9 and Prevotella 2 genera,but enriched the Lachoiraceaea family including the Lachnospiraceae FCS020 group(P<0.05).Moreover,VA reduced the relative abundance of Prevotella 7 and Prevotella 1 but enriched Lachnospira,Eubacterium eligens group,and Eubacterium xylanophilum group(P<0.05),while FA showed a limited effect on these genera.The results demonstrated that both VA and FA could alleviate inflammation and oxidative stress,but only VA has a significant positive effect on the growth performance of LPS-challenged piglets potentially through modulating gut microbiota.