Flexural wave bandgap properties of phononic crystal beams with interval parameters

Uncertainties are unavoidable in practical engineering,and phononic crystals are no exception.In this paper,the uncertainties are treated as the interval parameters,and an interval phononic crystal beam model is established.A perturbation-based interval finite element method(P-IFEM)and an affine-based interval finite element method(A-IFEM)are proposed to study the dynamic response of this interval phononic crystal beam,based on which an interval vibration transmission analysis can be easily implemented and the safe bandgap can be defined.Finally,two numerical examples are investigated to demonstrate the effectiveness and accuracy of the P-IFEM and A-IFEM.Results show that the safe bandgap range may even decrease by 10%compared with the deterministic bandgap without considering the uncertainties.

Genome Characteristics and Evolution of Pseudorabies Virus Strains in Eastern China from 2017 to 2019

Since late 2011,outbreaks of pseudorabies virus(PRV)have occurred in southern China causing major economic losses to the pig industry.We previously reported that variant PRV forms and recombination in China could be the source of continued epidemics.Here,we analyzed samples from intensive pig farms in eastern China between 2017 and 2019,and sequenced the main glycoproteins(gB,gC,gD,and gE)to study the evolution characteristics of PRV.Based on the gC gene,we found that PRV variants belong to clade 2 and detected a founder effect during by the PRV epidemic.In addition,we detected inter-and intra-clade recombination;in particular,inter-clade recombination in the gB genes of strains FJ-ZXF and FJ-W2,which were recombinant with clade 1 strains.We also found specific amino-acid changes and positively selected sites,possibly associated with functional changes.This analysis of the emergence of PRV in China illustrates the need for continuous monitoring and the development of vaccines against specific variants of PRV.

Modeling and parameter identification of linear time-varying systems based on adaptive chirplet transform under random excitation

In this paper,a time–frequency algorithm based on adaptive chirplet transform for parameter modeling and identification of Linear Time-Varying(LTV)systems under random excitation is presented.It is assumed that the solution of responses of LTV structures is expressed as the sum of multicomponent Linear Frequency Modulated(LFM)signals in a short-time.Then the measured acceleration response is used to perform the adaptive chirplet transform,in which an integral algorithm is employed to reconstruct the velocity and displacement responses.The vibration differential equation with time-varying coefficients is transformed into a simple linear equation.Furthermore,for systems under random excitation,the input–output relation based on correlation function is also derived to estimate the parameters including physicals parameters and instantaneous modal parameters.The full procedure of the method is presented and validated by using simulated responses.The results show that the presented method is accurate and robust for various LTV systems under random excitation.