A scaling limit for the length of the longest cycle in a sparse random digraph

We discuss the length of the longest directed cycle in the sparse random digraph , constant. We show that for large there exists a function such that a.s. The function where is a polynomial in . We are only able to explicitly give the values , although we could in principle compute any .     

Solvent‐free ring‐opening polymerization of lactones with hydrogen‐bonding bisurea catalyst

Development of effective organocatalysts for the living ring‐opening polymerization (ROP) of lactones is highly desired for the preparation of biocompatible and biodegradable polyesters with controlled microstructures and physical properties. Herein, a new class of hydrogen‐bond donating bisurea catalysts is reported for the ROP of lactones under solvent‐free conditions. ROP of lactones mediated by the bisurea/7‐methyl‐1,5,7‐triazabicyclo[4.4.0]dec‐5‐ene (MTBD) catalyst exhibits a living/controlled manner, affording the polymers and copolymers with the well‐defined structure, predictable molecular weight, narrow molecular weight distribution, and high selectivity for monomer at low catalyst loadings at ambient temperature. The possible mechanism of bisurea/MTBD‐catalyzed ROP of lactones is proposed, in which the bisurea activates the carbonyl group of lactones while MTBD facilitates the nucleophilic attack of the initiating/propagating alcohol by hydrogen bonding. Moreover, the poly(ε‐caprolactone‐co‐δ‐valerolactone) [P(CL‐co‐VL)] random copolymers with various compositions were synthesized using the bisurea/MTBD catalyst. The measurements of thermal properties and crystalline structure demonstrate that the CL and VL units are cocrystallized in the crystalline phase of P(CL‐co‐VL) copolymers. © 2018 Wiley Periodicals, Inc. J. Polym. Sci., Part A: Polym. Chem. 2019 , 57, 90–100     

Existential monadic second order logic of undirected graphs: The Le Bars conjecture is false

In 2001, J.-M. Le Bars disproved the zero-one law (that says that every sentence from a certain logic is either true asymptotically almost surely (a.a.s.), or false a.a.s.) for existential monadic second order sentences (EMSO) on undirected graphs. He proved that there exists an EMSO sentence ? such that $\mathsf{P}(G_n??)$ does not converge as $n\to \infty$ (here, the probability distribution is uniform over the set of all graphs on the labeled set of vertices $\{1,\dots ,n\}$). In the same paper, he conjectured that, for EMSO sentences with 2 first order variables, the zero-one law holds. In this paper, we disprove this conjecture.     

次线性期望下的一般中心极限定理

受Peng-中心极限定理的启发,本文主要应用G-正态分布的概念,放宽Peng-中心极限定理的条件,在次线性期望下得到形式更为一般的中心极限定理.首先,将均值条件E[X_n]=ε[X_n]=0放宽为|E[X_n]|+|ε[X_n]|=O(1/n);其次,应用随机变量截断的方法,放宽随机变量的2阶矩与2+δ阶矩条件;最后,将该定理的Peng-独立性条件进行放宽,得到卷积独立随机变量的中心极限定理.     

Stochastic sensitivity analysis of coupled acoustic-structural systems under non-stationary random excitations

This paper presents a new sensitivity analysis method for coupled acoustic–structural systems subjected to non-stationary random excitations. The integral of the response power spectrum density (PSD) of the coupled system is taken as the objective function. The thickness of each structural element is used as a design variable. A time-domain algorithm integrating the pseudo excitation method (PEM), direct differentiation method (DDM) and high precision direct (HPD) integration method is proposed for the sensitivity analysis of the objective function with respect to design variables. Firstly, the PEM is adopted to transform the sensitivity analysis under non-stationary random excitations into the sensitivity analysis under pseudo transient excitations. Then, the sensitivity analysis equation of the coupled system under pseudo transient excitations is derived based on the DDM. Moreover, the HPD integration method is used to efficiently solve the sensitivity analysis equation under pseudo transient excitations in a reduced-order modal space. Numerical examples are presented to demonstrate the validity of the proposed method.     

Dynamic and buckling analysis of polymer hybrid composite beam with variable thickness

This work deals with a study of the dynamic and buckling analysis of polymer hybrid composite(PHC) beam. The beam has variable thickness and is reinforced by carbon nanotubes(CNTs) and nanoclay(NC) simultaneously. The governing equations are derived based on the first shear deformation theory(FSDT). A three-phase HalpinTsai approach is used to predict the mechanical properties of the PHC. We focus our attention on the effect of the simultaneous addition of NC and CNT on the vibration and buckling analysis of the PHC beam with variable thickness. Also a comparison study is done on the sensation of three impressive parameters including CNT, NC weight fractions, and the shape factor of fillers on the mechanical properties of PHC beams,as well as fundamental frequencies of free vibrations and critical buckling load. The results show that the increase of shape factor value, NC, and CNT weight fractions leads to considerable reinforcement in mechanical properties as well as increase of the dimensionless fundamental frequency and buckling load. The variation of CNT weight fraction on elastic modulus is more sensitive rather than shear modulus but the effect of NC weight fraction on elastic and shear moduli is fairly the same. The shape factor values more than the medium level do not affect the mechanical properties.     

无轴承旋翼柔性梁载荷特性研究

应用Hamilton原理建立了双路传力的无轴承旋翼运动方程。采用均匀入流模型,基于直升机飞行平衡条件,建立了无轴承旋翼柔性梁载荷的计算模型,并通过算例验证了模型的精度。利用该模型,研究了全机重心位置、机身气动阻力以及平尾安装角对柔性梁载荷特性的影响,给出了各因素对柔性梁载荷的影响趋势,得出了降低柔性梁载荷的方法。数值结果表明:2cm左右重心位置的变化能够引起9%~11%的柔性梁载荷变化量,15%气动阻力的增加会导致约9%的柔性梁载荷的增大;2°平尾安装角的变化引起约10%柔性梁载荷的变化量,3°平尾安装角的变化引起约26%柔性梁载荷的变化。     

A new Monte Carlo model for predicting the mechanical properties of fiber yarns

Understanding the complicated failure mechanisms of hierarchical composites such as fiber yarns is essential for advanced materials design. In this study, we developed a new Monte Carlo model for predicting the mechanical properties of fiber yarns that includes statistical variation in fiber strength. Furthermore, a statistical shear load transfer law based on the shear lag analysis was derived and implemented to simulate the interactions between adjacent fibers and provide a more accurate tensile stress distribution along the overlap distance. Simulations on two types of yarns, made from different raw materials and based on distinct processing approaches, predict yarn strength values that compare favorably with experimental measurements. Furthermore, the model identified very distinct dominant failure mechanisms for the two materials, providing important insights into design features that can improve yarn strength.