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The tribological properties of the epoxy were significantly improved due to the tribological synergy of biomimetic F-CDs and sulfonated h-BN.

In the present study, a stochastic model of explosive ground motions applying the dimension-reduction method is proposed, and the reliability evaluation of a nonlinear frame structure under such excitations is realized by means of the probability density evolution method and an equivalent extreme-value-based reliability evaluation strategy. Firstly, the evolutionary power spectrum density function of the explosive ground motions is modeled by respectively identifying the normalized total energy distribution function and the frequency total energy distribution function on the basis of the measured motion records. In addition, an exponential model is constructed to forecast the seismic characteristics of the explosive ground motions based on the given distance to the explosive source and the charge quantity. Then, the representative samples of the explosive ground motions are simulated using the dimension-reduction method. The simulation results show that the generated acceleration samples have significant seismic characteristics of the explosive ground motions, and the accuracy is verified by comparing the second-order statistics with the sample set and the corresponding targets. Due to the fact that the probabilities of the representative samples simulated by the dimension-reduction method can compose a comprehensive probability set, it contributes to the refined dynamic response analysis and reliability evaluation of complex structures combining with the probability density evolution method. The accurate dynamic response analysis and reliability evaluation of a nonlinear frame structure illustrates the effectiveness of the proposed model and the dimension-reduction method for simulating the explosive ground motions. The numerical results demonstrate that the explosive ground motions have a substantial effect on the nonlinear behavior and the security of engineering structures.

A simple method was proposed to produce a flexible heat spreader with efficient thermal transportation performance.

Due to their excellent biocompatibility, outstanding mechanical properties, high strength-to-weight ratio, and good corrosion resistance, titanium (Ti) alloys are extensively used as implant materials in artificial joints. However, Ti alloys suffer from poor wear resistance, resulting in a considerably short lifetime. In this study, we demonstrate that the chemical self-assembly of novel two-dimensional (2D) diamond nanosheet coatings on Ti alloys combined with natural silk fibroin used as a novel lubricating fluid synergistically results in excellent friction and wear performance. Linear-reciprocating sliding tests verify that the coefficient of friction and the wear rate of the diamond nanosheet coating under silk fibroin lubrication are reduced by 54 and 98%, respectively, compared to those of the uncoated Ti alloy under water lubrication. The lubricating mechanism of the newly designed system was revealed by a detailed analysis of the involved microstructural and chemical changes. The outstanding tribological behavior was attributed to the establishment of artificial joint lubrication induced by the cross binding between the diamond nanosheets and silk fibroin. Additionally, excellent biocompatibility of the lubricating system was verified by cell viability, which altogether paves the way for the application of diamond coatings in artificial Ti joint implants.

For effective heat dissipation in portable electronics, there is a great demand for lightweight and flexible films with superior thermal transport properties. Despite extensive efforts, enhancing the intrinsic low thermal conductivity of polymers while simultaneously maintaining their flexibility is difficult to achieve due to the dilemma of quarrying appropriate filler loading. Herein, a cellulose nanofiber-based film with high in-plane thermal conductivity up to 72.53 W m

In the present paper, a framework of dimension-reduction modeling method is developed for a dual stochastic dynamic structural system of spectrum-compatible non-stationary stochastic ground motion ...

As industrialization and urbanization in China have significantly increased ecological problems such as environmental pollution and resource waste, it has become important to be able to comprehensively assess ecological wellbeing performance (EWP) when seeking high-quality human wellbeing and economic growth within specific ecological limits. Therefore, to explore the EWP spatial and temporal distribution characteristics, this paper established an evaluation index system that considers ecological economic efficiency and economic welfare efficiency from input and output perspectives. The EWPs in 30 Chinese provinces (autonomous regions, municipalities) from 2006 to 2017 were then measured using a two-stage super-efficiency slacks-based model (Super-SBM) and data envelopment analysis (DEA) window analysis method. It was found that: (1) the average EWP value in the Chinese provinces was relatively low at 0.698, with the highest EWP in Beijing, Hainan, and Shanghai and the lowest in Xinjiang, Ningxia, and Qinghai, (2) the average provincial EWP fluctuated from 2006 to 2017 with a &ldquo, decline-rise-decline-rise&rdquo, feature, (3) China&rsquo, s EWP value was spatially supported by the quadrangular &ldquo, Beijing-Shanghai-Hainan-Sichuan&rdquo, pole and continued to radiate to areas along these lines. These research findings provide theoretical insights and practical implications for regional ecological protection and human welfare improvements in China.

A framework of spectral representation-based dimension reduction for simulating multivariate non-stationary stochastic ground motion processes is addressed in this paper. By means of introducing random functions serving as constraints correlating with the orthogonal random variables in the original spectral representation scheme, the high-dimensional randomness degree involved in the multivariate stochastic processes can thus be reduced substantially. To this aim, three random function forms considering the combination of trigonometric functions and orthogonal polynomials are constructed for simulation purpose. Accordingly, the accurate representation of the original stochastic processes is realized with merely three elementary random variables, overcoming the principal challenge of numerous random variables faced by the Monte Carlo simulation method. Also, the consistency of the statistics between the sample functions of stochastic ground motions and strong motion records is established with update of the ground motion model parameters in stochastic simulation techniques. Numerical investigations involving the comparisons with the Monte Carlo simulation method and the validation based on the strong motion records are presented to demonstrate the superiority and effectiveness of the proposed methodology in practical engineering applications.

In this paper, two kinds of proper orthogonal decomposition (POD) representations for simulating the non-stationary stochastic vector processes are derived based on the basic theory of POD, namely the orthogonal-random-variables-based POD representation and the random-phase-angles-based POD representation. It is clarified that the random-phase-angles-based scheme is a special case of the orthogonal-random-variables-based scheme, and the differences between them are analyzed from the number of elementary random variables and the constraint conditions. It is found that the randomness degree (the number of elementary random variables) of the non-stationary stochastic vector processes could be greatly reduced by introducing some appropriate constraint conditions. To this end, the efficient dimension reduction simulation of the non-stationary stochastic vector processes with just two elementary random variables is realized through introducing more rigorous constraints on the orthogonal random variables in the orthogonal-random-variables-based scheme. Also, the complete probability information of the stochastic processes is fully emerged. Through the numerical analysis of the ground motion stochastic field simulation, it is obtained that the relative errors of the mean and standard deviation, evolutionary power spectrum and coherence function of the non-stationary ground motion acceleration vector process are all in good agreement with the corresponding target values, which shows that the proposed method is effective and accurate. Meanwhile, in order to further verify the applicability of this method in terms of engineering characteristics upon ground motion, according to the five classes of the typical soil sites divided in “Seismic ground motion parameters zonation map of China”, 920 strong motion records are selected for comparing and analyzing the response spectrum and the Fourier amplitude spectrum of ground motion acceleration, respectively. The research shows that the simulation results of the proposed method have good consistency with the strong motion records, which lays a solid foundation for this proposed method applied in engineering applications.

It is of great necessity to achieve the efficient and accurate representation of ground motion fields considering the spatial variation of which possess paramount importance to the seismic safety and reliability evaluation of lifeline systems. To circumvent the difficulties caused by the decomposition of cross power spectral density (PSD) matrix and the interpolation between discretized spatial points in the spectral representation method (SRM) for uni-dimensional multi-variate (1D-nV) stochastic vector process (regarded as discrete stochastic field), a wavenumber-frequency SRM (WSRM) for simulating multi-dimensional uni-variate (mD-1V) spatial-temporal stochastic field (regarded as continuous stochastic field) has been developed for years. In this paper, an updated WSRM (UWSRM), which can reduce the number of elementary random variables, is proposed for simulating the 2D-1V stochastic ground motion fields. Compared with the conventional WSRM (CWSRM) which belongs to the Monte Carlo simulation schemes, merely two elementary random variables are required to realize the precise modeling of ground motion fields. For the sake of facilitating the calculation, the UWSRM embedded in the Fast Fourier Transform (FFT) technique is applied to simulate the stochastic ground motion fields. Numerical results including the comparison of the accuracy and efficiency with the CWSRM verify the effectiveness of the UWSRM. Moreover, to illustrate the application prospect of the UWSRM, the refined random seismic response analysis of a buried pipeline network is implemented by combining with the probability density evolution method (PDEM). The analysis results preliminarily demonstrate the applicability of the UWSRM in lifeline systems.