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To rapidly analyze the dynamic characteristics of a compliant stroke amplification mechanism (CSAM) with completely distributed compliance, an analytical model based on the dynamic stiffness matrix with consideration of the damping effect is proposed. The natural frequency of the CSAM is optimized without attenuation of the amplification ratio based on this model. The optimized CSAM exhibits an approximately 112% higher natural frequency than the original mechanism along the main motion direction. The optimization result is verified through finite element simulation, with less than a 7% difference being observed. Moreover, the effects of frequency on the amplification ratio and input stiffness of the optimized CSAM are also discussed. The structural resonance is defined as the failure criterion of the optimized CSAM, and the sensitivity of the failure probability to manufacturing errors at different positions is analyzed. The findings show that the failure probability of the CSAM is more sensitive to parameters associated with the coordinates of the output stage and vertex.

Even though a great number of methods have been developed for time-variant reliability analysis (TRA), crude Monte Carlo simulation (MCS) is still widely used alone or combined with other methods to enhance the efficiency and accuracy of TRA. Multilevel Monte Carlo (MLMC) is introduced to TRA herein in order to reduce the computational complexity of MCS. MLMC first discretizes the time interval of interest by a geometric sequence of different timesteps. The finer grid is associated with smaller discretization error but larger computational cost. Accounting for the computational complexity of each level and the contribution that each level makes to the time-variant failure probability, the allocation of computational resource is then optimized in order to achieve a satisfying estimation of failure probability at the minimal computational cost. MLMC retains the robustness of crude MCS with respect to nonlinearity and dimensions of the time-variant performance function. Two benchmark examples are adopted to validate the effectiveness of the proposed MLMC. The results show that achieving the same accuracy level of results, the proposed method saves considerably computational cost relative to crude MCS.

Importance sampling methods are extensively used in time-independent reliability analysis. However, the kind of methods is barely studied in the field of time-variant reliability analysis. This article presents an importance sampling method for time-variant reliability analysis. It increases the probability of sampling failure trajectories of a time-variant performance function. To develop the method, the instantaneous performance function at a predefined time instant is regarded as a time-independent one. A time-independent importance sampling is first implemented on the instantaneous performance function in order to obtain instantaneous samples of stochastic processes and random variables. Then, conditional trajectories of stochastic processes are generated on the condition of instantaneous samples achieved above, which utilizes the correlationship among instantaneous uncertainties at different time instants associated with stochastic processes. Subsequently, trajectories of the time-variant performance function are obtained. Validation results show that comparing with crude Monte Carlo simulation, the proposed method remarkably increases the probability of sampling failure trajectories. The efficiency and accuracy of the proposed method are demonstrated.

To improve the efficiency and accuracy of reliability assessment for structures with small failure probability and time-consuming simulation, a new structural reliability analysis method (RCA-PCK) is proposed, which combines PC-Kriging model and radial centralized adaptive sampling strategy. Firstly, the PC-Kriging model is constructed by improving the basis function of Kriging model with sparse polynomials. Then, the sampling region which contributes a great impact on the failure probability is constructed by combining the radial concentration and important sampling technology. Subsequently, the k-means++ clustering technology and learning function LIF are adopted to select new training samples from each subdomains in each iteration. To avoid the sampling distance in one subdomain or the distance between the new training samples in two subdomains being too small, we construct a screening mechanism to ensure that the selected new training samples are evenly distributed in the limit state. In addition, a new convergence criterion is derived based on the relative error estimation of failure probability. Four benchmark examples are given to illustrate the convergence process, accuracy and stability of the proposed method. Finally, the transmission error reliability analysis of thermal-elastic coupled gears is carried out to prove the applicability of the proposed method RCA-PCK to the structures with strong nonlinearity and time-consuming simulation.

Even though extensive efforts have been made, structural reliability analysis method with both efficiency and robustness is still infrequent in engineering especially when time-consuming numerical models are involved. To address the issue, this paper develops multi-ring-based important sampling (MRIS) and incorporates it into the Kriging-based reliability analysis method authors previously proposed. MRIS can uniformly fill the region of importance with an acceptable number of random points regardless of the number of most probable points and failure sub-domains of investigated structure. As MRIS does not need to evaluate Kriging model during sampling random points, its efficiency does not decrease with increasing the training points of Kriging model, which is a substantial advantage. Therefore, it is used as an optimization method to search for the best next point so as to adaptively increase the accuracy of Kriging model. Additionally, the failure probability predicted by Kriging model and its corresponding accuracy measure are roughly calculated with MRIS. Both of them are essential to judge whether Kriging model meets with a prescribed requirement. Four benchmark examples verify the accuracy, efficiency, and robustness of the proposed reliability analysis method.

With the development of production technology, the mechanical structure has become more and more complicated, which makes the simulation process of the corresponding computer model very time-consuming. As a result, the reliability analysis needs to consume huge time resources. To deal with this problem, an improved method, which balances the accuracy of failure probability and the efficiency of computation, is proposed. The novelty of the proposed method is the use of an efficient point selection strategy, the k-means algorithm, and the constraint of correlation among the training points. The k-means algorithm can divide the candidate points into a few groups. Therefore, we can update the Kriging model by selecting several sample points which have large contributions to improve the accuracy of failure probability in each iteration. Meanwhile, a constraint is applied to control the relative location among points of DoE to avoid redundant information. The efficiency and accuracy of the proposed method are verified through two numerical examples. Finally, a type of artillery coordination system as a representative of the complex mechanisms is mentioned. And the proposed method is applied to calculate the reliability of the position accuracy of the coordination process, which proves the significance of the proposed method in engineering practice.

System reliability analysis involving multiple failure modes is challenging when performance functions are associated with time-consuming codes. This paper aims to enhance the efficiency of system reliability analysis by reducing the number of evaluations of time-consuming models. To achieve that, an adaptive Kriging-based method is proposed. In order to develop the method, a quantificational error measure of Kriging models (i.e. surrogate models of performance functions associated with each failure mode) is first derived. The stepwise accuracy-improvement strategy (SAIS) is then modified to solve system reliability problems, and the modified SAIS is called SAIS-SYS. The method for system reliability analysis is finally developed based on the derived error measure and SAIS-SYS. In the proposed method, Kriging models, i.e. the surrogate models of original performance functions, are adaptively refreshed according to SAIS-SYS until the associated error measure is smaller than a prescribed threshold. After Kriging models meet with accuracy requirement, the system failure probability can be obtained through a random simulation method and no additional evaluations of original performance functions is needed. The accuracy, efficiency and robustness of the proposed method are validated by four examples.

The temperature dependence of initial transient current-voltage (I-V) characteristic of planar perovskite solar cell by one-step solution process is investigated. An S-shaped I-V characteristic emerges in response to low temperature and the photovoltaic parameters drop dramatically. This is mainly attributed to the increasing amount of negative charges accumulating in the TiO 2 /CH 3 NH 3 PbI 3 interface region and the reduced built-in field separating the photo-generated carriers in the absorber layer. The influence of negative charge accumulation can be represented by two extra diodes that are in series with a conventional solar cell circuit model at low temperature whereas it acts as a resistor with low resistivity above room temperature. These findings help to understand the charge transport mechanism in perovskite solar cells.

The uniform and compact n-type TiO 2 window layers were prepared by RF sputtering using a TiO 2 ceramic target. A high open circuit voltage of about 1.03 V with the efficiency of 13.23% can be obtained as compared to 0.92 V of solution based TiO 2 . Nearly 100% coverage of perovskite film on sputtered TiO 2 can be observed in the scanning electron microscopy images, obviously higher than 92% coverage on solution-based TiO 2 . The full coverage of perovskite and the proper band alignment between sputtered TiO 2 and spiro-OMeTAD are two reasons responsible for the high open circuit voltage. The effects of annealing, growth temperature, sputtering target and thickness on performance of solar cell are also discussed.

The surface texture with a long alignment was observed on the surface of CH3NH3PbI3−xClx films prepared using one-step solution deposition. We found that it appears only when hydroiodic acid with stabilizer H3PO2 is adopted to prepare CH3NH3I powder. However, even with this stabilizer, the surface texture of CH3NH3PbI3−xClx films can also be eliminated completely by sufficiently lateral diffusion before annealing, which can be achieved by high speed coating above 3000 rpm or drying for 30 min at room temperature. The later process results in a smooth surface with homogeneous grains and hence the improvement of photovoltaic performance.

Carbon films with the thicknesses varying from 10 to 600 nm in the architecture range of carbonaceous graphene to graphitic bonding were synthesized on Si wafer. The films were prepared by radio frequency plasma enhanced chemical vapor deposition under 300 °C without any catalyst and hydrogen-assistant ambient as well. The films found to be composed of microcrystalline graphene and graphite inclusions with a maximum graphene film size of 2 µm. Raman spectral characterization verified the bonding form of the graphene–graphitic films to be mostly sp2. In this work, the complicated transfer printing process for carbon/silicon (C/Si) devices and the quality degradation of the hybrid films were avoided by the direct deposition of the carbonaceous films on Si substrate. The current–voltage feature of the devices manifested that the devices possess an excellent rectifying behavior in dark and the characteristic of photovoltaic in the illumination (known as solar cells).

The time evolution of the current–voltage characteristic of planar heterojunction perovskite solar cell (PSC) is studied within an operating temperature range of 200–325 K. The photovoltaic (PV) performance of PSC is found to be influenced by five carrier transport pathways, which strongly depend on operating temperature and light illumination. At low temperature, a severe degradation of PV performance is presented but temporary. This is attributed to ion accumulation at the TiO2/CH3NH3PbI3 and hole transport material/CH3NH3PbI3 interfacial regions, as an origin of screening effect of built-in field, evidenced by the low external quantum efficiency (EQE). By light illumination at open-circuit, a steady PV performance will be reached and the stabilization time increases with decreasing temperature. The recovery of PV performance is attributed to ion diffusion in CH3NH3PbI3 layer in the absence of electric field. The EQE observations indicate that photogenerated carriers are separated and collected efficiently after a long time light illumination due to a reduction of the screening effect. At high temperature, because of the low ion density at interfacial regions, the PV performance shows a quick response to light. These findings may help understanding of the mechanism of temperature-dependent photogenerated carrier transport in the PSC.

Organic-inorganic halide perovskite semiconductors with the attractive physics properties, including strong photoluminescence (PL), huge oscillator strengths, and low nonradiative recombination losses, are ideal candidates for studying the light-matter interaction in nanostructures. Here, we demonstrate the coupling of the exciton state and the cavity mode in the lead halide perovskite microcavity system at room temperature. The Purcell effect in the coupling system is clearly observed by using angle-resolved photoluminescence spectra. Kinetic analysis based on time-resolved PL reveals that the spontaneous emission rate of the halide perovskite semiconductor is significantly enhanced at resonance of the exciton energy and the cavity mode. Our results provide the way for developing electrically driven organic polariton lasers, optical devices, and on-chip coherent quantum light sources.