The prediction of dynamic crack propagation in brittle materials is still an important issue in many engineering fields. The remeshing technique based on scaled boundary finite element method (SBFEM) is extended to predict the dynamic crack propagation in brittle materials. The structure is firstly divided into a number of superelements, only the boundaries of which need to be discretized with line elements. In the SBFEM formulation, the stiffness and mass matrices of the super-elements can be coupled seamlessly with standard finite elements, thus the advantages of versatility and flexibility of the FEM are well maintained. The transient response of the structure can be calculated directly in the time domain using a standard time-integration scheme. Then the dynamic stress intensity factor (DSIF) during crack propagation can be solved analytically due to the semi-analytical nature of SBFEM. Only the fine mesh discretization for the crack-tip super-element is needed to ensure the required accuracy for the determination of stress intensity factor (SIF). According to the predicted crack-tip position, a simple remeshing algorithm with the minimum mesh changes is suggested to simulate the dynamic crack propagation. Numerical examples indicate that the proposed method can be effectively used to deal with the dynamic crack propagation in a finite sized rectangular plate including a central crack. Comparison is made with the results available in the literature, which shows good agreement between each other.

The platform with bucket foundations can penetrate and migrate by underpressure/positive pressure technique caused by pumping water out/in the bucket. However, the construction process of bucket foundations cannot be clearly observed and effectively controlled due to the special nature of sea environment. By using an advanced simulation development tool of Multigen Creator, the visual construction simulation program for the platform with bucket foundations was developed to set up the virtual reality system with interaction control and observation in every view angle based on the secondary development technology of Vega platform. The application results show that the method is feasible and effective by simulating the whole construction process for the platform with four bucket foundations.

In this paper, an electrical resistance tomography (ERT) imaging method is used as a classifier, and then the Dempster-Shafer’s evidence theory with fuzzy clustering is integrated to improve the ERT image quality. The fuzzy clustering is applied to determining the key mass function, and dealing with the uncertain, incomplete and inconsistent measured imaging data in ERT. The proposed method was applied to images with the same investigated object under eight typical current drive patterns. Experiments were performed on a group of simulations using COMSOL Multiphysics tool and measurements with a piece of porcine lung and a pair of porcine kidneys as test materials. Compared with any single drive pattern, the proposed method can provide images with a spatial resolution of about 10% higher, while the time resolution was almost the same.

By the application of life cycle assessment (LCA) methodology, this paper estimates the environmental impacts of production and disposal of traction motors used in electric vehicles in China. The results show that the total energy use, the criteria emissions and the greenhouse gases (GHG) emissions of a traction motor production and disposal are about 2,899,MJ, 4.5,kg and 259.5,kg per motor, respectively. Among the regulated emissions, the SO _x emission ranks first by total mass, followed by CO, PM10, NO _x, PM2.5, and volatile organic compound (VOC). The motor material production stage accounts for most of the energy consumption and emissions, followed by the assembly stage and the end-of-life disposal stage. In this study, the environmental performance analysis is extended to the comparison between the use of secondary material and primary material for the material production stage. It is found that using 100% secondary material results in a 52.9% reduction in energy consumption, a 49.8% reduction in regulated emissions, and a 49.3% reduction in GHG emissions compared with the use of 100% primary material.

To investigate the seismic behavior of autoclaved aerated concrete load-bearing masonry wall (AACLMW), a piece of control block wall without constructional measures and five pieces of block walls with different constructional measures were tested under low reversed cyclic loading which imitated low to moderate earthquake force. The seismic behavior of AACLMW with different constructional measures in terms of failure mode, hysteretic curve, deformation capacity and displacement ductility was studied and compared with that without constructional measures. The experimental results indicate that the constructional measures comprising constructional columns and horizontal concrete strips are effective for improving the seismic behavior of AACLMW. The study in this paper can provide a reliable experimental basis for further analysis and engineering application of AACLMW in the future.

The influence of small organics on the adsorption characteristics of activated carbon produced from industrial pyrolytic tire char (APTC)for malachite green (MG) was investigated by a batch method. Phenol was chosen as the representative of small organics. The effects of phenol on adsorption equilibrium, kinetics and thermodynamics were studied systematically. The results indicate that APTC is a potential adsorbent for MG. The presence of phenol decreases the adsorption capacity of APTC for MG, but improves the rate of adsorption, while the adsorption characteristics, such as equilibrium, kinetics and thermodynamics are not affected by phenol. The adsorption equilibrium data follow Langmuir isotherm and the kinetic data are well described by the pseudo-second-order kinetic model. The adsorption process follows intra-particle diffusion model and the adsorption rate is determined by more than one process. Thermodynamic study shows that the adsorption is an endothermic and spontaneous physisorption process.

To establish a method for determining five saponins (notoginsenoside R1, ginsenoside Rg1, ginsenoside Re, ginsenoside Rb1 and ammonium glycyrrhizinate) in Glycyrrhizae, Notoginseng and Ginseng, the high performance liquid chromatography with diode array detector (HPLC-DAD) method was applied to an Inertsil ODS-SP column (4.6 mm×250 mm, 5 μm) with a mobile phase consisting of acetonitrile-0.05% phosphoric acid in a gradient elution manner. The flow rate was 1.0 mL/min. The column temperature was 30 °C and the detection wavelengths were 203 nm and 237 nm, respectively. The linear ranges were 0.700 0–7.000 0 μg for R₁ (r=1.000 0), 0.751 1–7.511 4 μg for Rg1 (r=1.000 0), 0.677 2–6.771 6 μg for Re (r=1.000 0), 0.733 9–7.339 1 μg for Rb1(r= 1.000 0), and 0.540 0–5.399 8 μg for ammonium glycyrrhizinate (r=0.999 9), respectively. In addition, their average recoveries were 100.28%, 105.83%, 104.09%, 99.36% and 98.54%, respectively. The relative standard deviations (RSDs) of precision, reproducibility and recovery were all less than 1.5%. The results indicate that the method is simple, accurate and reproducible so that it can be used for the simultaneous determination of the five saponins in Chinese patent medicines containing the three kinds of herbs.

PtNi/C nanoparticles with different atomic ratios of Pt/Ni were produced in pulse microwave assisted polyol process. Transmission electron microscopy (TEM) images show uniform morphology. X-ray diffraction( XRD) pattern plus energy dispersive X-ray (EDX) spectroscopy suggests pure composition. Cyclic voltammogram study reveals that PtNi/C nanoparticles synthesized in pulse microwave assisted polyol process have better catalytic activity for the oxidation of methanol to carbon dioxide than those synthesized in continuous process.

Aiming at the assembly accuracy of a large aircraft transport jig, the effect of component error and the error of work-piece surface on the work-piece position and orientation in the 3-2-1 fixturing scheme is studied with the object pose space description method. The error mapping model between the connecting part of the front frame rack and its support base is modeled using the homogeneous transformation matrix (HTM) method. The probabilistic error is simulated using the Monte Carlo method. The measurement experiment was conducted by the laser tracker to verify the effectiveness of the approach, and the approach has been successfully applied to the production of transport jig.

Monte Carlo method was adopted to calculate the meshing error considering the manufacture error and assembly error of the meshing point along the time-varying contact line for helical gear pair. The flexural-torsion-axis dynamic model coupled was established under the tooth friction force and solved by the perturbation method to compute real dynamic tooth load. The change laws of the friction force and friction torque were obtained in a meshing period. The transmission error formulation was analyzed to introduce meshing excitations. The maximum dynamic transmission error, the maximum meshing force and the maximum dynamic factor were calculated under different speeds, external loads and damping factors. The conclusions can provide theoretical basis for the gear design especially in tooth profile correction.

An error correction technique to achieve a 14-bit successive approximation register analog-to-digital converter (SAR ADC) is proposed. A tunable split capacitor is designed to eliminate the mismatches caused by parasitic capacitors. The linearity error of capacitor array caused by process mismatch is calibrated by a novel calibration capacitor array that can improve the sampling rate. The dual-comparator topology ensures both the speed and precision of the ADC. The simulation results show that the SAR ADC after calibration achieves 83.07 dB SNDR and 13.5 bit ENOB at 500 kilosamples/s.

In order to classify the alertness status, 19 channels of electroencephalogram (EEG) signals from 5 subjects were acquired during daytime nap. Ten different types of features (including time domain features, frequency domain features and nonlinear features) were extracted from EEG signals, and an improved self-organizing map (ISOM) neuron network was proposed, which successfully identify three different brain status of the subjects: awareness, drowsiness and sleep. Compared with traditional SOM, the experiment results show that the ISOM generates much better classification accuracy, reaching as high as 89.59%.

This paper considers a reentrant scheduling problem on parallel primary machines with a remote server machine, which is required to carry out the setup operation. In this problem, each job has three operations. The first and last operations are performed by the same primary machine, implying the reentrance, and the second operation is processed on the single server machine. The order of jobs is predetermined in our context. The challenge is to assign jobs to the primary machines to minimize the makespan. We develop a genetic algorithm (GA) to solve this problem. Based on a simple strategy of assigning jobs in batches on the parallel primary machines, the standardized random key vector representation is employed to split the jobs into batches. Comparisons among the proposed algorithm, the branch and bound (BB) algorithm and the heuristic algorithm, coordinated scheduling (CS), which is only one heuristic algorithm to solve this problem in the literature, are made on the benchmark data. The computational experiments show that the proposed genetic algorithm outperforms the heuristic CS and the maximum relative improvement rate in the makespan is 1.66%.