Strain analysis of moving objects using a Fourier transform grid method

There is no good method to measure the shape and the strain distributions of a structure changing with time. We have previously proposed the Fourier transform grid method (FTGM) to measure the three-dimensional shape and surface strain distributions of stationary objects by analysing the two-dimensional grating images recorded with two cameras. In the stereoscopic method, it is very important to determine the accurate geometric parameters of the camera system. In this paper, the positions and the directions of cameras are accurately determined using the FTGM applied to images of a reference object on which a two-dimensional grating is drawn. Applications for analysing shape and strain distributions of vibrating rubber plates and a moving human skin are shown.     

阳泉市煤矿采空区地质因素对公路的破坏

介绍了阳泉市煤矿采空区对公路建设所造成的危害，对其上覆岩层变形破坏的地质因素及其破坏机理作了分析，指出应该采取各种措施减少对公路的破坏。     

预应力钢-混凝土组合梁的应用与研究

回顾了预应力钢 混凝土组合梁国内外应用与研究历史 ,分析了现有规范及理论的不足 ,并指出了有待解决的问题。     

Stress distribution on [100] Si wafer mapped by novel I-V analysis of MOS tunneling diodes

The current-voltage (I-V) characteristics of metal-oxide-semiconductor tunneling diodes distributed over a 3-in Si wafer were analyzed to investigate the stress distribution on the wafer. Generally, the substrate injection saturation current (J/sub sat/) decreases as the gate injection leakage current (J/sub g/) increases, the latter being dominated by oxide thickness via a trap related mechanism. A universal curve to fit all analyzed data was found and it is suggested that devices with extremely high (low) J/sub sat/ at a given J/sub g/ should be located in areas of the silicon lattice with relatively high external compressive (tensile) stress because of the stress-induced bandgap variation effect. The mapped locations of the highly stressed devices on a 3-in [100] Si wafer correspond to the patterns of slips caused by thermal stress during rapid thermal processing, as described in previous reports.     

Electrical characterization of porous BaTiO3 using impedance spectroscopy in humid condition

The humidity response characteristics of La doped BaTiO₃ with different sintered densities and room temperature electrical conductivities were investigated using complex impedance measurement. The samples with low density and high resistivity showed the large and nearly linear sensitivity to the change of humidity. The impedance spectra of samples, when exposed to high humidity, can exhibit microstructure-related features, even though they do not give rise to a noticeable characteristic change when exposed to low humidity. The observed impedance patterns were dependent upon the density, and hence the oxidation kinetics of BaTiO₃.     

Temperature dependence of hydrogenated amorphous silicon thin-film transistors

The temperature dependence characteristics of hydrogenated amorphous silicon thin-film transistors were investigated. The results indicate that as the temperature was increased, the threshold voltage and the field-effect mobility were first increased, and then decreased, which may be controlled by different mechanisms at low and high temperatures. In addition, if the temperature was higher than 420 K, the Fermi level was promoted to the degenerate-like states, the current channel always existed due to the temperature effect, and the threshold voltage became negative.     

北京谱仪端盖簇射计数器工作气体的研究

为使北京谱仪端盖族射计数器更好地工作在自猝灭流光ＳＱＳ模式下，提高其能量分辨以及线性等指标，用Ａｒ，ＣＯ２，Ｌｓｏｂｕｔａｎｅ三元工作气体对探测器的工作性能进行了仔细研究，找出了一适合于主雇地数器的工作气体，此外，还研究了异丁的纯度对探测器性能的影响。     

Classification and prediction of the critical heat flux using fuzzy theory and artificial neural networks

A new method to predict the critical heat flux (CHF) is proposed, based on the fuzzy clustering and artificial neural network. The fuzzy clustering classifies the experimental CHF data into a few data clusters (data groups) according to the data characteristics. After classification of the experimental data, the characteristics of the resulting clusters are discussed with emphasis on the distribution of the experimental conditions and physical mechanism. The CHF data in each group are trained in an artificial neural network to predict the CHF. The artificial neural network adjusts the weight so as to minimize the prediction error within the corresponding cluster. Application of the proposed method to the KAIST CHF data bank shows good prediction capability of the CHF, better than other existing methods.