Estimation of Aeroelastic Parameters of Bridge Decks Using Neural Networks

A new method of estimating flutter derivatives using artificial neural networks is proposed. Unlike other computational fluid dynamics based numerical analyses, the proposed method estimates flutter derivatives utilizing previously measured experimental data. One of the advantages of the neural networks approach is that they can approximate a function of many dimensions. An efficient method has been developed to quantify the geometry of deck sections for neural network input. The output of the neural network is flutter derivatives. The flutter derivatives estimation network, which has been trained by the proposed methodology, is tested both for training sets and novel testing sets. The network shows reasonable performance for the novel sets, as well as outstanding performance for the training sets. Two variations of the proposed network are also presented, along with their estimation capability. The paper shows the potential of applying neural networks to wind force approximations.     

Computer modeling of the continuous annealing furnace

A computer program to calculate the strip temperature heated in the continuous annealing furnace was developed, using the zone method for radiative heat transfer analysis with the measured gas temperature in the furnace. Using theF _E Operator, the present study considered the effects of soot and transient species, in addition to the H₂O−CO₂ gas mixture on the gas radiative heat transfer. The predicted strip temperature distribution forF _E=1.05 represented well the measured data. The maximum difference in the heat flux transfered to the strip from the combustion gas forF _E=1.0 (without soot and transient species gas radiation) and 1.05 (with soot and transient species gas radiation) was about 15%. The present study also investigated the effects of line speed and thickness variations on the strip temperature, establishing the bases for the on-line computer model.     

Feature selection techniques and comparative studies for large-scale manufacturing processes

In order to efficiently and effectively control an overall process in the process industry, a few important parameters should be identified from high-dimensional, non-linear, and correlated data. Feature selection techniques can be employed to extract a subset of process parameters relevant to product quality. The performance of these techniques depends on the precision of the prediction model formulated to quantify the relationship between the process parameters and the quality characteristics. Although the neural network-based partial least squares (NNPLS) method has been proven to be effective in prediction models for the aforementioned industrial process data, feature selection techniques appropriate for NNPLS models have yet to appear. Here, several techniques for scoring the relevance of process parameters to product quality are proposed and validated by applying three datasets. These experiments show that the proposed techniques can discriminate relevant process parameters from irrelevant ones.     

Effects of potential and heat treatment on phase transition of alumina dielectric layer

The characteristics and growth behaviors of alumina dielectric layer formed by anodic oxidation were investigated. The aluminum oxide layer anodized at 400 V was predominantly amorphous alumina, but at the applied potentials more than 500 V, amorphous and crystalline γ-alumina were existed in anodic oxide layer and the ratio of γ-alumina increased with the increasing applied potential. During the heat treatment at 600^°C or higher temperature, amorphous alumina layer was transformed into the crystalline γ-alumina. The phase transition of anodic amorphous alumina into crystalline depends on anodic applied potentials and heat-treatment temperatures.     

Structural properties of 0.65Pb(Mg1/3Nb2/3)O3–0.35PbTiO3 relaxor ferroelectric thin films on SrRuO3 conducting oxides

Coating of 0.65Pb(Mg_1/3Nb_2/3)O₃–0.35PbTiO₃ (PMN–PT) relaxor ferroelectrics by a sol–gel method is followed by growth of epitaxial SrRuO₃ (SRO) metallic oxide electrodes on SrTiO₃ (STO) single-crystal substrate by pulsed laser deposition. High-quality PMN–PT films on SRO with preferred growth orientation were successfully fabricated by controlling the operation parameters. Structural properties of relaxor ferroelectric PMN–PT thin films on SRO/STO substrates have been studied by X-ray diffraction (XRD), transmission electron microscopy (TEM) and atomic force microscopy (AFM). In-plane and out-of-plane alignments of the heterostructure are confirmed and the structural twinning of the materials are also revealed.     

Strength and fracture toughness of nano and micron-silica particles bidispersed epoxy composites: evaluated by fragility parameter

In this study, we discuss the composition effect of 240 nm and 1.56 μm-silica particles on strength and fracture toughness by examining two parameters, fragility and glass transition temperature, that were derived from the thermo-viscoelasticity measurements. Experimental results showed that the composites had a lower fragility with higher strength and fracture toughness as the content of nanoparticles was increased regardless of glass transition temperature. The improvement in mechanical properties from adding nanoparticles was definitely explained by the fragility represented the heterogeneity in polymer matrix, and this was related to the interaction between particles and matrix. The fragility was found to be an effective parameter for evaluating strength and fracture toughness of epoxy composite containing a bidispersion of nano and micron-silica particles.     

基于复数权值神经元的数字逻辑最稳健设计

复数权值神经元由于引入了多阈值逻辑而具有更强的性能,文中根据其数学模型,结合二进神经元稳健性的概念,提出了基于该神经元的稳健性定义.并结合定义,实现了基于单个神经元的基本数字逻辑以及异或运算的最稳健设计方案,从而证明了该稳健神经元实现任意数字逻辑的有效性和可行性,说明了其强大的处理能力.     

Polysaccharide‐based artificial extracellular matrix: Preparation and characterization of three‐dimensional,macroporous chitosan,and heparin composite scaffold

Scaffold‐guided tissue engineering based on synthetic and natural occurring polymers has gained many interests in recent year. In this study, the development of a chitosan‐heparin artificial extracellular matrix (AECM) is reported. Three‐dimensional, macroporous composite AECMs composed of heparin (Hep) and chitosan (Chito) were prepared by an interpolyelectrolyte complex/lyophilization method. The Chito‐Hep composite AECMs were, respectively, crosslinked with glutaraldehyde, as well as cocrosslinked with N,N‐(3‐dimethylaminopropyl)‐N′‐ethyl carbodiimide (EDC/NHS) and N‐hydroxysuccinimide (NHS). The crosslinking reactions were examined by FT‐IR analysis. In physiological buffer solution (PBS), the EDC/NHS‐crosslinked Chito‐Hep composite AECM showed a relative lower water retention ratio than its glutaraldehyde‐crosslinked counterparts. The EDC/NHS‐crosslinked Chito‐Hep composite AECMs showed excellent biocompatibility, according to the results of the in vitro cytotoxic test. This result suggested that the EDC/NHS‐crosslinked Chito‐Hep composite AECMs might be a potential biomaterial for scaffold‐guided tissue engineering applications. © 2008 Wiley Periodicals, Inc. J Appl Polym Sci, 2008     

Effects of tube rupture modeling and the parameters on the analysis of multiple steam generator tube rupture event progression in APR1400

A multiple steam generator tube rupture (MSGTR) event in APR1400 has been investigated using the best estimate thermal hydraulic system code, MARS1.4. The effects of the parameters such as the number of ruptured tubes, rupture location, affected steam generator on the analysis of the MSGTR event in APR1400 are examined. In particular, tube rupture modeling methods, single tube modeling (STM) and double tube modeling (DTM), are compared. The APR1400 is found to have the capability of allowing more than 30 min to operators for the MSGTR event of five tubes. The effects of rupture location on the MSSV lift time is not significant in the case of STM, but the MSSV lift time for tube-top rupture is found to be 25.3% larger than that for rupture at the hot-leg side tube sheet in the case of DTM. The MSSV lift time for the cases that both steam generators are affected (4C5x, 4C23x) are found to be larger than that of the single steam generator cases (4A5x, 4B5x) due to a bifurcation of the primary leak flow. The discharge coefficient of Cd is found to affect the MSSV lift time only for a smaller value of 0.5. It is found that the most dominant parameter governing the MSSV lift time is the leak flow rate. Whether any modeling method is used, it gives the similar MSSV lift time if the leak flow rate is close, except in the case where both steam generators are affected. Therefore, the system performance and the MSSV lift time of the APR1400 are strongly dependent on the break flow model used in the best estimate system code.