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  • Open Access

    ARTICLE

    Experimental Study on Mechanical Properties Degradation of TP110TS Tube Steel in High H2S Corrosive Environment

    Deli Gao1, Zengxin Zhao2

    CMC-Computers, Materials & Continua, Vol.26, No.2, pp. 157-166, 2011, DOI:10.3970/cmc.2011.026.157

    Abstract The research on casing corrosion in sour environment by a synergism of sweet corrosion and H2S corrosion has become the basis of casing selection and casing string safety evaluation with more and more sour reservoirs containing high H2S concentration being developed. It is essential to scientifically utilize casing service ability and reasonably control production rate of gas well to achieve the effective and safe developing of gas resources during the safety period of casing service with a precise casing life prediction. Scanning electron microscopy and tensile testing were applied to investigate the corrosion of TP110TS tube More >

  • Open Access

    ARTICLE

    A Fully Coupled Poroelastic Reactive-Transport Model of Cartilage

    Lihai Zhang*, Bruce S. Gardiner*, David W. Smith*, Peter Pivonka*, Alan Grodzinsky

    Molecular & Cellular Biomechanics, Vol.5, No.2, pp. 133-154, 2008, DOI:10.3970/mcb.2008.005.133

    Abstract Cartilage maintains its integrity in a hostile mechanical environment. This task is made more difficult because cartilage has no blood supply, and so nutrients and growth factors need to be transported greater distances than normal to reach cells several millimetres from the cartilage surface. The chondrocytes embedded within the extracellular matrix (ECM) are essential for maintaining the mechanical integrity of the ECM, through a balance of degradation and synthesis of collagen and proteoglycans. A chondrocyte senses various chemical and mechanical signals in its local microenvironment, responding by appropriate adaption of the local ECM. Clearly a… More >

  • Open Access

    ARTICLE

    Thermal Cycling Degradation of T650 Carbon Fiber/PT-30 Cyanate Ester Composite

    Huanchun Chen1, Kunigal Shivakumar1

    CMC-Computers, Materials & Continua, Vol.8, No.1, pp. 33-42, 2008, DOI:10.3970/cmc.2008.008.033

    Abstract Thermal cycling degradation effect on tensile and flexural properties of Cytec T650 carbon/Lonza Primaset PT-30 cyanate ester composite rods used for gas turbine engine brush seals was evaluated. The composite rods were thermal cycled in air from room temperature to 315°C for 100, 200, 400, 600 and 800 cycles. Each thermal cycle is a one hour period with 28 minutes hold at peak temperature and a high heating/cooling rate of 73°C/min. The composite withstood the first 100 thermal cycles with less than 10% property change. After that, tensile strength and fracture strain as well as More >

  • Open Access

    ARTICLE

    Modeling of Degraded Composite Beam Due to Moisture Absorption For Wave Based Detection.

    Shamsh Tabrez, Mira Mitra, S. Gopalakrishnan1

    CMES-Computer Modeling in Engineering & Sciences, Vol.22, No.1, pp. 77-90, 2007, DOI:10.3970/cmes.2007.022.077

    Abstract In this paper, wave propagation is studied in degraded composite beam due to moisture absorption. The obtained wave responses are then used for diagnosis of the degraded zone. Moisture absorption causes an irreversible hygrothermal deterioration of the material. The change in temperature and moisture absorption changes the mechanical properties. Thus this affects the structure in dimensional stability as well as material degradation due to reduction in mechanical properties. Here, the composite beam is modeled as Timoshenko beam using wavelet based spectral finite element (WSFE) method. The WSFE technique is especially tailored for simulation of wave More >

  • Open Access

    ARTICLE

    Neural Network Mapping of Corrosion Induced Chemical Elements Degradation in Aircraft Aluminum

    Ramana M. Pidaparti1,2, Evan J. Neblett2

    CMC-Computers, Materials & Continua, Vol.5, No.1, pp. 1-10, 2007, DOI:10.3970/cmc.2007.005.001

    Abstract A neural network (NN) model is developed for the analysis and prediction of the mapping between degradation of chemical elements and electrochemical parameters during the corrosion process. The input parameters to the neural network model are alloy composition, electrochemical parameters, and corrosion time. The output parameters are the degradation of chemical elements in AA 2024-T3 material. The NN is trained with the data obtained from Energy Dispersive X-ray Spectrometry (EDS) on corroded specimens. A very good performance of the neural network is achieved after training and validation with the experimental data. After validating the NN More >

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