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  • Open Access


    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 propagation. It involves Daubechies scaling… More >

  • Open Access


    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 flexural modulus were gradually reduced.… More >

  • Open Access


    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 model, simulations were carried out… More >

  • Open Access


    A Correlation Coefficient Approach for Evaluation of Stiffness Degradation of Beams Under Moving Load

    Thanh Q. Nguyen1,2, Thao T. D. Nguyen3, H. Nguyen-Xuan4,5,*, Nhi K. Ngo1,2

    CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 27-53, 2019, DOI:10.32604/cmc.2019.07756

    Abstract This paper presents a new approach using correlation and cross-correlation coefficients to evaluate the stiffness degradation of beams under moving load. The theoretical study of identifying defects by vibration methods showed that the traditional methods derived from the vibration measurement data have not met the needs of the actual issues. We show that the correlation coefficients allow us to evaluate the degree and the effectiveness of the defects on beams. At the same time, the cross-correlation model is the basis for determining the relative position of defects. The results of this study are experimentally conducted to confirm the relationship between… More >

  • Open Access


    Biodegradation of Medicinal Plants Waste in an Anaerobic Digestion Reactor for Biogas Production

    Kabir Fardad1, Bahman Najafi1, Sina Faizollahzadeh Ardabili1, Amir Mosavi2,3, Shahaboddin Shamshirband,4,5,*, Timon Rabczuk2

    CMC-Computers, Materials & Continua, Vol.55, No.3, pp. 381-392, 2018, DOI: 10.3970/cmc.2018.01803

    Abstract Glycyrrhiza glabra, Mint, Cuminum cyminum, Lavender and Arctium medicinal are considered as edible plants with therapeutic properties and as medicinal plants in Iran. After extraction process of medicinal plants, residual wastes are not suitable for animal feed and are considered as waste and as an environmental threat. At present there is no proper management of waste of these plants and they are burned or buried. The present study discusses the possibility of biogas production from Glycyrrhiza Glabra Waste (GGW), Mentha Waste (MW), Cuminum Cyminum Waste (CCW), Lavender Waste (LW) and Arctium Waste (AW). 250 g of these plants with TS… More >

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