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    An Artificial Neural Network Model to Predict Material Characteristics From the Results of Miniature Disk Bending Tests 

    Source: Journal of Pressure Vessel Technology:;2015:;volume( 137 ):;issue: 001:;page 11404
    Author(s): Ghosh, A. K.; Verma, Vishnu; Behera, G.
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: The inverse problem of evaluating mechanical properties of material from the observed values of load and deflection of a miniature disk bending specimen is discussed in this paper. It involves analysis of large amplitude, ...
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    Reliability Assessment of Failure Assessment Diagram Based Fitness for Service Procedure Including the Effect of Bias in Modeling 

    Source: Journal of Pressure Vessel Technology:;2017:;volume( 139 ):;issue: 005:;page 51602
    Author(s): Rastogi, Rohit; Ghosh, Siddhartha; Ghosh, A. K.; Vaze, K. K.
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: This paper presents the estimation of the reliability levels associated with a cracked pipe found acceptable as per the failure assessment diagram (FAD) based acceptance criteria of ASME Section XI, Appendix H. This ...
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