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Full-Text Articles in Materials Science and Engineering
Assessment Of Material State For Predicting The Durability Of Composites, Vamsee Vadlamudi, Muthu Ram Prabhu Elenchezhian, Partha Pratim Das, Rassel Raihan, Kenneth Reifsnider
Assessment Of Material State For Predicting The Durability Of Composites, Vamsee Vadlamudi, Muthu Ram Prabhu Elenchezhian, Partha Pratim Das, Rassel Raihan, Kenneth Reifsnider
Institute of Predictive Performance Methodologies (IPPM-UTARI)
The long term behavior of composites have been extensively studied for the last four decades. Given the heterogeneity of these materials, the damage accumulation mechanisms lead to superior fatigue performance of composites compared to metals. However, due to the ‘sudden death’ behavior controlled by defect coupling, the precursor to fracture plane development of these materials, the challenge remains on how to assess the real-time material state and predict when it becomes critical? In the recent past, broadband dielectric spectroscopy (BbDS) has been used successfully to assess the material state and predict the material state change (triggered by defect coupling) for …
Unsupervised Learning Methods For Identification Of Defects In Heterogeneous Materials, Muthu Ram Prabhu Elenchezhian, Vamsee Vadlamudi, Rassel Raihan, Kenneth Reifsnider
Unsupervised Learning Methods For Identification Of Defects In Heterogeneous Materials, Muthu Ram Prabhu Elenchezhian, Vamsee Vadlamudi, Rassel Raihan, Kenneth Reifsnider
Institute of Predictive Performance Methodologies (IPPM-UTARI)
The complexity of composite materials due to the nature of their numerous laminated layers, stacking sequences, type of fibers, resin, and other external factors has challenged the world of structural health monitoring (SHM) and non-destructive inspection (NDI). Post-processing of these SHM and NDI methods has been mostly a manual time-consuming process, with human inspection causing errors associated with the bias decision made by NDI inspectors. Recent advances also call for Cure On The Fly (COTF), by integrating NDI with advanced technologies and analysis techniques such as Artificial Intelligence (AI) and Machine Learning (ML) for on-line real-time predictions of a defect, …
Performance Enhancement And Prediction Of Composite Materials With Embedded Electrospun Piezoelectric Sensors, Rahman Jani Mazed, Muthu Ram Prabhu Elenchezhian, Vamsee Vadlamudi, Md Riaz Uddin Ahmed, Rassel Raihan, Kenneth Reifsnider
Performance Enhancement And Prediction Of Composite Materials With Embedded Electrospun Piezoelectric Sensors, Rahman Jani Mazed, Muthu Ram Prabhu Elenchezhian, Vamsee Vadlamudi, Md Riaz Uddin Ahmed, Rassel Raihan, Kenneth Reifsnider
Institute of Predictive Performance Methodologies (IPPM-UTARI)
In today’s world, continuous fiber reinforced composite materials are extensively used in the aerospace, automotive and other structural industries. Since the applications of such fibers demand for a high safety rating, it is of utmost importance for engineers who design such materials to analyze its safety. When cracks are developed in such materials, the mechanical, electrical, and thermal properties also get altered as a function of the cracks. Previous studies have shown that changes in electrical properties can be directly correlated with the development of cracks in the material which can then be used to predict the remaining life of …