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Articles 1 - 7 of 7
Full-Text Articles in Engineering
Stiffness Degradation In Fatigue Life Of Composites Using Dielectric State Variables, Muthu Ram Prabhu Elenchezhian, Partha Pratim Das, Minhazur Rahman, Vamsee Vadlamudi, Rassel Raihan, Kenneth Reifsnider
Stiffness Degradation In Fatigue Life Of Composites Using Dielectric State Variables, Muthu Ram Prabhu Elenchezhian, Partha Pratim Das, Minhazur Rahman, Vamsee Vadlamudi, Rassel Raihan, Kenneth Reifsnider
Institute of Predictive Performance Methodologies (IPPM-UTARI)
Composite materials are widely used in aerospace and automotive structures for decades and over the years the community has gained a better understanding of the damage and failure modes of composites under fatigue. In this article, a dielectric characterization methodology for in-situ monitoring of composites under fatigue environments is proposed. A novel method of measuring the dielectric state variables in Broadband Dielectric Spectroscopy (BbDS) using Extremely Conductive Silver Epoxy Adhesive (ECSEA) paste is presented. These dielectric state variables serve to identify the precursor of the beginning of the end of life of the composite material under fatigue loading. The reliability …
The Effect Of Room-Temperature Aging On Enthalpy And Dielectric Property Of Carbon-Fiber/Epoxy Composite Prepreg And The Mechanical Property Of Manufactured Composite, Monjur Morshed Rabby, Minhazur Rahman, Partha Pratim Das, Muthu Ram Prabhu Elenchezhian, Relebohile George Qhobosheane, Vamsee Vadlamudi
The Effect Of Room-Temperature Aging On Enthalpy And Dielectric Property Of Carbon-Fiber/Epoxy Composite Prepreg And The Mechanical Property Of Manufactured Composite, Monjur Morshed Rabby, Minhazur Rahman, Partha Pratim Das, Muthu Ram Prabhu Elenchezhian, Relebohile George Qhobosheane, Vamsee Vadlamudi
Institute of Predictive Performance Methodologies (IPPM-UTARI)
Fiber-based reinforced plastics are widely used materials in different industries - e.g., Automotive, Aerospace, Defense- because of their various advantages. The most reliable raw materials for manufacturing fiber-based composites are pre-impregnated reinforcing fiber (prepreg). However, the limitation of using prepreg lies in its instability at room temperature. Prepregs have a specific out-life which sometimes makes the manufacturing process difficult. The objective of this study is to find out a way to investigate the room temperature aging effect on prepreg by analyzing the enthalpy and dielectric properties. In this study, differential scanning calorimetry (DSC) was used to measure the reaction enthalpy …
Artificial Intelligence In Real-Time Diagnostics And Prognostics Of Composite Materials And Its Uncertainties – A Review, Muthu Ram Prabhu Elenchezhian, Vamsee Vadlamudi, Rassel Raihan, Kenneth Reifsnider, Erick Reifsnider
Artificial Intelligence In Real-Time Diagnostics And Prognostics Of Composite Materials And Its Uncertainties – A Review, Muthu Ram Prabhu Elenchezhian, Vamsee Vadlamudi, Rassel Raihan, Kenneth Reifsnider, Erick Reifsnider
UTARI Researcher Publications
In the era of the 4th industrial revolution of big data, Artificial Intelligence (AI) is widely used in each and every field of composite materials which includes design and analysis, material storage, manufacturing, non-destructive testing (NDT), Structural Health Monitoring (SHM) and Prognostics of its Remaining Useful Life (RUL), Material State (MS) and damage modes. While these AI models are rapidly developed and integrated into the Industrial Internet of Things (IIoT) to keep track of the health of a composite material from its birth to death, these integrations remain uncertain for prognostics without the certainty of its previous material state. This …
Supporting Materials From The Program "Development Of A Physically-Based Creep Model Incorporating Eta Phase Evolution For Nickel Base Superalloys", N. R. Mohale, C. L. White, P. G. Sanders, W. W. Milligan, J. P. Shingledecker, P. A. Bridges
Supporting Materials From The Program "Development Of A Physically-Based Creep Model Incorporating Eta Phase Evolution For Nickel Base Superalloys", N. R. Mohale, C. L. White, P. G. Sanders, W. W. Milligan, J. P. Shingledecker, P. A. Bridges
Michigan Tech Research Data
This research was funded by the US Department of Energy, Fossil Energy Program, Grant Number DE-FE0027822, with Omer Bakshi as the Program Manager. The grant conditions required that all supporting data and materials would be made publicly-available. This public repository was created on May 13, 2021.
Effects Of Surface Characteristics On Mechanical And Dielectric Properties Of Adhesively Bonded Carbon Fiber Composites, Minhazur Rahman, Gayathri Kola, Monjur Morshed Rabby, Muthu Ram Prabhu Elenchezhian, Relebohile George Qhobosheane, Vamsee Vadlamudi
Effects Of Surface Characteristics On Mechanical And Dielectric Properties Of Adhesively Bonded Carbon Fiber Composites, Minhazur Rahman, Gayathri Kola, Monjur Morshed Rabby, Muthu Ram Prabhu Elenchezhian, Relebohile George Qhobosheane, Vamsee Vadlamudi
Institute of Predictive Performance Methodologies (IPPM-UTARI)
The rapid rise of fiber reinforced composite usage in aircraft, spacecraft and automobile industries made the proper comprehension of repair and joining of these materials a crucial aspect. Adhesive bonding is one of the most advantageous and desirable joining and repair technique for fiber reinforced composites. However, the heterogeneity of fiber reinforced composites and the complex interfacial nature of the adhesive bonds, makes most non-destructive evaluation and assessment techniques ineffective to assess the state of the bond. Different manufacturing and surface preparation techniques impart different surface characteristics to the adherends, hence proper understanding of the state of bonds is dependent …
Ordinary Differential Equations With Machine Learning For Prediction Of Smart Composite Fracture Toughness, Relebohile George Qhobosheane, Muthu Ram Prabhu Elenchezhian, Vamsee Vadlamudi, Kenneth Reifsnider, Rassel Raihan
Ordinary Differential Equations With Machine Learning For Prediction Of Smart Composite Fracture Toughness, Relebohile George Qhobosheane, Muthu Ram Prabhu Elenchezhian, Vamsee Vadlamudi, Kenneth Reifsnider, Rassel Raihan
Institute of Predictive Performance Methodologies (IPPM-UTARI)
This work in on the development of an ordinary differential equation (ODE) model coupled with statistical methods for the prediction of fracture toughness of a magnetostrictive, piezoelectric smart self-sensing Fiber Reinforced Polymer (FRP) composite. The smart composite with sensing properties encompasses Terfenol-D alloy nanoparticles and Single Walled Carbon NanoTubes (SWCNT). To explore various configurations the of nanoparticle constituents’ effect on fracture toughness within the FRP composite, the ODE model developed within a finite element analysis (FEA) environment is considered to attain fracture observations across the solution space. The acquired FEA data is then used to feed the machine-learning (ML) algorithms …
Data-Driven Discovery Of Material States In Composites Under Fatigue Loads, Muthu Ram Prabhu Elenchezhian, Vamsee Vadlamudi, Rassel Raihan, Kenneth Reifsnider
Data-Driven Discovery Of Material States In Composites Under Fatigue Loads, Muthu Ram Prabhu Elenchezhian, Vamsee Vadlamudi, Rassel Raihan, Kenneth Reifsnider
Institute of Predictive Performance Methodologies (IPPM-UTARI)
Our community has a widespread knowledge on the damage tolerance and durability of the composites, developed over the past few decades by various experimental and computational efforts. Several methods have been used to understand the damage behavior and henceforth predict the material states such as residual strength (damage tolerance) and life (durability) of these material systems. Electrochemical Impedance Spectroscopy (EIS) and Broadband Dielectric Spectroscopy (BbDS) are such methods, which have been proven to identify the damage states in composites. Our previous work using BbDS method has proven to serve as precursor to identify the damage levels, indicating the beginning of …