The principal objective of this study is to employ non-destructive broadband dielectric spectroscopy/impedance spectroscopy and machine learning techniques to estimate the moisture content in FRP composites under hygrothermal aging. Here, classification and regression machine learning models that can accurately predict the current moisture saturation state are developed using the frequency domain dielectric response of the composite, in conjunction with the time domain hygrothermal aging effect. First, to categorize the composites based on the present state of the absorbed moisture supervised classification learning models (i.e., quadratic discriminant analysis (QDA), support vector machine (SVM), and artificial neural network-based multilayer perceptron (MLP) classifier) have been developed. Later, to accurately estimate the relative moisture absorption from the dielectric data, supervised regression models (i.e., multiple linear regression (MLR), decision tree regression (DTR), and multi-layer perceptron (MLP) regression) have been developed, which can effectively estimate the relative moisture absorption from the dielectric response of the material with an R2 value greater than 0.95. The physics behind the hygrothermal aging of the composites has then been interpreted by comparing the model attributes to see which characteristics most strongly influence the predictions.

This research work focuses on the development of a piezoelectric magnetostrictive smart composite with advanced sensing capability. The composite piezoelectric property is achieved from the dispersion of single-walled carbon nanotubes (SWCNTs) and the magnetostrictive property from Terfenol-D nanoparticles. Finite element analysis (FEA) is used to examine the feasibility of modelling the piezoelectric (change in electric field) and magnetostrictive (change in magnetic field) self-sensing responses in the presence of applied stress. The numerical work was coupled with a series of mechanical tests to characterize the piezoelectric response, magnetostriction response and mechanical strength. Tensile tests of the composite samples manufactured as is (virgin), samples with SWCNTs, samples with Terfenol-D nanoparticles and samples with both SWCNTs and Terfenol-D nanoparticles were conducted. It was observed that an increase in volume fraction of Terfenol-d nanoparticles increases the change in magnetization, therefore increasing voltage response up to the point of saturation. The optimum change in amplitude was observed with 0.35% volume fraction of Terfenol-D nanoparticles. A constant ratio of SWCNTs was maintained, and maximum change in electrical resistance was at 7.4%. Fracture toughness for the samples with all nanoparticles was explored, and the results showed improved resistance to crack propagation.

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The aviation and automobile industries have recently depended on thermoset epoxy-based prepreg as a raw material for manufacturing composites. Since prepregs have a limited out-life (i.e., the maximum storing time allowed at room temperature), they must be stored in refrigerators at low temperatures. If not maintained, they can often adversely affect the desired quality of the final product. Prepregs are often discarded once the prepreg out-life ends, leading to a loss of millions of dollars and a detrimental impact on the environment. Therefore, it is necessary to develop a simple method to monitor prepreg aging/degradation in order to ensure its usability or repurpose prepreg usage. In this study, we used broadband dielectric spectroscopy to monitor the degradation state of the glass fiber/epoxy prepreg sample stored at room temperature, and the data has been used to predict the mechanical performance of the final manufactured composite part. The frequency-based nondestructive dielectric measuring technique was used to calculate the dielectric strength and relaxation time of the prepregs. The dielectric strength decreased and relaxation time increased with aging, allowing the aging progression to be captured. Furthermore, with aging, the real permittivity value changes to a lower value and the relaxation peak in imaginary permittivity with respect to frequency shifts to a lower frequency. The physics behind this dielectric measurement method has been understood in the context of analyzing the prepreg’s cure kinetics parameters, which has been investigated using differential scanning calorimetry. Overall, this simple dielectric-based monitoring technology will provide confidence in the future use of degraded or out-of-life raw material systems for manufacturing.

Background: Blunt trauma abdomen is a common surgical emergency which may present as an isolated problem or as a part of poly trauma. Road traffic (automobile) accident is the most common cause of blunt trauma abdomen.Methods: After initial resuscitation and achieving hemodynamic stability, all patients were subjected to careful history and clinical examination. Depending on the clinical findings, decision for further investigations as four-quadrant aspiration, X-ray of chest and abdomen erect view and abdominal ultrasound were taken. The decision to operate or non-operative management depended on the outcome of clinical examination and results of diagnostic tests.Results: This is a clinical study of 100 patients who were admitted, treated and followed up in Gauhati Medical College and Hospital, Guwahati, Assam, India from 1st July, 2015 to 30th June, 2016. In this study, the incidence of blunt trauma abdomen was found to be 69.78% out of all abdominal trauma patients. The most common cause was found to be road traffic accidents (67%). The commonest age group was 21 to 30 years comprises about 39% of patients. The average age was 30.82 years. Spleen was the most common organ involved (44%). 53.52% of patient having solid organ injured was managed conservatively. Out of 60 operative cases, 25 (41.7%) cases were operated within 3-6 hours.Conclusions: Patients with blunt trauma abdomen should have early and accurate diagnosis and prompt, proper and prudent management to improve overall prognosis.