Masood Shah

Smart sensing layer for the detection of damage due to defects in a laminated composite structure

A smart sensing layer based on polystyrene and carbon nanoparticles has been developed. It has been deposited on the composite specimens for real-time, in situ monitoring of structural health. The strain response of the smart sensing layer has been recorded for composite laminates using different defect configurations (notch spacing). Numerical simulations of the stress–strain concentration have been carried out in order to determine the state of strain at the smart sensing layer, in the presence of different notch configurations. It has been observed that the sensing layer detects well the presence of large deformations and damage due to defects in the structure, with clearly defined peaks at the points of structural damage.

Influence of electric discharge machining on fatigue limit of high strength aluminum alloy under finish machining

Abstract The aim of this study was to investigate the fatigue limit of the electric discharge machined aluminum alloy 2024 T6. Machining was performed at 3, 6, 9, and 12 A discharge current values while all other parameters were kept constant. The fatigue tests were performed on a four-point rotating bending machine at the frequency of 50 Hz and at ambient temperature. Fatigue limits at 107 cycles were determined using staircase (up-and-down) method and the obtained data was analyzed statistically. For reference purposes, fatigue strength of the conventionally turned specimens was also found by the same technique. The EDM surface is characterized by its morphology, roughness, hardness, and thickness of the resolidified layer. The effects of discharge current values on these surface characterizing parameters and subsequent influence on fatigue limit have been discussed.

Evaluation of Fatigue Behavior and Surface Characteristics of Aluminum Alloy 2024 T6 After Electric Discharge Machining

Abstract The effect of electric discharge machining (EDM) on surface quality and consequently on the fatigue performance of Al 2024 T6 is investigated. Five levels of discharge current are analyzed, while all other electrical and nonelectrical parameters are kept constant. At each discharge current level, dog-bone specimens are machined by generating a peripheral notch at the center. The fatigue tests are performed on four-point rotating bending machine at room temperature. For comparison purposes, fatigue tests are also performed on the conventionally machined specimens. Linearized SN curves for 95% failure probability and with four different confidence levels (75, 90, 95 and 99%) are plotted for each discharge current level as well as for conventionally machined specimens. These plots show that the electric discharge machined (EDMed) specimens give inferior fatigue behavior as compared to conventionally machined specimen. Moreover, discharge current inversely affects the fatigue life, and this influence is highly pronounced at lower stresses. The EDMed surfaces are characterized by surface properties that could be responsible for change in fatigue life such as surface morphology, surface roughness, white layer thickness, microhardness and residual stresses. It is found that all these surface properties are affected by changing discharge current level. However, change in fatigue life by discharge current could not be associated independently to any single surface property.

EDM of Aluminum Alloy 6061 Using Graphite Electrode Using Paraffin Oil and Distilled Water as Dielectric Medium

EDM machining of Al 6061 was performed under varying conditions of pulse current and pulse duration. Graphite was used as an electrode material with distilled water and paraffin oil as two different dielectric mediums. The aim is to characterize the surface integrity produced as a result of EDM machining under both varying electrical and non-electrical parameters as it is important in determining the service life of EDM machined components. The vertical, horizontal and corner surfaces are studied independently for each single set of conditions. The average white layer thickness (AWLT) and surface roughness was found to be dependent on pulse current values and pulse duration. The dielectric medium also has an influence on the thickness and nature of white layer. It was found that the thickness and nature of the white layer formed from distilled water is different from that of paraffin oil. New methods of AWLT and surface roughness measurement through an optical microscope are described. The surface roughness method developed was calibrated against an identical surface roughness tester. Finally, material removal rate, tool wear rate, the presence of micro cracks, voids and globules were compared for different conditions and conclusions were drawn according to the actual physical conditions during machining.

Normalization of fatigue crack growth data in AISI H11 tool steel at room and elevated temperature

The fatigue crack growth rate of materials is shown to be dependent on the testing conditions like load ratio R and testing temperature. Great interest exists in normalizing this data onto a single curve. In this research, some methods commonly used to normalize the effect of R ratio are tested on Fatigue Crack Growth Rate (FCGR) curves of AISI H11 tool steel. These methods are based on either purely mathematical relations or on the effect of crack closure in variable R ratio tests. A model based on the crack tip opening displacement measurements to normalize the effect of R ratio as well as temperature is also used. This model takes into account the material-hardening coefficient, yield stress, Young’s modulus, and the crack tip opening displacement measurements. Crack tip opening displacement measurements have also been directly used to characterize the FCGR. A method is presented to find out crack closure as well as crack tip opening displacement using 2D digital image correlation measurements near the crack tip. At the end, a critical analysis of the four normalization techniques is presented.