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ThesisItem Open Access Specimen geometry and material property uncertainity model for probabilistic fatigue life predictions(G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2006-08) Bhatt, Sandeep; Gope, P.C.The analysis of cracks within structure is an important application if the damage tolerance and durability of structures and components are to be predicted. As part of the engineering design process, engineers have to assess not only how well the design satisfies the performance requirements but also how durable the product will be over its life cycle. Often cracks cannot be avoided in structures; however the fatigue life of the structure depends on the location and size of these cracks. In order to predict the fatigue life for any component, crack growth study needs to be performed. Fatigue life is related to and is affected to a great extent with the uncertainties in both the material properties and the specimen or component geometrical parameters. The intent of the work is to contribute to the fundamental understanding of fatigue life and its relation with these uncertainties. Fatigue life data exhibits wide scattered results due to inherent microstructural inhomogeneity in the material properties even if the test specimens are taken from the same lot and tested under same loading condition. As the fatigue testing is time consuming and costly, setting up of an analytical method for prediction of fatigue life is necessary. In the present work an approximate analytical model derived from the energy theorem and probabilistic nature of material properties and specimen geometry parameters are combined and correlated to determine the associated error in the predicted fatigue life. The prediction is based on minimization of error. The predicted values of fatigue life are compared with the experimental values available in literature.ThesisItem Open Access A neural network model for predicting fatigue life of carbon steel, copper alloy and aluminium alloy under constant amplitude loading(G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2005-01) Singh, Dalvir; Gope, P.C.Fatigue failure has been intensively studied for a more than a century. Fatigue in metals often progresses by the initiation of a single crack and its intermittent propagation until catastrophic failure, which occurs with or without warning. Fatigue testing of materials is a time consuming and expensive process. If every fatigue condition is to be investigated, this results in many different experiments involving many variables. The problem is compounded by the proliferation of new materials requiring evaluation and increasingly demanding applications for these materials. This derives the need for more accurate fatigue life prediction. A potential solution to this requirement is offered by artificial neural networks (ANNs). ANNs are an alternative to conventional programmed computing and are based on the operation of the brains. Now ANN has been used successively to many engineering applications. ANNs also offers a means of handling many multi-variable parameters for which an exact analytical model does not exist or would be difficult to develop. ANNs also provide a compact method of considering large amounts of data and simple means of assessing the liking outcome of a complex problem with a specified set of conditions. The analysis of fatigue life data requires all these capabilities. In the present investigation an artificial neural network (ANN) model has been developed to predict the fatigue life for a given probability of failure for carbon steel, aluminium alloys and copper alloys. Architecture of the of the ANN model consists of two hidden layers and –24-6-; -24-6-; -18-6-; -30-6-; hidden nodes for 0.41 and 0.19carbon steel, plain carbon steel, aluminium alloys, copper alloys respectively with an output target. This has been established through a series of trials, which allows convergence in a shortest training time. The inputs for training the ANN model includes chemical composition, mechanical properties, applied stress and probability of failure. The predicted fatigue life is found to be well within a scatter band of 2 with regression coefficient r 0.987. The average rms error is 0.00004, 0.00005, 0.00004, 0.00004 for 0.41 and 0.19 carbon steel, plain carbon steel, aluminum alloys, copper alloys respectively. The predicted results are also compared with the other statistical model available in the literature.ThesisItem Open Access Mechanical and thermal properties of acrylic hydrazide cured epoxy; in- situ polymerization(G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2004-08) Yadav, Ram Piyare; Sah, P.L.A series of acrylic hydrazide (AH) cured epoxy were synthesized at varying concentration of acrylic hydrazide ranging 11.5:1 to 6.14:1 (epoxy: acrylic hydrazide, v/v %) through in-situ polymerization method. In present investigation it has been observed that density of AH cured epoxy composite is slightly higher compared to hardener HY951 cured epoxy composite at same concentration of curing agent. Wear behavior has been tested and it is observed that acrylic hydrazide cured epoxy 9:1 & 7.33:1 (epoxy: acrylic hydrazide, v/v %) have lower wear rate compared to hardener HY951 cured epoxy. Mechanical and thermal property of the developed composite has been determined and results were compared with composite made from commercially available hardener HY951 cured epoxy CY230. It is found that composite developed with acrylic hydrazide cured epoxy CY230 of ratio 9:1 & 7.33:1 have higher tensile strength, compressive strength, impact strength and hardness compared to HY951 cured epoxy composite. With reference to its material fringe value, it can also be used as photo-elastic material. For spectral characterization UV-VIS spectra and FTIR tests were conducted to study the stabilization of the developed composites. DTA-DTG-TG tests were conducted to study the thermal properties of the composites. Results are compared with HY951 cured epoxy composite. Properties are found to be superior than the composite made from HY951 cured CY230.ThesisItem Open Access Active contour models applied to obtain the shape of tibiae and fibulae from Computed Tomography (CT) scans(G.B. Pant University of Agriculture and Technology, Pantnagar - 263145 (Uttarakhand), 2008-07) Satsangi, Dev Prakash; Saxena, RakeshThe present study was undertaken to apply “active contour models to obtain the shape of tibiae and fibulae from their computed tomography (CT) scans” data. Computed Tomography (CT) is a non-invasive technique to provide images of any part of human body without superimposition of adjacent structures. Studies using computed tomography combined with image active contour have revealed the accuracy of the shapes obtained in CT. Various boundary detection algorithms for CT images have been developed in the last few decades but very few of them are completely automatic. Features such as digitization of initial boundary, closed contours, automatic continuous mode are included in this work. This approach also contains options such as expansion and shifting of initial boundary in order to obtain the final shape. Validation of the algorithm is provided by including artificially created bone slices in standard shapes. The obtained digitized data can further be used for prosthetic applications. The digitized data points of bone and soft tissue used for making 3D model surface. This surface model can be further used to create 3D Finite Element Model which can be used in stress analysis towards design of prosthesis in medical field.ThesisItem Open Access Studies on diesel alcohol emulsification and performance evaluation of C.I. engine on emulsified fuels(Govind Ballabh Pant University of Agriculture and Technology;Pantnagar, 2005) Gupta, Vijay Kumar; Agrawal, P.K.ThesisItem Open Access Modifications in mechanical and thermal properties of epoxy polymethyl methacrylate composite through nanoclay reinforcement(Govind Ballabh Pant University of Agriculture and Technology;Pantnagar, 2006) Mannan, K. Tamil; Sah, P.L.