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This paper addresses the problem of analyzing measurement data to estimate the variations in turbine blade life in the presence of manufacturing variability. A methodology that employs existing denoising techniques, namely, Principal Component Analysis and Fast Fourier Transform analysis, is proposed for filtering measurement error from the measured data set. An approach for dimensionality reduction is employed that uses prior knowledge on the measurement error obtained from analyzing repeated measurements. The proposed methodology also helps in capturing the effects of manufacturing drift with time and the blade to blade manufacturing error. The filtered data is then used for generating three-dimensional representations of probable manufactured blade shapes from the limited number of available measurements. This is accomplished by using a Free-Form Deformation based approach for deforming a nominal mesh to the desired shapes. Estimations of life on the probable turbine blade shapes manufactured over a span of 1 year indicate a reduction of around 1.7% in the mean life relative to the nominal life, with a maximum relative reduction of around 3.7%, due to the effects of manufacturing variability. [DOI: 10.1115/1.4002806]

Waste from the electronics industry; 'e-waste,' is creasing at an alarming rate. The industrialized countries of the world are beginning to dress the problem, as e-waste is inundating solid-waste-disposal facilities, [...]

Aerospace design optimization typically explores the effects of structural performance and aerodynamics on the geometry of a component. This paper presents a methodology to incorporate manufacturing cost and fatigue life models within an integrated system to simultaneously trade off the conflicting objectives of minimum weight and manufacturing cost while satisfying constraints placed by structural performance and fatigue. A case study involving the design of a high pressure turbine disk from an aircraft engine is presented. Manufacturing cost and fatigue life models are developed in DECISIONPRO[TM], a generic modeling tool, whereas finite element analysis is carried out in the Rolls-Royce PLC proprietary solver SC03. A multiobjective optimization approach based on the nondominated sorting genetic algorithm (NSGA) is used to evaluate the Pareto front for minimum cost and volume designs. A sequential workflow of the different models embedded within a scripting environment developed in MATLAB[TM] is used for automating the entire process. [DOI: 10.1115/1.2779899]

Abstract The present study is an effort to identify a potent chemopreventive agent against various diseases (including cancer) in which oxidative stress plays an important causative role. Here, we investigated [...]

Summary Basil or sweet basil (Ocimum basilicum) is cultivated throughout India and is known for its medicinal value. The effects of doses of 200 and 400 mg/kg body weight of [...]

India's farm families suffer from malnutrition despite their ability to produce the food they need for nourishment. Unlike the poor working class in the cities, farmers have no steady income. Their earnings are dependent on the success of their harvests. Nutrition of farm families is also based on produce surplus, if any. Staple food production must be given careful attention to meet nutritional problems of rural communities. More inexpensive but nutritious substitutes for far products are also recommended.