Development of advanced criteria for blade root design and optimization

In gas and steam turbine engines, blade root attachments are considered as critical components which require special attention for design. The traditional method of root design required high experienced engineers yet the strength of the material was not fully exploited in most cases. In the current thesis, different methodologies for automatic design and optimization of the blade root has been evaluated. Moreover, some methods for reducing the computational time have been proposed. First, a simplified analytical model of the fir-tree was developed in order to evaluate mean stress in different sections of the blade root and disc groove. Then, a more detailed two-dimensional shape of the attachment capable to be analyzed in finite element (FE) analysis was developed for dovetail and fir-tree. The model was developed to be general in a way to include all possible shapes of the attachment. Then the projection of the analytical model over the 2D model was performed to compare the results obtained from analytical and FE methods. This comparison is essential in the later use of analytical evaluation of the fir-tree as a reduction technique of searching domain optimization. Moreover, the possibility of predicting the contact normal stress of the blade and disc attachment by the use of a punch test was evaluated. A puncher composed of a flat surface and rounded edge was simulated equivalent to a sample case of a dovetail. The stress profile of the contact in analytical, 2d and 3d for puncher and dovetail was compared. As an optimizer Genetic Algorithm (GA) was described and different rules affecting this algorithm was introduced. In order to reduce the number of callbacks to high fidelity finite element (FE) method, the surrogate functions were evaluated and among them, the Kriging function was selected to be constructed for use in the current study. Its efficiency was evaluated within a numerical optimization of a single lob. In this study, the surrogate model is not used solely in finding the optimum of the attachment shape as it may provide low accuracy but in order to benefit its fast evaluation and diminish its low accuracy drawback, the Kriging function (KRG) was used within GA as a pre-evaluation of the candidate before performing FE analysis. Moreover, the feasible and non-feasible space in a multi-dimensional complex searching domain of the attachment geometry is explained and also the challenge of a multi-district domain is tackled with a new mutation operation. In order to rectify the non-continuous domain, an adaptive penalty method based on Latin Hypercube Sampling (LHS) was proposed which could successfully improve the optimization convergence. Furthermore, different topologies of the contact in a dovetail were assessed. Four different types of contact were modeled and optimized under the same loading and boundary conditions. The punch test was also assessed with different contact shapes. In addition, the state of stress for the dovetail in different rotational speed with different types of contact was assessed. In the results and discussion, an optimization of a dovetail with the analytical approach was performed and the optimum was compared with the one obtained by FE analysis. It was found that the analytical approach has the advantage of fast evaluation and if constraints are well defined the results are comparable to the FE solution. Then, a Kriging function was embedded within the GA optimization and the approach was evaluated in an optimization of a dovetail. The results revealed that the low computational cost of the surrogate model is an advantage and the low accuracy would be diminished in a collaboration of FE and surrogate models. Later, the capability of employing the analytical approach in a fir-tree optimization is assessed. As the fir-tree geometry has a higher complexity working domain in comparison to the dovetail, the results would be consistent for the dovetail also. Different methods are assessed and compared. In the first attempt, the analytical approach was adopted as a filter to select out the least probable fit candidates. This method could provide a 7\% improvement in convergence. In another attempt, the proposed adaptive penalty method was added to the optimization which successfully found the reasonable optimum with 47\% reduction in computational cost. Later, a combination of analytical and FE models was joined in a multi-objective multi-level optimization which provided 32\% improvement with less error comparing to the previous method. In the last evaluation of this type, the analytical approach was solely used in a multi-objective optimization in which the results were selected according to an FE evaluation of most fit candidates. This approach although provided 86\% improvement in computational time reduction but it depends highly on the case under investigation and provides low accuracy in the final solution. Furthermore, a robust optimum was found for both dovetail and fir-tree in a multi-objective optimization. In this trial, the proposed adaptive penalty method in addition to the surrogate model was also involved

Determination of the Constants of GTN Damage Model Using Experiment, Polynomial Regression and Kriging Methods

Damage models, particularly the Gurson–Tvergaard–Needleman (GTN) model, are widely used in numerical simulation of material deformations. Each damage model has some constants which must be identified for each material. The direct identification methods are costly and time consuming. In the current work, a combination of experimental, numerical simulation and optimization were used to determine the constants. Quasi-static and dynamic tests were carried out on notched specimens. The experimental profiles of the specimens were used to determine the constants. The constants of GTN damage model were identified through the proposed method and using the results of quasi-static tests. Numerical simulation of the dynamic test was performed utilizing the constants obtained from quasi-static experiments. The results showed a high precision in predicting the specimen’s profile in the dynamic testing. The sensitivity analysis was performed on the constants of GTN model to validate the proposed method. Finally, the experiments were simulated using the Johnson–Cook (J–C) damage model and the results were compared to those obtained from GTN damage model

Innovative Design of Attachment for Turbine Blade Rotating at High Speed

There is evidence of a lack of knowledge in the design of the blade/disk attachment so that the strength of the materials is not fully exploited and the load capability of the attachment is underestimated. The aim of this work is to improve the engineers' capability in designing the attachment so that higher loads can be carried with the same material. To this end, an optimization method has been applied to the attachment design. A dovetail blade root was chosen as case study and the objective function was the static equivalent stress in the blade and the disc. The dovetail was described by variable parameters under geometrical and physical constraints. Optimization was performed with a Genetic Algorithm (GA). The result of the optimization procedure is the optimal set of parameter values that minimizes the equivalent stress on the critical areas. Moreover, a surrogate function was utilized as a booster to the GA to save computational time. Stress analysis was performed with a commercial Finite Element (FE) software to provide the exact fitness value. An in-house code was developed to manage both the optimization process and the input/output interface with the FE software. The same code provides a decision-making core. This core checks for feasibility of the geometry of the current set of parameters. The expected result is an optimized profile in terms of Von-Misses equivalent stress

Study on efficacy of Probiotic in Broiler Chickens diet

Abstract: 400 day old chicks were distributed randomly into 4 treatments and 4 replicates in each treatment (25 birds in each replicate) and fed standard feed. The effects of different levels of probiotic in diets for 49 days were studied. Humoral immune responses were studied by conducting experiments on cellular proliferation, entry and survival of beneficial bacteria in gut, immunoglobulin titers. Mean body weight. Gain, feed intake and feed efficiency were recorded significantly (P<0.05).Immune response of chicks through study of levels of anti-body productions (even after SRBC injections) in experimental groups were also significantly different as compared with the control group (P<0.01).The bacteriological and intestinal morphology studies were showed significantly different in birds, when fed probiotics. Therefore, it can be suggested the Probiotic (Biomin Imbo) can be safely used at the rate of 0.1, 0.05 and 0.025% in starter, grower and finisher diets. The aim of the experiment was to evaluate whether selected Probiotic (Biomin Imbo) 3×10 8 cfu/g have different immunomodulating effects in broiler chickens