Paper Title

THERMAL BARRIER COATINGS AND THEIR EFFECT ON TURBINE BLADE PERFORMANCE

Abstract

On the turbine blade, thermal barrier coatings (TBCs) are applied to lower the temperature of the underlying substrate and offer defense against hot corrosion and oxidation caused by hightemperature gases. The performance and effectiveness of the coatings can be enhanced by the blade\'s optimal ceramic top-coat thickness distribution. Because the goals of high thermal insulation performance, long operation durability, and low fabrication cost conflict, designing the coatings\' thickness is a multi-objective optimization problem. This study created a process for designing the gas turbine blade\'s TBC thickness distribution, which ranges from 100 μm to 500 μm. Nickel alloy is used to create the base material for the blade geometry, and partially stabilized zirconia is chosen as the coating material. The multi-objective optimization problem in this case was solved using a weighted-sum approach after three-dimensional finite element models were constructed with CATIA and examined with ANSYS WORKBENCH. A suitable multi-region top-coat thickness distribution scheme was created while taking fabrication cost, productivity, and manufacturing accuracy into account.
KEYWORDS : Thermal Barrier Coatings; Oxidation; corrosion; Ceramic Top-coat thickness

Paper Title

ANALYSIS OF NUMERICAL METHODS TO INCLUDE DYNAMIC CONSTRAIN IN TSCOPF MODELS

Abstract

Transient Stability Constrained Optimal Power Flow (TSCOPF) models effectively solve the optimization of power system operation, including steady state and dynamic constraints. TSCOPF studies incorporate the electromechanical oscillations of synchronous machines into well-known optimal power flow models. The discretized differential equations that depict the system dynamics in the optimization model are one of the primary methods used in TSCOPF studies. This study examines the effects of the integration time step and various implicit and explicit numerical integration techniques on the solution of a TSCOPF model. The impact on power dispatch, the overall cost of generation, the precision of the computation of electromechanical oscillations between machines, and the magnitude of the optimization problem are specifically examined and the computational time.
KEYWORDS : power system transient stability; economic dispatch; numerical integration methods; non-linear programming; optimal power flow

Paper Title

TRANSFORMATION OF BIG DATA THROUGH MACHINE LEARNING AND IT’S APPLICATIONS

Abstract

Both Sciences and Industry are towards a data revolution. And this has led to a complete data of new formats and unparalleled data bases. Such an increase in huge amount of data have given rise to an opportunity for Machine Learning and Bigdata to come concurrently and to develop Machine Learning methods that have the capability to hold present data types and for navigation of large amount of information with minimal or no human intervention. By implementing fast and effective algorithms and information driven models for processing of data, Machine Learning is capable to give faultless results. Today Machine Learning is being vigorously utilized in a wide range of areas than we anticipate. A pure Machine Learning process, the more data provided to the system, the more it can learn from it, returning the results that are looking for, and that’s why it works well with Bigdata. Without it, the Machine Learning can\'t keep running at its at most level and this is because of the way that with less information, the machine has less examples to gain from, and subsequently its results may be influenced. This paper gives the survey on applications and challenges of Machine Learning techniques, advanced learning methods towards Bigdata.
KEYWORDS : Machine Learning, Bigdata, Deep Learning, Neural Networks.