Presentation Sample: Quantitative Data Analysis

Designing Experiments for Research: Issues Critical to the Success of Future Gas Turbine Engines

Definition: Quantitative Data Analysis

Quantitative data analysis refers to a data analysis technique seeking to understand behaviors using complex mathematical techniques
Also uses statistical modeling, research and measurement
Done for measurement, valuation or performance evaluation in research instruments
Uses nominal, ordinal, interval and ratio or scale measurements.

Area of Focus: Issues Critical to the Success of Future Gas Turbine Engines

A research can be directed to experimental as well as analytical simulation or modeling of steady altogether with unsteady flow processes
Focus will be interactions that are inherent in the turbo machine blade rows
Issues addressed include blade row interactions unsteady dynamics, high cycle exhaustion, structural dynamics, blade row structures and aerodynamic mistuning
Quantitative data analysis determine critical issues to enhance success of gas turbines in future.

Earlier Application

Gas turbines play significant roles in minimization of gas emissions in the world
Their potentials evolve with evolving climate initiatives and regulations
However, several factors have been detected to influence success of these turbines
These factors include identification, illustration of compressor and fan concepts resulting to enhanced performance altogether with improved reliability (Han, Dutta, & Ekkad, 2012)

Earlier Applications: Cont.

Turbines should be protected from hazardous pollutants that are likely to get way to during gas processing
Department of Energy (DOE) has been involved in research and development in order to address critical issues towards transition of cleaner and fuel diverse supply of power in future
Efficient and clean natural gas has been proved to play roles in driving global economy in gas fired turbine systems
Turbines success in future will be determined by research and developments on their performance systems.

Factors Affecting Validity of Experiments (Turbo Machine Blade Rows)

External Factors

Validity of experiment will be influenced by the interaction between testing and treatment
It is vital to have several tests before the final test in the turbine operations in order to have valid results
Moreover, multiple-treatment interferences can affect validity of results
In this case, results of turbine activities and several factors in the fans and compressors may be different hence affecting validity of results…”

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