Inverse Generation of Gas Turbine Component Performance Maps From Experimental Test Data

A significant hurdle in the development of performance simulation tools to analyze and evaluate nuclear power plants (NPP) is finding data relating to component performance maps. As a result, engineers often rely on an estimation approach using various scaling techniques. The purpose of this study is to determine the component characteristics of a closed-cycle gas turbine NPP using the existing component maps with the corresponding design data. The design data are applied for different working fluids using a multifluid scaling approach to adapt data from one component map into another. The multifluid scaling technique described herein was developed as an in-house computer simulation tool. This approach makes it easy to theoretically scale the existing maps using similar or different working fluids without carrying out a full experimental test or repeating the whole design and development process. The results of selected case studies show a reasonable agreement with the available data. The analyses intend to aid the development of cycles for Generation IV NPPs specifically gas-cooled fast reactors (GFRs) and very high-temperature reactors (VHTRs).

show abstract

“…However, some numerical methods are not as robust in regenerating data in some off-design operating regions. [12,13].…”

Section: Introductionmentioning

confidence: 99%

Performance Simulation to Understand the Effects of Multifluid Scaling of Gas Turbine Components for Generation IV Nuclear Power Plants

Osigwe

Gad-Briggs

Nikolaidis

et al. 2020

Journal of Nuclear Engineering and Radiation Science

View full text Add to dashboard Cite

show abstract

Control-Oriented System Identification of Turbojet Dynamics

Villarreal-Valderrama,

Liceaga-Castro,

Hernandez-Alcantara

et al. 2024

Aerospace

View full text Add to dashboard Cite

The autonomous operation of turbojets requires reliable, accurate, and manageable dynamical models for several key processes. This article describes a practical robust method for obtaining turbojet thrust and shaft speed models from experimental data. The proposed methodology combines several data mining tools with the intention of handling typical difficulties present during experimental turbojet modeling, such as high noise levels and uncertainty in the plant dynamics. The resulting shaft speed and thrust models achieved a percentage error of 0.8561% and 3.3081%, respectively, for the whole operating range. The predictive power of the resulting models is also assessed in the frequency domain. The turbojet cut frequencies are experimentally determined and were found to match those predicted by the identified models. Finally, the proposed strategy is systematically tested with respect to popular aeroengine models, outperforming them both in the time and frequency domains. These results allow us to conclude that the proposed modeling method improves current modeling approaches in both manageability and predictive power.

show abstract

Inverse Generation of Gas Turbine Component Performance Maps From Experimental Test Data

Cited by 2 publications

References 1 publication

Performance Simulation to Understand the Effects of Multifluid Scaling of Gas Turbine Components for Generation IV Nuclear Power Plants

Performance Simulation to Understand the Effects of Multifluid Scaling of Gas Turbine Components for Generation IV Nuclear Power Plants

Control-Oriented System Identification of Turbojet Dynamics

Contact Info

Product

Resources

About