Tabular Machine Learning Methods for Predicting Gas Turbine Emissions [PDF]
Machine Learning and Knowledge Extraction 2023, 2023 Predicting emissions for gas turbines is critical for monitoring harmful pollutants being released into the atmosphere. In this study, we evaluate the performance of machine learning models for predicting emissions for gas turbines. We compare an existing predictive emissions model, a first principles-based Chemical Kinetics model, against two machine ...
arxiv +1 more source
Development of helium turbine loss model based on knowledge transfer with Neural Network and its application on aerodynamic design [PDF]
arXiv, 2023 Helium turbines are widely used in the Closed Brayton Cycle for power generation and aerospace applications. The primary concerns of designing highly loaded helium turbines include choosing between conventional and contra-rotating designs and the guidelines for selecting design parameters.
arxiv
The influence of various optimization algorithms on nuclear power plant steam turbine exergy efficiency and destruction [PDF]
arXiv, 2021 This paper presents an exergy analysis of the whole turbine, turbine cylinders and cylinder parts in four different operating regimes. Analyzed turbine operates in nuclear power plant while three of four operating regimes are obtained by using optimization algorithms - SA (Simplex Algorithm), GA (Genetic Algorithm) and IGSA (Improved Genetic-Simplex ...
arxiv
Inverse Aerodynamic Design of Gas Turbine Blades using Probabilistic Machine Learning [PDF]
arXiv, 2021 One of the critical components in Industrial Gas Turbines (IGT) is the turbine blade. Design of turbine blades needs to consider multiple aspects like aerodynamic efficiency, durability, safety and manufacturing, which make the design process sequential and iterative.The sequential nature of these iterations forces a long design cycle time, ranging ...
arxiv
Analysis of the Near-Wall Flow in a Turbine Cascade by Splat Visualization [PDF]
, 2019 Turbines are essential components of jet planes and power plants. Therefore, their efficiency and service life are of central engineering interest. In the case of jet planes or thermal power plants, the heating of the turbines due to the hot gas flow is critical.
arxiv +1 more source
Estimation of Gas Turbine Shaft Torque and Fuel Flow of a CODLAG Propulsion System Using Genetic Programming Algorithm [PDF]
arXiv, 2020 In this paper, the publicly available dataset of condition based maintenance of combined diesel-electric and gas (CODLAG) propulsion system for ships has been utilized to obtain symbolic expressions which could estimate gas turbine shaft torque and fuel flow using genetic programming (GP) algorithm. The entire dataset consists of 11934 samples that was
arxiv
Predictive energy management for hybrid electric aircraft propulsion systems [PDF]
arXiv, 2021 We present a Model Predictive Control (MPC) algorithm for energy management in aircraft with hybrid electric propulsion systems consisting of gas turbine and electric motor components. Series and parallel configurations are considered. By combining a point-mass aircraft dynamical model with models of electrical losses and losses in the gas turbine, the
arxiv
Gas turbine diagnostic system [PDF]
arXiv, 2011 The creation of the systems models is very actual at present time, because it allow to simulate the work of some complex equipment without any additional spends. The given model of gas turbine is allowed to test and optimize the software for gas turbine automation systems, study station personal, like operators and engineers and will be useful for ...
arxiv
A Thermodynamic based and Data Driven Hybrid Network for Gas Turbine Modeling [PDF]
arXiv, 2021 The on-wing engine performance is difficult to track for thermodynamic models because of its inaccurate component maps, and also difficult for data driven methods for their over-fitting to measurement errors. So, we propose a thermodynamic based and data driven hybrid network for gas turbine modeling.
arxiv
Environmental Pollution Prediction of NOx by Process Analysis and Predictive Modelling in Natural Gas Turbine Power Plants [PDF]
arXiv, 2020 The main objective of this paper is to propose K-Nearest-Neighbor (KNN) algorithm for predicting NOx emissions from natural gas electrical generation turbines. The process of producing electricity is dynamic and rapidly changing due to many factors such as weather and electrical grid requirements.
arxiv