Gas Turbine Simulation Program (GSP) Demo.The course is sponsored by international companies via the Dutch Foundation for Gas Turbine Education ( SGO). Senior academic students interested in working in this field can add it to their curriculum as an elective course. The course is aimed at engineers in the propulsion and power sector. Use GTPsim, a brand new tool for detailed power and propulsion system design and performance analysis.Use the Gas Turbine Simulation Program GSP, the Delft University's in-house tool, well known and used in the international gas turbine community, or, alternatively.Apply the Modelica modeling language to develop propulsion and power system models.Understand the theoretical elements on which simulation software is based.Use the models to optimize design and operation of power and propulsion systems for specific applications.Use models and the results of simulations to analyze a variety of relations and interactions within the systems.Develop modular system models based on physical relations using a 9-step method.After taking this course, you will be able to:
You will also become competent in running these computer models to solve complex problems like those pertaining to the design, operation, R&D, life-cycle management, maintenance, repair and overhaul (MRO), and control of power and propulsion systems.
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You will learn a unique and proven method to develop modular system models and how to implement them in state-of-the-art specialized software. In this unique course, you will advance your system modeling skills, which are at the core of the design process and essential for predicting and evaluating performance. Aviation has been and is at the forefront in this respect, and the power sector has always benefited from such innovation. The solution of these problems very often demands engineers who are versed in the latest know-how in system modeling and simulation. The comparisons show that the proposed method shows evident superiority in early warning of performance faults for gas turbines over other methods.The world is facing new challenges on sustainability and global warming and, as a result, propulsion and power technologies will play an even greater role in shaping the future. The proposed method is utilized to analyze actual measured data of LM2500 +, and the results verify that the new-built digital model has higher accuracy and better efficiency. The third solution focuses on the early warning based on the digital twin model, which self-learns the alarm threshold of the warning feature of gas-path parameters using the kernel density estimation. The introduction of an error module to the existing model can greatly shorten the modeling cycle. Secondly, the idea of controlling the relative accuracy of model parameters is developed. Firstly, a novel performance modeling strategy is proposed to make the simulation effect close to the actual gas turbine by fusing the mechanism model and measurement data. This paper proposes a digital twin model-based early warning method for gas-path faults that breaks through the above obstacles from three aspects. However, three technical difficulties need to be solved: (1) low modeling precision caused by individual differences between gas turbines, (2) poor solution efficiency due to excessive iterations, and (3) the false alarm and missing alarm brought by the traditional fixed threshold method.
The digital twin-driven performance model provides an attractive option for the warn gas-path faults of the gas turbines.
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