Patents by Inventor Nicolas SCHMIT

Nicolas SCHMIT has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Method and apparatus for predicting turbine outlet temperature in gas turbine
    Patent number: 11428118
    Abstract: In a method for predicting a turbine outlet temperature at a future use of a gas turbine based on a past use thereof, the turbine outlet temperature (objective variable) at the future use is predicted by a turbine outlet temperature model by using a parameter (explanatory variable) in environmental and operational conditions planned for the future use and a rotating speed of a fan (explanatory variable) planned for the future use, and coefficients with respect to the explanatory variables are identified through a learning. In the learning, the coefficients are identified based on a regression learning of the explanatory variables and the objective variable of the turbine outlet temperature model made by using the parameter, the rotating speed of the fan and the turbine outlet temperature at the past use of the gas turbine.
    Type: Grant
    Filed: October 1, 2018
    Date of Patent: August 30, 2022
    Assignee: IHI CORPOTATION
    Inventors: Nicolas Schmit, Masato Kaniwa, Yukihiro Kawano, Shiho Sodekoda
  • METHOD AND APPARATUS FOR PREDICTING TURBINE OUTLET TEMPERATURE IN GAS TURBINE
    Publication number: 20190032512
    Abstract: In a method for predicting a turbine outlet temperature at a future use of a gas turbine based on a past use thereof, the turbine outlet temperature (objective variable) at the future use is predicted by a turbine outlet temperature model by using a parameter (explanatory variable) in environmental and operational conditions planned for the future use and a rotating speed of a fan (explanatory variable) planned for the future use, and coefficients with respect to the explanatory variables are identified through a learning. In the learning, the coefficients are identified based on a regression learning of the explanatory variables and the objective variable of the turbine outlet temperature model made by using the parameter, the rotating speed of the fan and the turbine outlet temperature at the past use of the gas turbine.
    Type: Application
    Filed: October 1, 2018
    Publication date: January 31, 2019
    Applicant: IHI Corporation
    Inventors: Nicolas SCHMIT, Masato KANIWA, Yukihiro KAWANO, Shiho SODEKODA