Patents by Inventor Peter S. Chang

Peter S. Chang 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).

  • Publication number: 20240069248
    Abstract: Anti-reflective optical structures are disclosed. The anti-reflective optical structures include sub-wavelength structures in order to produce one or more index of refraction gradients within the anti-reflective optical structures. The one or more index of refraction gradients can reduce reflection of light over a broad band of wavelengths.
    Type: Application
    Filed: March 9, 2023
    Publication date: February 29, 2024
    Inventors: Mohamed Mahmoud, Huiyang Deng, Satyarth Suri, Jason S. Pelc, Peter L. Chang
  • Patent number: 6567795
    Abstract: Power industry boiler tube failures are a major cause of utility forced outages in the United States, with approximately 41,000 tube failures occurring every year at a cost of $5 billion a year. Accordingly, early tube leak detection and isolation is highly desirable. Early detection allows scheduling of a repair rather than suffering a forced outage, and significantly increases the chance of preventing damage to adjacent tubes. The instant detection scheme starts with identification of boiler tube leak process variables which are divided into universal sensitive variables, local leak sensitive variables, group leak sensitive variables, and subgroup leak sensitive variables, and which may be automatically be obtained using a data driven approach and a leak sensitivity function. One embodiment uses artificial neural networks (ANN) to learn the map between appropriate leak sensitive variables and the leak behavior.
    Type: Grant
    Filed: December 1, 2000
    Date of Patent: May 20, 2003
    Assignees: Tennessee Technological University, Tennessee Valley Authority
    Inventors: Ali T. Alouani, Peter S. Chang
  • Publication number: 20010001149
    Abstract: Power industry boiler tube failures are a major cause of utility forced outages in the United States, with approximately 41,000 tube failures occurring every year at a cost of $5 billion a year. Accordingly, early tube leak detection and isolation is highly desirable. Early detection allows scheduling of a repair rather than suffering a forced outage, and significantly increases the chance of preventing damage to adjacent tubes. The instant detection scheme starts with identification of boiler tube leak process variables which are divided into universal sensitive variables, local leak sensitive variables, group leak sensitive variables, and subgroup leak sensitive variables, and which may be automatically be obtained using a data driven approach and a leak sensitivity function. One embodiment uses artificial neural networks (ANN) to learn the map between appropriate leak sensitive variables and the leak behavior.
    Type: Application
    Filed: December 1, 2000
    Publication date: May 10, 2001
    Inventors: Ali T. Alouani, Peter S. Chang