Material Sciences Based Predictive Models: A Step by Step Demonstration of How Sentient Builds a DigitalClone Model
Dr. Raja Pulikollu, Chief Materials Scientist and Vice President of Commercial Implementations , explains Sentient Science’s technical approach to predict future contact-based fatigue and wear life with DigitalClone prognostic models.
Watch to Learn:
- How the model is built and parameterized
- What inputs go into the model
- How the model is deployed to solve problems in the Energy, Transportation, Industrial and Aerospace markets
Engineers, tribologists, and material scientists who work with rotating equipment and components should watch this webinar. An example of a bearing and a gear in a gearbox will be shown.
Dr. Raja Pulikollu
Vice President of Implementations and Chief Materials Scientist
Dr. Pulikollu is responsible for the commercial implementation of DigitalClone solutions and for the research and development of DigitalClone Material. His expertise includes material science, mechanical metallurgy, prognostics and health management, fatigue and fracture mechanics, probabilistic life prediction methods, and micro-structural analysis. He holds a Ph.D. in Material Science from Wright State University.