Project Description

The heart of power plant design is the equipment that converts different forms of energy (nuclear, wind, solar, hydraulic, etc.) into useable electrical energy on the grid. During extreme events such as earthquakes etc., this critical and sensitive equipment may be subjected to violent shaking / disturbances. The saving factor for this equipment is 'damping': natural, artificial / synthetic, or isolation. Natural damping is a poorly understood and somewhat mysterious phenomenon as it is difficult to calculate, anticipate, or design for. In structural design, damping may be enhanced by concrete cracking, slip in steel connections, deformations in attachments etc. However, it is also the most cost-effective way to reduce the impact of violent shaking / disturbance during extreme events. This project will develop experimental methods, numerical models, and machine-learning based tools / approaches to quantify natural damping and assist power plant and equipment designers in understanding the magnitude, uncertainty, and statistical reliability of natural damping in a designed system. While it may seem pedantic / academic, the influence of changing natural damping by even 1% can have a huge economic and project-wide impact on power plant design that is best extolled by practitioners and vendors who are clamoring for this research and results.  

Start Date

January, 2025

Postdoc Qualifications

Ph.D.
Earthquake Engineering
Seismology
Dynamics
Equipment design / classification

Co-advisors

Amit Varma, School of Civil Engineering, Purdue University
Sanj Malushte, Purdue Applied Research Institute, LLC

Bibliography