Abstract
Billions of dollars are spent each year on clean, renewable energy and the operations of traditional power plants to meet the demands of electricity consumption here in the U.S. and around the world. Energy companies are always feeling the pressure to provide the electricity people rely on every day in their personal and professional lives. With bigger, more powerful computers, and the fast development of new technology, the demand for electricity will continue to grow forcing energy companies to adopt more efficient inspection applications to provide high quality, sustainable power in the future. The U.S. generated 4.12 trillion kilowatt hours of electricity in 2020. The leader in electric generation is natural gas with 40 percent of the total amount. Natural gas was followed by nuclear at 20 percent, coal at 19 percent, wind at 8.4 percent, hydro at 7.3 percent, and solar at 2.3 percent. The NDT industry along with engineering and materials science is a critical part of the longevity of new and aging power plants around the world. This paper will discuss through examples and case studies the technology and analysis that goes into power plant condition assessments. Emphasis will be given to the NDT 4.0 technologies used in power plants to overcome traditional challenges when dealing with condition assessment inspections. It will be show that no one technology can be the answer to all problems, but that it takes a team of engineers and NDT personnel to provide high quality assessments that provide meaningful results. We will also show how Internet of Things (IoT), Augmented Reality (AR), Artificial Intelligence (AI), Machine Learning and smart technologies combined with engineering analysis and materials science can create long lived, safe, and efficient power across many different power plant types.
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