Both spatially and financially, nuclear reactors are costly projects — especially when deterred by natural earthly causes. In particular, nuclear infrastructure can easily be disrupted by seismic activity.
To address the issue, University of Wyoming researcher Ankit Saxena recently received a two-year grant of nearly $200,000 from the National Science Foundation in order to pursue the study of particle dampers.
According to the university release, the project’s aim is to “revolutionize the design of particle dampers using topology optimization, an advanced engineering design technique” in the hopes of affording nuclear infrastructure better protection from seismic waves.
Conventional particle dampers involve a cavity in which entrapped particles can sense and respond to external vibrations, dissipating any interference as it arrives. Unfortunately, the development of these dampers has proved complex and expensive in the past, so Saxena intends to simplify and optimize their design with an emphasis on dispelling seismic frequencies.
Meanwhile, Saxena and his team aim to establish research partnerships with universities across the United States, boosting the project’s visibility and scope in the long term, per the Wyoming release.
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Although solar and wind power tend to be the most commercially viable options when it comes to renewable energy, nuclear power isn’t far behind. While still an imperfect solution — considering the massive expenses required in developing nuclear reactors and the radioactive waste by-product of nuclear fission — nuclear plants are capable of yielding massive amounts of energy with far less pollution than that generated through the combustion of fossil fuels. The latest research grant may help bolster the reliability of nuclear energy in the face of seismic activity over the years to come.
“While this NSF project specifically focuses on seismic protection of nuclear power plants, the topology optimization-based particle damper design methodology … has broad applicability across a wide range of real-world systems,” Saxena told the university.
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