Ivan Maldonado

UTK nuclear engineering

Robust computational tools
for nuclear power

There can be little argument that what the world needs now are considerably more viable options for cost-effective, sustainable, carbon-free electrical energy.

Although no other country produces as much electricity from nuclear power as the U.S., that output comprises only 20 percent of our total requirement. In contrast, France produces 80 percent of its electricity from nuclear plants that have operated safely and reliably for many years. To achieve this higher percentage, the French take advantage of uniform management, operations, and safety systems for reactors with standardized designs that function as state utilities. If the U.S. is to boost growth of its own industry with emerging, competitive designs—while keeping efficiency and safety concerns paramount—it must address the critical need for a new generation of robust computational tools capable of predicting and tracking the status and performance of every single nuclear fuel pin in the core of a reactor—before, during, and after operation.

That is where the work undertaken by JDRD researcher Ivan Maldonado and graduate student Brenden Mervin comes in; and they are on course to bring about fundamental and radical change. Exploiting a unique approach and solution developed by their partnering LDRD team, led by John Wagner, they propose to develop and test highly accurate and fine-grained methods to analyze and predict the state of each fuel pellet from among the huge numbers found in the fuel core of modern nuclear power plants. Since these methods will eventually make it possible to precisely determine the composition of each fuel pin, they also have important implications for the larger issue of nonproliferation of nuclear material by providing for accounting, controls, and safeguards.

Maldonado brings to this collaboration exceptional research and industrial experience in computational reactor physics and nuclear fuel management that will readily enable transfer of the new method to production.

Additional information about Maldonado can be found on his departmental web page, G. Ivan Maldonado

Above: Cross sections of a fuel pin cell, a fuel assembly lattice, and quarter core. Instead of using the multi-level, coarse-grained represented by the latter two figures, the collaborating research projects employ the tremendous power of Jaguar's advanced petaflops processors at ORNL to model and simulate each and every fuel pellet and pin cell as depicted in the first figure.