University of California, Berkeley
As a high school student, Mario Ortega wanted to become a lawyer. He saw a future where he could help people and earn a stable income.
Ortega spent extracurricular hours participating in mock trial but also fell in love with word problems in advanced placement calculus classes, leading him to consider a career in science or engineering. A high school counselor reminded him that law school required an undergraduate degree and advised him to start with engineering.
Ortega, the oldest child of Mexican immigrants and the first in his family to go to college, headed to the University of New Mexico in his native Albuquerque and studied nuclear engineering. He knew of the high-quality math and science work done at Sandia and Los Alamos, the two Department of Energy national laboratories in his backyard. He was also drawn to a field strongly connected with society. “The thing about nuclear engineering is that you can’t hide from the impact,” he says. “I was getting this really great technical education while also being constantly made aware that when I solve this very particular equation it could possibly impact the world in ways that nobody can imagine.”
By his senior year, he had taken computational methods courses to learn Monte Carlo methods (which rely on random sampling) and deterministic ways (which proceed in a preplanned manner) to study the neutron transport equation, the accounting process for these subatomic particles in a nuclear reactor. As with calculus, he soon was hooked on solving problems with computers. “It’s almost like there’s music in the equations,” he says, and they provide clues about how to solve them. He started doing computational research, which led to internships at Sandia National Laboratories.
Although it was eye-opening to work with codes that scientists and engineers use day to day, Ortega “wanted to be the person who makes these codes. I want to know how everything works inside.” He stayed at UNM and completed a master’s degree.
When Ortega scanned job ads he soon realized the positions that interested him required a Ph.D. He ended up at the University of California, Berkeley, where a DOE Computational Science Graduate Fellowship supports his doctoral research.
Every time a neutron splits an atomic nucleus, it produces more neutrons. If those new particles cleave other atomic cores, the reaction sustains itself. At Berkeley, Ortega has focused on solving critical equations that tell engineers whether a nuclear system can support a self-sustaining chain reaction. It’s a complex problem with seven independent variables. To compute the solution, he considers each part geometrically, carving it into cross-sections that are statements of how likely a neutron is to cause fission. But the energy and direction of the neutron matter, too. “Before you know it you have millions of little slices to express a nuclear reactor or some sort of nuclear experiment,” Ortega says.
He puts all of this information into a large matrix equation, which he’s solved using a range of high-performance computing resources at Lawrence Livermore National Laboratory. The mathematics requires developing iterative methods, which start with an initial guess that’s repeatedly refined over all the individual slivers until it produces a solution. But Ortega also has to ensure that the way he carves up this problem produces results that match real-world physics.
In his 2017 practicum at Sandia in New Mexico, Ortega used a similar strategy to look at charged radiation, which, unlike neutrons, added magnetic and electric fields to the problem. In 2018, he spent the summer working with his Livermore collaborators on ways to accelerate the computational methods developed in his Ph.D. research and on better understanding how generalizable and flexible they are.
Ortega will graduate in summer 2019 and hopes to return to a national lab as a postdoctoral researcher. “It’s a good mix of wonderful research along with a group of people who are paid to think about ‘how does this help the U.S.? How does this help the world?’ ” Ortega says. “The part of me that wanted to go to law school is very happy being in the middle – not only being able to talk math and science but hopefully even being able to talk policy eventually.”
Image caption: At the University of California, Berkeley, Mario Ortega has solved equations that tell engineers whether a nuclear system can support a self-sustaining chain reaction. This two-dimensional slice from a mixed oxide-plutonium fuel assembly for a nuclear reactor maps areas of higher neutron density (yellow and orange) next to areas of lower neutron density (blues). Credit: Mario Ortega.