Simulating Solutions to Significant Situations

As engineering becomes more complex, so do the solutions to its problems. 

Researchers at the University of Pittsburgh Swanson School of Engineering’s Department of Mechanical Engineering and Materials Science (MEMS) are turning toward computational science, artificial intelligence (AI), and data-enabled engineering to meet the challenge by founding their own computational group. 

Computational science, AI, and data-enabled engineering combine multiple areas of research like quantum physics, applied mathematics, and high-performance computing to allow engineers to perform experiments in places where they’re not possible. 

“Much of design optimization is a computational problem,” said Hessam Babaee, MEMS associate professor and an expert in applied math. “You don’t go and try building an airfoil using different geometries and testing it in a wind tunnel. That’s obviously extremely expensive, but you can now do that in the computer.” 

This area of recent growth in the department has become one of its core pillars of research, expanding now into quantum computing. Because of the work of its leading faculty and graduate students, it’s established top research competencies for computational science and simulation in the country.

“What’s happening inside our department is very exciting,” said Department Chair Brian Gleeson. “Computational science and simulation is the future of engineering and we’re at the forefront of it.“

Bridging Computer Science and Engineering

Computational science flourishes when different strengths all take part in the process. 

The MEMS professors behind the group, including Babaee, each bring a unique speciality: 

• Distinguished Professor and James T. MacLeod Chair Peyman Givi: expertise in Computational Transport Phenomena
• Assistant Professor Juan José Mendoza Arenas: expertise in Quantum Physics
• Associate Professor and William Kepler Whiteford Faculty Fellow İnanç Şenocak: expertise in High Performance Computing

These different elements of scientific computing help the process flow more efficiently while opening opportunities for further research. Because of their expertise, these professors were able to expand their computational group outside the lab, offering new classes within the department to introduce students to these concepts and applications. 

“These courses are an extension of the engineering to these areas of computational science and computational methods,” Senocak explained.

Mendoza Arenas added that it’s important for students to see how the calculation is being done as well as the underlying physics of the result. 

Success in Simulation

Graduate students involved in the group have seen tremendous success upon completion of their PhD program. 

“The power of our group can easily be measured by the fact that all of our students that graduated – they are bombarded with offers,” Givi said. 

Michael Donello, a research scientist at NASA Langley Research Center, was part of the computational group while he was in the PhD program in Pitt’s Department of Mechanical Engineering and Materials Science. He credits his work within the group for his current position. 

“I was always interested in programming, even as an undergraduate student at Pitt,” Donello said. “It gives you the opportunity to solve complex engineering problems that require a multidisciplinary approach.”

When part of the group, Donello worked mostly in reduced order modeling for computational fluid dynamics. His final project ultimately ended up being funded by NASA, as well as being the center of his program and thesis. 

However, for the group, job offers aren’t the only end goal. 

“Our research, especially as it continues to grow and evolve, will help others,” Mendoza Arenas said. “And I believe that principal will encourage others to join in our goal.”