When Michel Seiler came to Old Dominion University three years ago, he was thrilled to have access to the Virginia Modeling, Analysis and Simulation Center.

Seiler, the endowed chair of real estate and economic development at ODU and the director of the school’s Institute of Behavioral and Experimental Real Estate, wanted to study patterns in the housing market, and he said VMASC had the perfect tools for his research.

Many people immediately think of modeling and simulation’s military uses, but there are many more uses for the technology than that, he said.

“You can absolutely use this to solve real-world problems,” he said.

Using VMASC technology, Seiler, along with Andy Collins, a research assistant professor at VMASC, and Nina Fefferman, an epidemiologist, set out to study the real-world problem of strategic mortgage defaults — which occur when homeowners voluntarily stop paying their mortgages — to find out how such defaults affect the real estate market.

“We’ve been doing a lot of studies on the concept of strategic default,” Seiler said. “We find that it is an increasing problem in society.”

On Monday, the group was recognized by Gov. Bob McDonnell for its use of modeling and simulation technology on the project, titled “Strategic Mortgage Defaults — An Epidemiological Approach.”

The project was named the winner of the cross-boundary collaboration in modeling and simulation category of the Governor’s Technology Awards, which honors technology initiatives in the public sector throughout Virginia.

Seiler said he and others in the group used VMASC technology to create an environment in which they could study the effects of strategic defaults without suffering real-world consequences.

“We couldn’t just unleash a theory into the world,” he said. “We created an artificial world in the modeling and simulation environment. If we were wrong (about something), we would just crash the model, not the real world.”

In the project, Seiler and his colleagues studied strategic default as if it were a disease spreading across the housing market.

He said homeowners could “catch the disease” from neighbors or from real estate experts who see it as option for people who are struggling to pay their mortgages.

If a homeowner sees a neighbor default without consequences, Seiler said, he or she is more likely to do the same.

“When you think the system is not fair, it changes your perspective,” he said.

The model also showed how the housing market would be affected if the default disease spread quickly.

“If too many people adopt that philosophy, it’s going to kill the market,” Seiler said.

Using the model, the group also adopted a hypothesis for how to suppress the number of defaults.

Seiler said the most effective way to stop defaults from destroying the housing market is to shorten the time it takes for the homeowners to be taken out of their homes.

“It’s not good how the system is working at all,” he said.

Seiler added the modeling and simulation technology was essential to the project and research.

While he appreciates the award, he said, he just enjoys what he does and hopes it will make a difference.

“To me, I love the work,” Seiler said. “It’s about an incredibly important topic in today’s society.”