UC Ph.D. candidate’s algorithm saves companies time and money

A lot of time goes into making an engine. Before actually manufacturing the engine, engineers run designs through tests to ensure the engine will work once built. Between numerical and virtual analyses and experimental tests – processes that take weeks, sometimes months – time and money can start adding up. 

“When designing modern day engineering devices, you have to look at whole spectrum of design criteria or design matrix, and that’s going to take months,” said University of Cincinnati aerospace engineering Ph.D. candidate Himakar Ganti. “Numerical simulations take a lot of time, and they are extremely high fidelity. As a designer, you don’t always need that.”

Ganti recently won a poster award at the University of Kentucky’s Commonwealth Computational Summit for his work in developing an algorithm that can serve as an alternative to these lengthy numerical simulations. Ganti’s “quick-and-dirty” calculation gives designers the data sets they need, without all the fine details.

“Sometimes a good emulator can be just as detailed as a high-fidelity simulation. You can use data from numerical simulations and build an algorithm off that,” said Ganti. “Then you can predict a model and get a designer a data set in a couple of days rather than months.”

To create this algorithm, Ganti started simple, reducing the engine to one component: The injection velocity. Understanding the flow when diesel fuel is injected to an engine can allow engine designers to optimize the flow and make the process more efficient. Ganti analyzed the data points in actual flow processes simulated experiments and then developed the general framework of an algorithm to predict these same flows.