The Stanford Predictive Science Academic Alliance Program (PSAAP) is using computers to model the physical complexities of the hypersonic environment –specifically, how fuel and air flow through a hypersonic aircraft engine, known as a scramjet engine. They have a five-year, $20 million U.S. Department of Energy grant.
The program focuses on what is known as the scramjet’s ‘unstart’ problem. “If you put too much fuel in the engine when you try to start it, you get a phenomenon called ‘thermal choking,’ where shock waves propagate back through the engine,” he explained. “Essentially, the engine doesn’t get enough oxygen and it dies. It’s like trying to light a match in a hurricane.”
Modeling the unstart phenomenon requires a clear understanding of the physics and then reproducing mathematically the immensely complex interactions that occur at hypersonic speeds.
PSAAP’s principal goal is to try to quantify those uncertainties – the known unknowns – so that scramjet engineers can build the appropriate tolerances into their designs to allow the engines to function in extraordinary environments.
Measuring what the engineers call epistemic uncertainty is common in real-world experimental work, where researchers typically note uncertainties in their measurements in the form of bars that have upper and lower limits. But hard numbers generated by computer models do not have uncertainty bars and therefore can take on an unwarranted, potentially dangerous air of certainty.
“We have asked experimentalists for a long time to give us uncertainty bars on their measurements,” said Moin. “But I think the time is right to ask the computationalists to do the same.”