A fuel leak and then an engine problem during final liftoff preparations led NASA to call off the launch of its mighty new moon rocket Monday on its debut flight with three test dummies aboard.

The next launch attempt will not take place until Friday at the earliest and could be off until next month.

When NASA's Artemis 1 lunar mission takes off on August 29, on board will be four science experiments—including one from Canada.

UBC pharmaceutical sciences professor Dr. Corey Nislow is sending yeast and algae cultures into space, in a pod not much bigger than a shoebox, to study the effects of cosmic rays and near zero gravity on living organisms.

When the spacecraft returns after its uncrewed 42-day orbit around the Moon, Dr. Nislow will get his samples back, along with the information they contain.

In this Q&A, he explains what the NASA project could mean for medical advances on Earth and in space.

What is it exactly that you're sending into to space, and why?

We chose to study Chlamydomonas reinhardtii—a single-cell green alga—and 6,000 yeast mutants.

A test flight of NASA's powerful new Moon rocket may be possible on Friday, officials said, after the US space agency scrubbed Monday's launch because of an engine issue.

"Friday is definitely in play," Artemis 1 mission manager Mike Sarafin told reporters.

"They're still holding in the launch countdown configuration and we're preserving the option for Friday."

© 2022 AFP

A spacecraft attitude kinematics model, attitude measurement model, and filter algorithm are three important parts in spacecraft attitude determination, and a high-precision filtering algorithm is the key to attitude determination. The classical sigma-point Kalman filter (SPKF) is widely used in a spacecraft state estimation area with the Gaussian white noise hypothesis.

Although the SPKF algorithm performs well in ideal Gaussian white noise, the actual operating conditions of the spacecraft in orbit are complicated. Space environmental interference, solar panel jitter, and flicker noise will make the noise no longer meet the Gaussian distribution and present a heavy-tailed non-Gaussian situation, where the classical SPKF filtering method is no longer applicable, and there will be obvious accuracy degradation or even filtering divergence.

In a research paper recently published in Space: Science & Technology, a joint team from the Army Engineering University of PLA and Chinese Academy of Military Science, proposed a robust Centered Error Entropy Unscented Kalman Filter (CEEUKF) algorithm by combining the deterministic sampling criterion with the centered error entropy criterion.