A New Rocket, Electric Soil, & AI That Predicts Chaos (Patreon)

NASA Tests New 3D-Printed Rocket Engine

Hot exhaust spews from NASA’s new 3D printed rocket engine. Image Credit: NASA.

NASA has tested its new 3D printed rocket propulsion system, dubbed the Rotating Detonation Rocket Engine (RDRE). Engineers at Marshall Space Flight Center in Huntsville, Alabama were able to successfully run the RDRE for over four minutes, producing over 25 KiloNewton of thrust force. Their aim is 44 KiloNewton, which would produce more thrust with less fuel than NASA’s traditional liquid rocket engines.

The new engine owes its efficiency to detonation that goes on continuously. For this, the incoming fuel and oxidizer are injected while they rotate around a ring-shaped channel. Each time circling fuel and oxidizer passes the igniter, the resulting combustion produces supersonic pressure waves of exhaust, which are pushed through the channel and out of the rocket to propel the vehicle forward. The engine is also noteworthy for being partly 3D printed from GRCop-42, a copper alloy developed by NASA to withstand extreme pressure and temperature without overheating.

You can watch a NASA video about the engine here, read a press release about it here, check out a NASA blog here and a detailed explanation of RDR engines here.  You can also read more about NASA’s recent progress with 3D printed rocket parts in other applications here.

Electronic “E-Soil” to Revolutionize Farming

Hydroponic (water-based) agriculture.

Researchers from Linköping University in Sweden have developed electrically conductive “e-Soil” which accelerates the growth of seedling in hydroponic gardening. Hydroponic gardening is a space-efficient method of plant cultivation in which seedlings are grown without soil in a suspension of nutrient substrate in water. It’s becoming more popular as the world has to both feed and host an increasing number of people.

The conductive e-Soil substrate’s main structural component is cellulose, an abundant polymer found in the cell walls of plants, and requires very little power to activate. Barley shoots whose root systems were electronically stimulated via the new “e-Soil” substrate grew on average 50% more in the same time period as regular hydroponically grown barley. The plants also used NO3 more efficiently than controls, meaning they need less fertilizer.

Press release here, paper here.

AI Accurately Predicts Chaos*

*But Does a Better Job When Trained on the Physics

Examples of chaotic attractors in the data set. Gilpin, William (2023), Phys. Rev. Research 5 043252

Chaotic systems are famous for the butterfly effect, in which an initial small change grows exponentially in time. However, chaotic systems are still perfectly deterministic in that their dynamics is entirely predictable given the exact initial conditions. This raises the interesting question of whether it is possible to train an artificial intelligence to predict chaos because it’s deterministic, or whether it’s impossible because extrapolating the training data will inevitably lead to exponentially large errors.

William Gilpin of the University of Texas at Austin has put the question to test with the largest-scale study to date on forecasting chaos. He compared 24 state-of-the-art methods on 134 simple systems with 17 forecast metrics. His study reveals that the large-scale domain-agnostic (non-physically motivated) forecast methods consistently produce accurate predictions over up to two dozen Lyapunov times, that is the time-scale for the exponential divergence to happen. Still, over longer periods of time, the physically informed hybrid computational methods win out, retaining a comparative advantage.

So physicists aren’t out of a job – yet.

Press release here, paper here, and watch the author’s video on X here.