"As far as we know, there's nothing like this in Earth orbit so far," says Holger Hermanns, a professor of computer science at Saarland University. In collaboration with his doctoral student Gilles Nies and student Marvin Stenger, Hermanns has developed a procedure that allows for much more accurate predictions of the amount of battery power needed for a particular operation in space. Until now, space logisticians have had to make their predictions using excessively large and heavy batteries, taking up valuable space needed for other equipment and experiments. "Among other things, not enough attention has been paid to the recovery effect, a well-known phenomenon in mobile phones. If the phone dies due to a dead battery, often, after waiting just a few minutes, if you can get the phone back on, you can use it, at least for a short time," says Hermanns. The new battery model can be used to monitor the exact amount of power currently available and determine how much of it is present in a chemically bound form—that is, not immediately usable. This allows computer scientists to calculate the probability of the battery running out of charge at any given time.
The findings of the computer scientists in Saarbrücken can also be applied on Earth. "Batteries are ubiquitous—and a good battery model helps in many situations," says Holger Hermanns. Consider, for example, the energy demands of an electric car: "Until now, we could only answer the question: Under ideal conditions, will the battery charge be sufficient for this electric car to reach Frankfurt Airport? Now we can see if the air conditioning system can operate in such a way that you have a greater than 99 percent chance, at all times, of reaching your flight on time with the current charge," Hermanns explains.
Siemens and NVIDIA accelerate computational lithography by up to 17 times with Calibre and cuLitho
Siemens has announced new advancements in its collaboration with NVIDIA to accelerate computational lithography processes used in the manufacturing of advanced semiconductors.
The integration of NVIDIA cuLitho, a CUDA-X library for GPU-accelerated computational lithography, with the...
