FLF’s Machine 3 has been constructed to electromagnetically launch projectiles at hypervelocities and consists of six banks of capacitors arranged radially around a central vacuum chamber where the experiment takes place. The capacitors are charged up to 200,000 Volts over the period of a minute and the stored electrical energy is discharged in less than two microseconds. This generates up to 14 million Amps which create intense magnetic fields that launch the projectile into the center at velocities approaching 20 km a second, delivering 200 KJ of kinetic energy.
FLF tested the firing of three limbs last year and has now successfully commissioned the full, six limb machine and started science experiments. Each discharge is equivalent to 500 simultaneous lightning strikes. A total of 2.5 MJ are used for every discharge.
One of the challenges in this design is ensuring synchronicity in the firing of all six limbs that has to have nanosecond level accuracy. The electrical energy is stored in 192 capacitors that are arranged in pairs and each of the 96 pairs is controlled by a bespoke switch which is capable of holding off the voltage and transferring the huge currents involved. After the firing, Spectrum
M2i.4912-exp digitizer cards are used to acquire hundreds of machine diagnostics from each capacitor and switch along with numerous probes in the limbs covering current and voltage readings with a sampling rate of 10 MS/s (100 ns time interval). 32 cards are linked together in two banks of 16 using Spectrum’s Star-Hub feature to ensure synchronicity across all 256 input channels. This configuration provides the flexibility of adding additional channels if required in the future.
“This synchronization feature was a key reason why we chose Spectrum,” added Paul Holligan. “Everything happens in nanoseconds so accuracy of firing and data gathering is paramount. We could not have any possibility of errors coming in from this equipment as every firing provides us with invaluable data and we have to be confident in the quality of that data.”