Pseudorandom numbers can affect the accuracy of a simulation by accidentally causes pattens that could be missed by the system. This could skew the accuracy.

Random numbers are used to determine the statistics and generate frequency rules. Pseudorandom numbers can skew the resultant frequencies and greatly alter the accuracy of simulation.

There are many methods of generating pseudorandom numbers. Some of them are middle square (not very good), Mersenne twister, linear congruential generator (one the oldest used in math libraries, but subject to sequential corellation artifacts), and cryptographically secure generators.

In computing, a hardware random number generator is an apparatus that generates random numbers from a physical process.

That is an engine model number of the Kohler engine on the generator. Look on the generator end or on the control box for a similar metal tag that says "Kohler Generator" and it will have something like "6.5R22" with a spec and serial number listed below that in separate fields on the nameplate.