This paper presents a computational model written in Modelica for the high pressure piston prover (HPPP) used as the national primary standard for high pressure natural gas flow metering in Germany. With a piston prover the gas flow rate is determined by measuring the time a piston needs to displace a certain volume of gas in a cylinder. Fluctuating piston velocity during measurement can be a significant source of uncertainty if not considered in an appropriate way. The model was built to investigate measures for the reduction of this uncertainty. Validation shows a good compliance of the piston velocity in the model with measured data for certain volume flow rates. Reduction of the piston weight, variation of the start valve switching time and integration of a flow straightener were found to reduce the piston velocity fluctuations in the model significantly. The fast and cost effective generation of those results shows the strength of the used modelling approach.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.