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Functional principle of the gasQS static
21. Feb 2024
Bradley Visser, CTO of Mems AG, briefly explains the measuring principle of the gasQS static
The gasQS™ static is at the core of our range of gas quality measuring instruments. It is robust, accurate, fast, and is compensated for temperature and pressure. It is an excellent instrument for the measuring tasks it was designed for, but it also has its limits. In this article we look at the measuring principle of the gasQS static and explain why its use is limited to (quasi-)binary gas mixtures.
The gasQS static functions on the principle of a thermal conductivity measurement – a microheater suspended on a membrane heats the surrounding gas with a constant power, and the temperature of the membrane is measured by a pair of sensors located nearby. In the absence of forced convection (i.e. a gas flow) the temperature signal is directly dependent on the thermal conductivity of the gas – the more heat that is lost through the gas, the lower the signal from the temperature sensor.
Figure 1 - A schematic of the temperature distribution in the gas due to the microheater (left) and an image of the microthermal sensor (right).
Now, the thermal conductivity of a gas mixture is generally not of great interest to our customers, typically they would like to measure other properties such as the calorific value or methane number of the gas mixture, or the mole fraction of a particular component of the gas. In order to determine the relationship between the thermal conductivity and the customer-desired output property, each gasQS static is calibrated in-house with application specific gas mixtures. Below, an example calibration curve for a methane – hydrogen mixture at room temperature and pressure is shown.
Figure 2 - The characteristic curve of thermal conductivity of a methane-hydrogen gas mixture as a function of the hydrogen mole fraction.
This methodology functions very well for (quasi-)binary gas mixtures for which a direct relationship between the properties can be determined. For more complex gas mixtures, whereby the fractions of each gas may vary independently, it is not possible to define such a relationship. In such cases, we recommend that our customers look to our gasQS flonic for a solution to their requirements. With three independent gas property measurements, the gasQS flonic can easily handle more complex gas mixtures.
Differentiating between quasi-binary and multi-gas mixtures is important, for example, when working with natural gas. Natural gas is composed primarily of methane – at least 90% in most cases. The remainder is a mixture of longer chain hydrocarbons and other gases, which results in a large variance of the thermal conductivity and other gas properties. The composition and quality of natural gas supplied from a single source will generally remain constant over time, however a significant variance between different sources is to be expected.
Mixing a constant quality natural gas with another gas (e.g. hydrogen) is a perfect example of a quasi-binary gas mixture: an increase of the hydrogen fraction is accompanied by a reduction of the natural gas fraction, with each component of the natural gas scaling equally.
Mixing a natural gas
of varying quality with another gas on the other hand is an example of a
multi-gas mixture and would not be a suitable measurement task for a gasQS
static. In order to illustrate this point three different natural gas–hydrogen
mixtures are shown in the table below that have the same thermal conductivity.
Clearly in this case the measurement of thermal conductivity alone is not
sufficient to determine the molar concentration of hydrogen sufficiently
accurately.
Table 1 - Three natural gas-hydrogen mixtures with the same thermal conductivity. Large differences in the natural gas compositions are used to better illustrate the point. Such large fluctuations would not necessarily be expected at a single location.
| methane [mol%] | ethane [mol%] | CO2 [mol%] | propane [mol%] | hydrogen[mol%] | Thermal conductivity [mW m^-1 K^-1] |
|---|---|---|---|---|---|
| 94.9 | 3 | 1.1 | 1 | 0 | 31.52 |
| 90 | 5 | 3 | 1 | 1 | 31.52 |
| 85 | 7 | 3.88 | 2 | 2.12 | 31.52 |
In this particular case it would be possible to realise a solution to determine the mixing percentages of the gases with two gasQS statics, with one positioned before and the other after the mixing unit. This is an option that we will discuss in a future article.
In the plot below the response of a gasQS static calibrated for an average natural gas-hydrogen mixture is shown. The black 1:1 line represents the measurement of a natural gas-hydrogen mixture of the same quality as the calibration gas. The green dashed lines represent possible measurement results on account of reasonable changes of the quality of the natural gas compared to the calibration. For high hydrogen fractions the error becomes vanishingly small – the variation of the natural gas quality makes little difference when the thermal conductivity of the mixture is dominated by hydrogen!
Figure 3 - A comparison of the determined mole fraction of hydrogen versus true hydrogen mole fraction for an average natural gas for which the static has been calibrated (black line) and natural gases containing 100% and 85% methane, respectively (green dashed lines). The maximum errors for the extreme gas compositions are ±1.8% H2, respectively.
We hope that this article has helped to clear up any questions you may have regarding the measuring principle and the importance that calibration plays for the gasQS static. If you have any questions or feedback concerning this article or gasQS technology in general, then please don’t hesitate to contact us – we’d be happy to hear from you.
If you have any questions or feedback concerning
this article or gasQS technology in general, then please don’t hesitate to
contact us – we’d be happy to hear from you.