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Conversion of a piston--cylinder dimensional dataset to the effective area of a mechanical pressure generator



Patrick Egan, Eric S. Stanfield, John R. Stoup, Christopher W. Meyer


Recent developments in diameter metrology at NIST have improved the dimensional characterization of piston–cylinder assemblies (PCAs) to unprecedented precision. For the newest generation of PCA, the standard uncertainty on measurement of outer diameter is 12 nm, while uncertainty on measurement of inner diameter is 14 nm. With a high-accuracy dimensional dataset in hand, the task of determining the pressure generated by a specific PCA is reduced to converting diameter (and straightness and roundness) to effective area (and distortion coefficient). Details on how this was done for the artifact PCA2062 are described. PCA2062 was dimensioned in 2017 and 2020; the area repeated within 0.2 × 10-6 · A0. The calculation produced estimates of fall-rate and rotation-decay that agree with experimental observations within 12 %. Fall-rate is proportional to the square of gap-width, so the agreement between calculation and measurement validates the dimensional estimate of gap-width within (36 ± 42) nm, where the 42 nm standard uncertainty is governed by the present state of flow theory. The piston-gauge model is buttressed by three comparison tests against a laser barometer, which support a view that PCA2062 is linear and reproducible within 0.2 µPa/Pa. Finally, an estimate of uncertainty in the effective area of a dimensioned artifact is provided: as expected, diameter measurement is the main culprit, but there are open questions with the flow model that preclude an accurate evaluation of the distortion coefficient. For the 530 kPa operating range of PCA2062, distortion is not a significant problem, but the effect would be dominant in assemblies operating 1 MPa and above.
NCSLI Measure


Egan, P. , Stanfield, E. , Stoup, J. and Meyer, C. (2023), Conversion of a piston--cylinder dimensional dataset to the effective area of a mechanical pressure generator, NCSLI Measure, [online], (Accessed July 14, 2024)


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Created December 20, 2023, Updated December 26, 2023