Different input mathematical model of temperature, pressure, and flow for measurement uncertainty by Monte Carlo method

Bin Ren

doi:10.1117/12.2679570

18 July 2023 Different input mathematical model of temperature, pressure, and flow for measurement uncertainty by Monte Carlo method

Bin Ren

Author Affiliations +

Proceedings Volume 12722, Third International Conference on Mechanical, Electronics, and Electrical and Automation Control (METMS 2023); 127220A (2023) https://doi.org/10.1117/12.2679570
Event: International Conference on Mechanical, Electronics, and Electrical and Automation Control (METMS 2023), 2023, Hangzhou, China

Abstract

Four temperatures, four pressures and two flows are included necessarily in one whole operating condition for a heat exchanger, and they influence each other. They are also essential to calculate and report heat capacity Q and overall heat transfer coefficient k. It is important for Monte Carlo method to investigate different models of production of mass random data. In the present work, an input model of a uniform distribution was compared with that of a normal distribution for the same heat exchanger under the same reference operating condition. They were employed independently and respectively to produce 100,000 sets of random operating conditions on the base of a real test result. Though input temperature and pressure were both subject to the uniform distribution, the specific heat, density, thermal conductivity and fluid viscosity of the tested fluid did not necessarily follow a uniform distribution. The comparison showed that calculated Q, k and other relative parameters all were subject to the normal distributions; furthermore, the input model of normal distribution gives out the measurement uncertainty of 7374W, 58 W/ m2·K for Q, k, while that of uniform distribution lead to the measurement uncertainty of 7361W, 58 W/m2 K, respectively. Obviously, the difference is less than 1%, therefore they are considered to create the same measurement uncertainty for heat exchanger.

Citation Download Citation

Bin Ren "Different input mathematical model of temperature, pressure, and flow for measurement uncertainty by Monte Carlo method", Proc. SPIE 12722, Third International Conference on Mechanical, Electronics, and Electrical and Automation Control (METMS 2023), 127220A (18 July 2023); https://doi.org/10.1117/12.2679570

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KEYWORDS

Statistical analysis

Measurement uncertainty

Monte Carlo methods

Temperature metrology

Data modeling

Viscosity

Mathematical modeling

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