RASPBERRY PI 5-BASED MULTICHANNEL MEASUREMENT SYSTEM FOR GAS-FLOW RESISTANCE AND TEMPERATURE MONITORING IN A NATURAL ZEOLITE PACKED BED

Grzegorz Walowski, Dorota Anders, Barbara Dybek, Vadym Ptashnyk, Serhiy Syrotyuk, Patryk Radek

Abstract


Background. Experimental characterization of granular beds for sorption thermal energy storage requires simultaneous measurement of gas-flow resistance and temperature using flexible multichannel data acquisition. This study developed a Raspberry Pi 5-supervised measurement system for a natural clinoptilolite packed bed.

Materials and Methods. Experiments were performed in a thermally insulated 0.5 m³ reactor containing a 0.4 m clinoptilolite bed with a particle-size fraction of 0.5–1.0 mm. Oxygen was used as the working gas. Pressure signals were processed by a miniSTM32-based subsystem, while ten Pt1000 sensors, ADG732 multiplexers, and an AD7124-4 converter were used for temperature monitoring. Three repeated series were performed at eight gas-flow settings. Pressure-flow data were analyzed using mean values, sample standard deviation, and linear regression; temperature-pressure relationships were evaluated by linear regression and Pearson correlation. A stationary two-dimensional MATLAB model was used to assess the thermal response.

Results. Functional operation of the platform was verified, including a 41-point comparison of three pressure channels showing close inter-channel agreement. Pressure drop ranged from 7.93 to 99.79 kPa, while the mean value increased from 25.49 to 93.41 kPa. Linear regression showed a significant positive pressure-flow relationship (R² = 0.840, p = 0.0014). Temperature remained within 16.83–16.92 °C, with no significant dependence on pressure drop. MATLAB-calculated mean temperatures differed from experimental means by no more than 0.08%, and the calculated temperature increase due to viscous dissipation was below 0.005 °C.

Conclusions. The developed system enables integrated measurement of gas-flow resistance and temperature in a natural clinoptilolite packed bed. Experimental and numerical results indicate that substantial changes in flow resistance were not accompanied by a detectable systematic temperature response under the investigated conditions. The architecture provides a basis for further studies of zeolite beds under controlled sorption conditions relevant to thermal energy storage.

Keywords: embedded measurement system, Raspberry Pi 5, data acquisition, gas-flow resistance, natural zeolite, packed bed, thermal energy storage.


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References


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DOI: http://dx.doi.org/10.30970/eli.35.15

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