DESIGN, SIMULATION AND FABRICATION OF A COOLER AND CONTROLLER FACILITATING STUDY OF MAGNETIC FIELD EFFECTS ON NUCLEATION IN SUPER COOLED BULK WATER
DESIGN, SIMULATION AND FABRICATION OF A COOLER AND CONTROLLER FACILITATING STUDY OF MAGNETIC FIELD EFFECTS ON NUCLEATION IN SUPER COOLED BULK WATER
Date
2020
Authors
Francis, Sean
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Jun, Soojin
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Biological Engineering
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In this paper the effects of magnetic fields on supercooled water were investigated for application to a food supercooling storage technology that uses magnetic fields. Current cold storage technologies were reviewed and compared to supercooled storage, highlighting the latter’s longer storage periods without changing food texture. Literature on supercooled water was also reviewed, featuring crossover and relaxation phenomena definitions used in waters possible “liquid-liquid” critical point. Using equations from a previous Monte Carlo study, a correlation between magnetic fields and waters temperature was proposed, showing the magnetic moment between two water molecules in a given magnetic field will decrease with temperature. Furthermore, it was shown that the magnetic moment interaction between water molecules and a 0.6 T magnetic fields imparted ~-2.3*〖10〗^(-5) J/mol energies at -10°C.
With this model as a guideline, a cooling device (Supercooler 2) and controller were created to investigate supercooled waters interaction with magnetic fields. Energy balance calculations were used to define hardware specifications before creating a CAD model. Computational fluid dynamic (CFD) analysis on the model showed thermal gradients were minimized when simultaneously drawing heat from the top and bottom of the sample, validating this design feature. The main chassis and custom designed integral components were 3D printed from the CAD and assembled with a GMW 3470 electromagnet to create Supercooler 2 (Appendix F). The Supercooler 2 performance validation testing showed the sample gradient was 0.6°C when cooled bi-directionally and 1.19°C unidirectionally. Further analysis fitted a linear model to sample cooling rates where R^2=0.995 could be obtained with 95% prediction interval=±0.33 °C for 5 repeated replicates, demonstrating the linear temperature control accuracy and precision.
A preliminary study using 20 samples with pulsed magnetic fields from 1-100 Hz and 10-600 mT had a normally distributed nucleation temperature with mean= -7.39 and standard deviation=0.307°C. Linear regression models were fit to the results, showing positive correlation between increasing frequencies and supercooling magnitude. Negative correlation was shown between increasing field strength and supercooling magnitude. The independent variables, magnetic frequency and magnitude, were changed simultaneously and thus correlation with supercooling magnitude was ambiguous. This experimental method saved time and provided background data. Furthermore, outliers were discovered and the data provided by this study highlighted a group treated with 70 mT at 20 Hz. This group’s nucleation temperatures were 2.11 standard deviations away from the mean, while the average for the remaining dataset was 0.739, and therefore, it is suggested that the group be investigated for future studies.
The subsequent High Field Study improved upon critical experimental methods and process controls. This study focused on experimental groups treated with 600 mT 1 Hz fields and Control groups with no treatment. In the midst of the High Field Study, the PID process variable location was changed to improve smoothness of the sample temperature cooling profile. The result was a separation of groups; two Control groups and two Experimental groups. All groups were found to have the same cooling rates and steady state temperatures. This was shown with 95% prediction intervals=±0.68°C and ±0.82°C for steady state and linear cooling regimes, respectively. This included 16 Control groups (no magnetic field treatment) and 13 Experimental groups treated with 600 mT 1 Hz fields. Experimental groups were 1.5 to 2.9 times more likely to have a nucleation event than Control groups. The temperature profiles were statistically the same between all groups, therefore, the only remaining variable was the difference in treatment. Therefore, the Experimental groups had an increased nucleation probability compared to the control group because of the 600 mT 1 Hz treatment.
Description
In this paper the effects of magnetic fields on supercooled water were investigated for application to a food supercooling storage technology that uses magnetic fields. Current cold storage technologies were reviewed and compared to supercooled storage, highlighting the latter’s longer storage periods without changing food texture. Literature on supercooled water was also reviewed, featuring crossover and relaxation phenomena definitions used in waters possible “liquid-liquid” critical point. Using equations from a previous Monte Carlo study, a correlation between magnetic fields and waters temperature was proposed, showing the magnetic moment between two water molecules in a given magnetic field will decrease with temperature. Furthermore, it was shown that the magnetic moment interaction between water molecules and a 0.6 T magnetic fields imparted ~-2.3*〖10〗^(-5) J/mol energies at -10°C.
With this model as a guideline, a cooling device (Supercooler 2) and controller were created to investigate supercooled waters interaction with magnetic fields. Energy balance calculations were used to define hardware specifications before creating a CAD model. Computational fluid dynamic (CFD) analysis on the model showed thermal gradients were minimized when simultaneously drawing heat from the top and bottom of the sample, validating this design feature. The main chassis and custom designed integral components were 3D printed from the CAD and assembled with a GMW 3470 electromagnet to create Supercooler 2 (Appendix F). The Supercooler 2 performance validation testing showed the sample gradient was 0.6°C when cooled bi-directionally and 1.19°C unidirectionally. Further analysis fitted a linear model to sample cooling rates where R^2=0.995 could be obtained with 95% prediction interval=±0.33 °C for 5 repeated replicates, demonstrating the linear temperature control accuracy and precision.
A preliminary study using 20 samples with pulsed magnetic fields from 1-100 Hz and 10-600 mT had a normally distributed nucleation temperature with mean= -7.39 and standard deviation=0.307°C. Linear regression models were fit to the results, showing positive correlation between increasing frequencies and supercooling magnitude. Negative correlation was shown between increasing field strength and supercooling magnitude. The independent variables, magnetic frequency and magnitude, were changed simultaneously and thus correlation with supercooling magnitude was ambiguous. This experimental method saved time and provided background data. Furthermore, outliers were discovered and the data provided by this study highlighted a group treated with 70 mT at 20 Hz. This group’s nucleation temperatures were 2.11 standard deviations away from the mean, while the average for the remaining dataset was 0.739, and therefore, it is suggested that the group be investigated for future studies.
The subsequent High Field Study improved upon critical experimental methods and process controls. This study focused on experimental groups treated with 600 mT 1 Hz fields and Control groups with no treatment. In the midst of the High Field Study, the PID process variable location was changed to improve smoothness of the sample temperature cooling profile. The result was a separation of groups; two Control groups and two Experimental groups. All groups were found to have the same cooling rates and steady state temperatures. This was shown with 95% prediction intervals=±0.68°C and ±0.82°C for steady state and linear cooling regimes, respectively. This included 16 Control groups (no magnetic field treatment) and 13 Experimental groups treated with 600 mT 1 Hz fields. Experimental groups were 1.5 to 2.9 times more likely to have a nucleation event than Control groups. The temperature profiles were statistically the same between all groups, therefore, the only remaining variable was the difference in treatment. Therefore, the Experimental groups had an increased nucleation probability compared to the control group because of the 600 mT 1 Hz treatment.
Keywords
Food science,
Biophysics,
Bioengineering
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82 pages
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