Computerized, Transient Hot-Wire Thermal Conductivity (HWTC) Apparatus For Nanofluids The 6th WSEAS International Conference on HEAT and MASS TRANSFER (WSEAS - HMT'09) Ningbo, China, January 10-12, 2009 M. Kostic & Kalyan C. Simham Department of Mechanical Engineering NORTHERN ILLINOIS UNIVERSITY www.kostic.niu.edu www.kostic.niu.edu

Overview INTRODUCTION OBJECTIVE THEORY OF HOT-WIRE METHOD PRACTICAL APPLICATION OF HOT-WIRE METHOD DESIGN OF HOT-WIRE CELL INSTRUMENTATION DATA ACQUISTION CALIBRATION UNCERTAINTY ANALYSIS RESULTS CONCULSIONS RECOMMENDATIONS www.kostic.niu.edu

INTRODUCTION Nanofluids are colloidal suspensions of nanoparticles, nanofibers, nanocomposites in common fluids They are found to have enhanced thermal properties, especially thermal conductivity Thermal conductivity values of nanofluids may be substantially higher than related prediction by classical theories No-well established data or prediction formula suitable to all nanofluids Experimental thermal conductivity measurement of nanofluids is critical www.kostic.niu.edu

Table 1: Summary of landmark development in nanofluids * www.kostic.niu.edu * (reprinted with permission; reference listed within this table are with respect to (Manna et al 2005))

Nanofluid Preparation Methods One Step (Direct Evaporation and Condensation) Method Two Step Method or Kool-aid Method Chemical Method Fig1: Improved new-design for the one-step, direct evaporation-condensation nanofluid production apparatus, (Kostic 2006) www.kostic.niu.edu

Thermal Conductivity Material Property Determines ability to conduct heat Important for thermal Management Classification of Thermal Conductivity Measurement Techniques for Fluids Horizontal Flat Plate Method Vertical Coaxial Cylinder Method Steady State Hot-Wire Method Steady State Methods Line Source (Hot-Wire) Method Cylindrical Source Method Spherical Source Method Plane Source Method Non-Steady State Methods www.kostic.niu.edu www.kostic.niu.edu

Transient Hot-Wire Method for Fluids Advantages: Fast and Accurate Minimum Conduction and Radiation losses Minimize (or even avoid) Convection Classification of Hot-Wire Methods Standard Cross Wire Method Single Wire, Resistance Method Potential Lead Wire Method Parallel Wire Method www.kostic.niu.edu

OBJECTIVE Design Device to Suspend Hot-Wire Reduce Nanofluid Sample Size Minimize End Errors Uniform Tension on Hot-Wire Separate Wires for Power and Voltage Monitor Temperature Mechanism to Calibrate Hotwire Tension Flexibility for Cleaning and Handling Design www.kostic.niu.edu

OBJECTIVE Instrumentation Data Acquisition Calibration Electrical Circuit Flexible Connections Instrumentation Optimize to Reduce Noise Develop Program Data Acquisition Calibration Standard Fluids Uncertainty Analysis Thermal Conductivity www.kostic.niu.edu

Principle of Hot-Wire Method An infinitely long and thin, ideal continuous line source dissipating heat into an infinite medium, with constant heat generation General Fourier’s Equation Boundary Conditions Where T is the final temperature, T0 is the initial temperature, r is the radial distance and t is the time q is heat flux is thermal diffusivity kf is Thermal Conductivity and Ideal case: Line source has an infinite thermal conductivity and zero heat capacity www.kostic.niu.edu

series expansion of the exponential integration The temperature change at a radial distance r, from the heat source is conforms to a simple formula by applying boundary conditions series expansion of the exponential integration =0.5772 is the Euler’s constant Where, At any fixed radial distance, in two instances in time the equation, the temperature change can be represented as www.kostic.niu.edu

Practical application of hot-wire method A plot of temperature against the natural logarithm of time results in a straight line, the slope being propositional to kf Thermal Conductivity Practical application of hot-wire method The ideal case of continuous line is approximated with a finite wire embedded in a finite medium www.kostic.niu.edu Figure 2.1 Typical plot of temperature change against time for hot-wire experiment (Johns et al 1988)

Nanofluids Thermal Conductivity Methods By Other Authors Author, Year Nanofluid Thermal Conductivity Measurement Method Wang et al (1999) Horizontal flat plate method Lee et al (1999), Yu et al (2003) and Vadasz (2006) Vertical, single wire, hot-wire method Assael et al (2004) Two wires, hot-wire method Manna et al (2005) Thermal comparator Ma (2006) Horizontal, single wire, hot-wire method Simham (2008) www.kostic.niu.edu

Hot-wire Method for Nanofluid Nanofluids are electrically conducting fluids Availability of nanofluids Thermal expansion of wire Cleaning of the cell Hot-Wire Method for Electrically Conducting Fluids Problems identified by Nagasaka and Nagashima (1981) Possible current flow through the liquid, resulting in ambiguous measurement of heat generated in the wire, Polarization of the wire surface, Distortion of small voltage signal due to combination of electrical system with metallic cell through the liquid. www.kostic.niu.edu

is due to the presence of the insulation layer on the wire Where, is due to the presence of the insulation layer on the wire shifts (i.e. offsets) the plot of against ln (t), without changing the slope www.kostic.niu.edu

Insulation Coating Influence on Thermal Conductivity Measurement Yu and Choi (2006) The results of numerical simulation and experimental test show that, for most of the engineering applications, the relative measurement error of the thermal conductivity caused by the insulation coating are very small if the slopes of the temperature rise – logarithmic time diagram are calculated for large time values No correction to insulation coating is necessary even for the conditions that the insulation coating thickness is comparable to the wire radius, and that the thermal conductivity of the insulation coating is lower than that of the measured medium www.kostic.niu.edu

Reasons For Adapting Single Wire Method Simplicity of Operation Low Cost Easy Insulation Coating Easy Construction Design Optimized www.kostic.niu.edu

Selected Design Parameters Size of the wire (i.e., Wire radius) Type of insulation coating Length of the wire Sample size (length and radius of the cell) Selected Design Parameters Wire Diameter 50.8 µm Teflon Insulation coating thickness 25.4 µm Measured length of wire (after fabrication) is 0.1484 m Diameter of bounding wall is 0.0144 m Length of sample is 0.165 m www.kostic.niu.edu

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www.kostic.niu.edu Fig 2: Cross-sectional front view of improved transient hot-wire thermal Conductivity Cell

Fig 2: Top half cross-sectional front view of transient hot-wire thermal conductivity cell www.kostic.niu.edu

www.kostic.niu.edu Fig 3: Bottom half cross-sectional front view of transient hot-wire thermal conductivity cell

Fig 4: Cross sectional top view of the hot-wire cell at the middle www.kostic.niu.edu

Fig 5: Isometric view of transient hot-wire thermal conductivity cell www.kostic.niu.edu Fig 5: Isometric view of transient hot-wire thermal conductivity cell

www.kostic.niu.edu Fig 6: Left-side view of transient hot-wire thermal conductivity cell without the outer cell, base plate and protection pins

Fig 7: Calibration position of the hot-wire cell www.kostic.niu.edu Fig 7: Calibration position of the hot-wire cell

Spring Assembly = 0.0056 m = 0.1997 N Where, ΔZcal Zcal ΔZ0 (1) Spring Rod (2) Locking Nut Cell Cap (3) Tension Spring (4) Sliding Tube Fwa Spring Constant ζs Initial Spring Force Fsi Spring Assembly Where, Weight of spring rod,W1 = 0.00708 N Weight of locking nut, W2 = 0.1762 N Weight of tension spring,W3 = 0.0115 N Weight of sliding tube,W4 = 0.00490 N = 0.1997 N = 0.0056 m www.kostic.niu.edu

www.kostic.niu.edu Fig 8: Fabricated transient hot-wire thermal conductivity apparatus cell

Instrumentation www.kostic.niu.edu Figure 5.1 Schematics of electrical circuit with data acquisition system

Measurement Procedure The wire is heated with electrical constant power supply at step time The wire simultaneously serves as the heating element and as the temperature sensor The change in resistance of the wire due to heating is measured in time using a Wheatstone bridge circuit The temperature increase of the wire is determined from its change in resistance Thermal conductivity is determined from the heating power and the slope of temperature change in logarithmic time www.kostic.niu.edu

Signal Analysis Bridge Balance Resistance of the hot wire The bridge voltage output The Resistance change of Hot-Wire www.kostic.niu.edu

The Temperature change of Hot-Wire The Voltage Drop Across the Hot-Wire Heat Flux per Unit Length at any Instant of Time Thermal Conductivity www.kostic.niu.edu

Computerized Data Acquisition Data acquisition hardware and software are optimized to minimize signal noise and enhance gathering and processing of useful data Types of Data Measured Bridge voltage output Bridge voltage input Hot-wire Voltage Temperature of fluid Programming in LabVIEW A program has been written in LabVIEW application software to automatically calculate thermal conductivity www.kostic.niu.edu

Data Acquisition Hardware PCI – 6024E, Multifunctional DAQ Board (E–series family, PCI, PCMCIA bus, 16 single-ended/ 8 differential channel analog inputs, 12 bit input resolution, 200 kS/s maximum sampling rate, ± 0.05 V to ± 10 V input range, 2 analog inputs, 12 bit output resolution, 10 kSamples/s output range, 8 digital I/O, two 24 bit counter timer, digital trigger) SCXI – 1000, 4 Slot Signal Conditioning Chassis (shielded enclosure for SCXI module, low – noise environment for signal conditioning, forced air cooling, timing circuit) SCXI – 1102, 32 Differential Channel Thermocouple Input Module (programmatic input range of ± 100 mV to ± 10 V per channel, overall gain of 1 – 100, hardware scanning of cold junction sensor, 2 Hz low pass filtering per channel, relay multiplexer, over voltage protection of ± 42 V, 333 kS/s maximum sampling rate, 0-50 ºC operation environment temperature) SCXI – 1303, 32 Channel Isothermal Terminal Block for Thermocouple modules (SCXI front end mountable terminal block for SCXI-1100 and SCXI-1102/B/C, cold junction compensation sensor, open-thermocouple detection circuitry, isothermal construction for minimizing errors due to thermal gradient, cold junction accuracy for 15-35 ºC is 0.5 ºC and for 0-15 ºC & 25-50 ºC is 0.85 ºC, repeatability is 0.35 ºC) www.kostic.niu.edu

Data Acquisition Hardware SCXI – 1122, 16 Differential Channel Isolated Universal Input Module (DC input coupling, nominal range ± 250 V to ± 5 mV with overall gain of 0.01 to 2000, over voltage protection at 250 Vrms, maximum working voltage in each input should remain with 480 Vrms of ground and 250 Vrms of any other channel, cold junction compensation, bridge compensation, isolated voltage and current excitation, low pass filter setting at 4 kHz or 4 Hz, shunt calibration, 16 relay multiplexer, 100 Samples/s (at 4 kHz filter) and 1 Sample/s (at 4 Hz filter), two 3.333 V excitation level sources) SCXI – 1322, Shielded Temperature Sensor Terminal Block (SCXI front end mountable terminal block for SCXI -1122, on board cold junction sensor) SCXI – 1349, Shielded Cable Assembly (adapter to connect SCXI systems to plug-in data acquisition devices, mounting bracket for secure connection to the SCXI chassis) SH68-68-EP, Noise Rejecting, Shielded Cable (Connects 68-pin E Series devices (not DAQ cards) to 68-pin accessories, individually shielded analog twisted pairs for reduced crosstalk with high-speed boards) www.kostic.niu.edu

www.kostic.niu.edu Figure 5.3: LabVIEW Program Algorithm for Thermal Conductivity Measurement

Calibration Reference Temperature Two Standard Fluids Ethylene Glycol and Water Reference Temperature Resistances of the Wheatstone bridge circuit are measured as , = 2270.6 Ω = 0.1484 m = 2161.1 Ω = 7.715 Ω Where, = 8.106 Ω = 0.02652 Ω/°C is the the slope of dRw vs T www.kostic.niu.edu = 8.22 Ω

for ethylene glycol and distilled water Figure 6.1: Wire temperature change against time (in logarithmic scale) for ethylene glycol and distilled water www.kostic.niu.edu

www.kostic.niu.edu Figure 6.2: Heat input per unit length against time (for ethylene glycol and water)

Figure 6.3: Calibration data from time (1 s – 10 s), shows the selected time range for data reduction as 2s – 6 s, for ethylene glycol and water www.kostic.niu.edu

Ethylene glycol, shows the bias and precision error in measurement Figure 6.4: Results of repeatability measurement of thermal conductivity for Ethylene glycol, shows the bias and precision error in measurement www.kostic.niu.edu

for distilled water, shows the bias and precision error in measurement Figure 6.5: Results of repeatability measurement of thermal conductivity for distilled water, shows the bias and precision error in measurement www.kostic.niu.edu

Calibration Results Table 6.1: Uncertainty in repeatability of measured thermal conductivity Fluid Reference [W/m°C] Measured Bias Error Precision Error (95 %) Uncertainty Ethylene Glycol (32.5 °C) 0.254 0.253 - 0.395 % 2.03 % 2.06 % Distilled water (~ 26 °C) 0.612 0.619 1.2 % 2.23 % 2.52 % www.kostic.niu.edu

Uncertainty in Thermal Conductivity Rearranging in terms of the measured resistance change in the wire Uncertainty www.kostic.niu.edu

Uncertainty in Heat Input per Unit Length is the precision error in the average heat input per unit length Uncertainty in Wire Voltage www.kostic.niu.edu

Uncertainty in Total Resistance Change Uncertainty in Measured Bridge Voltage Input Uncertainty in Measured Bridge Voltage Output www.kostic.niu.edu

Uncertainty in Resistances Uncertainty in Multimeter Uncertainty in Resistance R1 Uncertainty in Resistance R2 Uncertainty in Resistance R3 Uncertainty in Resistance R3 www.kostic.niu.edu

Uncertainty in Temperature Coefficient of Resistance www.kostic.niu.edu Figure 6.7 Calibration of Temperature Coefficient of Resistance of Teflon Coated Platinum Hot-Wire

Uncertainty in Length of Hot-Wire Uncertainty in Slope of Total Resistance Change against Logarithmic Time www.kostic.niu.edu

Table 7.2: Percentage uncertainties Uncertainty (%) 1.629 2.274 1.627 0.231 3.245 www.kostic.niu.edu

Nanofluid thermal conductivity Measurement Nanoparticles: Copper, particle size 35 nm Base Fluid: Ethylene glycol and Water Concentration: 1 volumetric % Physical Stabilization: Ultrasonication www.kostic.niu.edu

Copper in Ethylene Glycol Nanofluid www.kostic.niu.edu Figure 7.1: Nanofluid thermal conductivity measurement of 1 vol % of copper in ethylene glycol

Copper In Water Nanofluid www.kostic.niu.edu Figure 7.2: Nanofluid thermal conductivity measurement of 1 vol % of copper in water

Improvements in Design Overall volume of the cell after fabrication is 35 ml Four wire arrangement to measure voltage drop independently from power wiring Incorporated a spring to provide a uniform tension and avoid any slackness due to expansion Effective off-centering mechanical design provides additional room for wiring and thermocouples Three thermocouples to verify the uniformity of the fluid temperature Electrical connection junctions are arranged on the cell for flexibility in connections and handling Boundary induced errors are minimized www.kostic.niu.edu

Conclusion Designed and Fabricated a Hot-wire cell with improvements Designed and Fabricated a Wheatstone bridge for Hot-wire cell Optimized Data Acquisition Hardware Developed a LabVIEW Program for Measuring Thermal Conductivity Calibrated the Apparatus with Standard Fluids www.kostic.niu.edu

Conclusion Bias Error is within 1.5 % Precision Error is within 2.5 % Total Uncertainty within 3.5 % at 95 % Probability Enhancement in Thermal Conductivity with Copper in Ethylene glycol is 13 % Enhancement in Thermal Conductivity with Copper in Water is 16 % www.kostic.niu.edu

RECOMMENDATIONS The uncertainty analysis shows that the resistors are the major contributors of error. This error can be reduced by using very high precision resistors with extremely small temperature coefficient of resistance. In the present study, temperature coefficient of resistance was determined through calibration over limited temperature range. Precise calibration under well controlled conditions with a larger temperature range would be beneficial. At present, the resistances are manually measured. This process can be automated in future. The data acquisition and LabVIEW® can be programmed to evaluate curvature of temperature versus logarithmic-time dependence (at initial heat-capacity and later convection non-linear regions), and automate evaluation if linear range relevant for thermal conductivity measurement. The hot-wire tension can be more accurately controlled using a micrometer in place of the fixed calibration gauge. www.kostic.niu.edu

Acknowledgements The authors acknowledge support by National Science Foundation (Grant No. CBET-0741078). The authors are also grateful for help in mechanical design and fabrication to Mr. Al Metzger, instrument maker and technician supervisor at NIU. www.kostic.niu.edu

Thank You www.kostic.niu.edu