Before we can perform meaningful heat transfer experiments, we must first ensure that our measurements are accurate. Temperature is one of the most fundamental and frequently measured quantities in thermal sciences, and yet every temperature sensor introduces some degree of error. These errors may stem from physical properties of the sensor, environmental interference, limitations in calibration, or misinterpretation of the output.
This lab focuses on two key aspects of experimental thermal systems: sensor calibration and lumped-parameter modeling. First, we will calibrate a range of temperature sensors—a thermocouple, an infrared thermometer, a platinum RTD, and even an analog alcohol thermometer—against a temperature derived from a barometric reference and the known boiling point of water. Calibration involves comparing the measured values to a known standard and estimating systematic offsets or correction factors. You'll observe how environmental conditions (like emissivity settings or measurement through glass) can significantly impact readings, especially with non-contact sensors.
After calibration, you will observe the cooling of a beaker of water and apply the correction factors to your measurements. From this cooling curve, you will model the system as a lumped thermal capacitance connected to the ambient environment via a thermal resistance. This is a version of Newton's law of cooling and allows us to estimate important system parameters: the thermal resistance \(R\) and cooling time constant \(\tau\).
The goal of the following lab exercise is not only to produce clean data, but also to understand and model the physical processes governing thermal behavior—and to do so with attention to both instrumentation and model fidelity.