Optimization of Cost Subject to Uncertainty Constraints in Experimental Fluid Flow and Heat Transfer

Uncertainty analysis in the initial stages of any experimental work is essential in obtaining high-quality data. It insures that the proposed experiment has been thoroughly planned, and that the quantities to be calculated from the experimental measurements will be known with reasonable accuracy and precision. While an uncertainty analysis helps insure reliable results, there is another equally significant aspect in the experimental planning stage: minimization of experimental equipment expenses. A method is presented here in which these two essential experimental elements are combined and viewed as an optimization problem for systematic examination. The analysis allows a systematic search for the least expensive combination of experimental equipment that will give the desired accuracy of results. For the numerical solution the Sequential Gradient Restoration Algorithm (SGRA) is selected. A typical experimental fluid flow and heat transfer problem is given, demonstrating the analysis and numerical solution.