With the simulation of engineering processes via numerical methods on the rise comes the need for a quantitative measure of the agreement between computational results and experimental measurements. The use of quantitative methods in the comparison of the results of numerical and experimental analyses supersedes the traditional qualitative approach. In the present paper, the importance of the role of modeling assumptions in a verification and validation effort is illustrated through a mesoscale combustor example. The various types of uncertainties encountered in the experimentation and numerical simulation are investigated. Through the investigation the initial modeling assumptions proved to be insufficient, producing a comparison error outside of the acceptable range. Thus, the modeling assumptions were sequentially revised, minimizing the comparison error and producing a successful verification and validation effort.