This thesis presents an overview of recent changes that have been made to the Sequentially Optimized Meshfree Approximation (SOMA) and provides a proof of concept for a penalty method algorithm for coupling experimental data with a computational fluid dynamics (CFD) solver. The penalty method provides a means to apply experimental data to improve SOMA's convergence rate and time to convergence. Using the driven cavity problem as validation, approximations produced using this adaptation are shown. The results successfully reproduces the flow from which the data was taken creating a means of using limited experimental data to generate a complete picture of a simulation domain. Flexibility in data type, location, and quantity are demonstrated as well as the effects of experimental error on the results and a means of negating it.