Gas-dynamic virtual nozzles (GDVNs) play a vital role in delivering biomolecular samples during diffraction measurements at X-ray free-electron laser facilities. Recently, submicrometer resolution capabilities of two-photon polymerization 3D printing techniques opened the possibility to quickly fabricate gas-dynamic virtual nozzles with practically any geometry. In our previous work, we exploited this capability to print asymmetric gas-dynamic virtual nozzles that outperformed conventional symmetric designs, which naturally leads to the question of how to identify the optimal gas-dynamic virtual nozzle geometry. In this work, we develop a 3D computational fluid dynamics pipeline to investigate how the characteristics of microjets are affected by gas-dynamic virtual nozzle geometry, which will allow for further geometry optimizations and explorations. We used open-source software (OpenFOAM) and an efficient geometric volume-of-fluid method (isoAdvector) to affordably and accurately predict jet properties for different nozzle geometries. Computational resources were minimized by utilizing adaptive mesh refinement. The numerical simulation results showed acceptable agreement with the experimental data, with a relative error of about 10% for our test cases that compared bell- and cone-shaped sheath-gas cavities. In these test cases, we used a relatively low sheath gas flow rate (6 mg/min), but future work including the implementation of compressible flows will enable the investigation of higher flow rates and the study of asymmetric drip-to-jet transitions.