Spatial discretization with NURBS meshes is increasingly being used in computational analysis, including computational flow analysis with complex geometries. In flow analysis, compared to standard discretization methods, isogeometric discretization provides more accurate representation of the solid surfaces and increased accuracy in the flow solution. The Space-Time Computational Analysis (STCA), where the core method is the ST Variational Multiscale method, is increasingly relying on the ST Isogeometric Analysis (ST-IGA) as one of its key components, quite often also with IGA basis functions in time. The ST Slip Interface (ST-SI) and ST Topology Change methods are two other key components of the STCA, and complementary nature of all these ST methods makes the STCA powerful and practical. To make the ST-IGA use, and in a wider context the IGA use, even more practical in computational flow analysis with complex geometries, NURBS volume mesh generation needs to be easier and more automated. To that end, we present a general-purpose NURBS mesh generation method. The method is based on multi-block-structured mesh generation with existing techniques, projection of that mesh to a NURBS mesh made of patches that correspond to the blocks, and recovery of the original model surfaces to the extent they are suitable for accurate and robust fluid mechanics computations. It is expected to retain the refinement distribution and element quality of the multi-block-structured mesh that we start with. The flexibility of discretization with the general-purpose mesh generation is supplemented with the ST-SI method, which allows, without loss of accuracy, C−1 continuity between NURBS patches and thus removes the matching requirement between the patches. We present mesh-quality performance studies for 2D and 3D meshes, including those for complex models, and test computation for a turbocharger turbine and exhaust manifold. These demonstrate that the general-purpose mesh generation method proposed makes the IGA use in computational flow analysis even more practical.