Considering structural design at both the macro- and mesoscale can result in novel and non-intuitive solutions, especially for applications in which there exist multiple performance criteria and/or constraints across multiple physical fields. In such an approach, it is crucial that the bounds of the design space at the mesoscale are well-defined such that the response of the structure at the macroscale remains feasible. Previous work has demonstrated the use of radial basis function (RBF) interpolations to generate N-dimensional constraint surfaces using optimal responses from a single Pareto frontier obtained via an initial optimization study that considers mesoscale structural topologies generated using a parametric L-system approach. However, it has been determined that the responses from a single Pareto frontier allow for the RBF constraints to extrapolate into areas that remain infeasible and are thus inadequate to fully define the bounds of the design space. This work will explore the extension of this approach to consider the 2N Pareto frontiers that exist for a given problem and demonstrate that they result in more rigorous material property constraints. This method will then be applied to an academic example that considers both structural and thermal boundary conditions, and the effects of both the material property constraints and trade-offs between the two sets of boundary conditions will be detailed.