The word "smeared" refers to a modeling technique applied to stiffened panels in which the representative stiffnesses of each stiffener is "smeared" into the overall panel stiffness formulation (ABD Matrix). This is done by extending the assumptions of Classic Lamination Theory (CLT), namely: plane sections remain in-plane after bending. For more information, see Panel Stiffness Formulation.
Smeared Stiffened Panels are particularly useful for preliminary trade studies and Sizing. Compared to discretely modeling stiffeners in the FEM, smeared models are much easier to construct. There is less labor involved in meshing because the grids do not have to be aligned with the stiffener spacing. These models are typically a lot more coarse, and therefore also see benefits when it comes to FEA Solve and HyperX Size times.
There's also no change in the HyperX Sizing and Analysis workflow between Smeared Stiffened Panels and simple panel designs. That means you can easily swap all designs and dimensions on the fly, even allowing multiple panel designs to be considered at once, without remeshing.
In order to model this Stiffened Panel configuration, a single plane of shell elements is meshed at the mid-plane of the top facesheet (no shell offsets). The element density is coarse and the element size is independent of the stiffener spacing. The Material x-axis is aligned with the stiffener direction (orange arrows) and the element normal directions are pointing away from the stiffeners (blue arrows).
In HyperX, Smeared Stiffened Panels are particularly useful for preliminary trade studies and Sizing. Since the models consist of only 2D shells each property is treated as a single Zone, which can be assigned any Stiffened Panel Design Property. These design concepts can then be traded without having to update the model - allowing you to easily swap designs and dimensions on the fly.
Also, since there are no stiffeners physically present in the mesh, all design variables are open - including stiffener spacing. This allows you to start your optimization with a clean slate and truly drive the design towards the lightest weight solution, rather than potentially locking design variables too early.