Optimization of Inflatable Spacecraft Interior Volume Using Constraints Driven Design

Over the past two decades, the emergence of mature associative geometry modeling tools and the related sophistication in associated manufacturing processes has enabled the design and realization of complex, nonlinear structures. To demonstrate the use of intelligent associative models, the design team developed an iterative method for refining the shell and interior design of surface endoskeletal inflatable modules (SEIM). The salient features of the design method are: the use of a custom shape-finding mathematical model written in the Processing integrated development environment (IDE) to determine the correct inflated shape of the shell; a 3D parametric model of the interior, built using the Grasshopper plugin for Rhinoceros 3D by Robert McNeel & Associates; and a semi-automated two-way transfer of data between the design and analysis tools. This paper presents preliminary results of the design method’s application to the optimization of the habitat version of SEIM. Here the independent variable is the inflatable shell geometry, which is controlled by the length of the structural strands in the two principle directions. The dependant variable is the ratio of floor area with a minimum clear height of 2.15 meters to the total available floor area. Fixed parameters are the geometry of the rigid frame and the stowed volume inside the launch platform. The parametric model allows rapid evaluation of the quality of the habitable spaces for a number of shell geometries.