ACT is able to provide insight into acquisition, operational, and life-cycle affordability early in program formulation prior to a commitment of architecture, or anytime during the program to change systems or subsystems. ACT analyzes different systems or architecture configurations for affordability that allows for a comparison of total life-cycle cost, annual affordability, cost per pound, cost per seat, cost per flight (average), and total payload mass throughput. Although ACT is not a deterministic model, it does use characteristics (parametric factors) of the architectures/systems being compared to produce important system outcomes (figures-of-merit). The outcome figures-of-merit provide the designer with information on the relative affordability of different configurations.

ACT is spreadsheet-based and contains a set of algorithms that processes system configuration and characteristics to a measure of system affordability. Parametric factors are derived from quantifiable data about each system configuration’s attributes. An initial algorithm converts quantifiable system configuration and characteristics data into a parametric factor for architecture/system complexity. The next set of ACT algorithms processes the complexity into system affordability figures-ofmerit. These algorithms are initialized using known space transportation data to “anchor” embedded values in the algorithms. While the Space Shuttle was initially used for the comparisons, a database of other anchors is envisioned.

The algorithms allow the comparison of standard processes embedded with mathematically consistent values. This will not necessarily produce an exact forecast (deterministic cost number), but instead provide consistent figures-of-merit suitable for surfacing more affordable and productive alternatives.

ACT is scalable in that it can compare architectural design concepts of largescale systems (elements) down to subsystems. Although the configuration of these systems may be vastly different, ACT can make functional comparisons based on multiple system attributes.

This work was done by Carey McCleskey, Timothy Bollo, and Jerry Garcia of Kennedy Space Center. For more information, contact the Kennedy Space Center Technology Transfer Office at (321) 867-5033. KSC-13714


NASA Tech Briefs Magazine

This article first appeared in the February, 2014 issue of NASA Tech Briefs Magazine.

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