TIETRONIX SOFTWARE INC — National Aeronautics and Space Administration SBIR Phase I: S5

TIETRONIX SOFTWARE INC — SBIR Phase I award from National Aeronautics and Space Administration.

Amount
$124,927
Agency
National Aeronautics and Space Administration
Program / Phase
SBIR · Phase I
Topic
S5
Solicitation
SBIR_19_P1
NAICS
Place of performance
TX
Period
2019-08-19 → 2020-02-18

Description

As Space systems become more complex and missionsrsquo; objectives become more challenging, with combination of advanced instrumentation, robotic systems and manned spacecraft, there is a clear need to rely on effective tools for performing trade evaluations in a cost-effective way. Currently there are model-based approaches used to develop system design. There is not a process for how to use model-based technology to conduct trade evaluations nor a cohesive toolset that combines the multiple analysis methods used to support trade analysis. Our proposed concept is to provide a model-based process and tool-suite that will support end to end system design trade evaluations, design optimizations and reporting. The proposed tool suite will use model-based system engineering techniques and visuals with a mix of traditional reporting elements: tables, graphs, etc. Our proposed innovation will define a trade space modeling methodology, provide a trade evaluation tool that will run analyses and extract results in a trade study report (with visuals and charts for ease of comparison) and displays results in an interactive user interface for optimization support. Tietronix has extensive experience with model-based systems engineering and fault management engineering that we will leverage. Our concept will provide an environment to integrate multiple evaluation methods into one. The tool suite will reduce the amount of effort to perform a trade evaluation by: 1. minimizing the number of tools used to conduct analysis, 2. auto-generating trade study reports from the model, and 3. allowing optimization capability within the tool to support multiple runs.