A Modeling Framework for Applying Discrete Optimization to System Architecture Selection and Application to In-Situ Resource Utilization

Abstract

This paper presents an approach to apply optimization to the selection of a system architecture. Early-stage design decisions that define the subsystem and component technologies that comprise a system architecture are often made with information generated from a limited number of trade studies and a historical background. These decisions can lock in a design too early, resulting in a sub-optimal or even infeasible design. Decisions for systems that have little or no historical background, such as lunar in-situ resource utilization (ISRU) systems, have only analyses and tests to be based on. To enable a wider search of the design space, a modeling framework is discussed that decomposes a system in a hierarchical fashion to describe primary subsystem functions and their technology implementation alternatives. This framework allows a system model to be built that captures all of the subsystem technology alternatives in one reconfigurable model for which the categorical, discrete technology decisions can be treated as design variables in an optimization routine. The NASA ISRU System Model follows this framework and is used as an application of system architecture optimization. A genetic algorithm is used to explore both the discrete and continuous design space of the model. Because the current ISRU System Model has a small set of discrete variables, the performance and computational cost of the genetic algorithm search are compared to a previously developed ISRU optimization scheme that involves full enumeration of the discrete variables followed by gradient-based optimization with the continuous variables. The initial tests of the genetic algorithm approach provide comparable results to the previously used approach, requiring 5100 function evaluations compared to a range of 4800-10,000 function evaluations with the enumeration methods.

Architecture decisions in different product classes for complex products

“…While much design research has been carried out into the creation of design concepts through experimental studies or generative systems and modeling methods for both requirements and functional modeling, the process of designing the system architecture of complex products in industry is not yet clearly identified or understood. Based on our own case studies and those published in the literature (Chepko et al, 2008; Bonjour et al, 2009; Albers et al, 2011; Moullec et al, 2013), this paper will argue that there is huge variation in the process of creating a system architecture and the decisions required to define a system architecture, as well as in the support that designers require to do so. The system architecture of a highly innovative one-off product, such as a space shuttle where new technology is employed to meet newly identified functions, is very different from that of mass product incremental products like traditional cars.…”

Hybrid Environmental Control System Integrated Modeling Trade Study Analysis for Commercial Aviation

“…For this reason DLO is done and often trade studies are conducted to study various options. The work by Chepko et al [43] outline the implantation of this type of optimization using a Genetic Algorithm applied to an in-situ resource utilization system model with nine primary architectures.…”

Generalized Multicommodity Network Flow Model for the Earth–Moon–Mars Logistics System

“…Various lunar ISRU systems have been proposed such as hydrogen reduction, methane carbothermal reduction, molten electrolysis (electrowinning), volatile extraction, and polar water ice extraction [7][8][9][10][11][12]. ISRU options on Mars include the Sabatier reaction, reverse water gas shift reaction, and atmosphere electrolysis.…”