A Multidisciplinary Design Optimization Tool for Spacecraft Equipment Layout Conception

Abstract

One issue the design team has to face in the process of building a new spacecraft, is to define its mechanical and electrical architecture. The choice of where to place the spacecraft´s electronic equipment is a complex task, since it involves simultaneously many factors, such as the spacecraft´s required position of center of mass, moments of inertia, equipment heat dissipation, integration and servicing issues, among others. Since this is a multidisciplinary task, the early positioning of the spacecraft´s equipment is usually done "manually" by a group of system engineers, heavily based on their experience. It is an interactive process that takes time and hence, as soon as a feasible design is found, it becomes the baseline. This precludes a broader exploration of the design space, which may lead to a suboptimal solution, or worse to a design that will have to be modified later. Recently, it has been shown the potential benefits of automating the process of spacecraft´s equipment layout using optimization techniques. In this paper, a prototype of an Excel ® based tool for multidisciplinary spacecraft equipment layout conception is described. Provided the geometric dimensions, mass and heat dissipation of the equipment, and the available positioning area, the tool can automatically generate many possible trade-off solutions for the layout. It allows the user to set specific equipment to specific areas of positioning, and different combinations of objective functions can be used to drive the design. The features of the tool are shown in a simplified three dimensional problem.

A Scalable Test Suite for Continuous Dynamic Multiobjective Optimization

“…SDP captures a number of real-world features. Examples include but not limited to the following applications: Electromagnetic micromirrors [38], crop growth [40], railway rescheduling [9], dynamic subset sum [42], speed reducer model [51], pressure vessel model [51], greenhouse control [48], predictive control [4], weapon selection & planning [46], PID control [10], unstable plant control [17], selfpaced learning [28], spacecraft equipment layout [27], distance minimisation [56], job shop scheduling [44], engine calibration [32], and water distribution systems [39].…”

Design of a linear time-invariant control system based on a multiobjective optimization approach

“…A comparison analysis among two multiobjective genetic algorithms applied to linear control design problems is presented by Sanchez et al (2008). We can also find in the literature multiobjective optimization techniques applied to space mission problems (Luo et al 2007;Moradi et al 2010;Ober-Blobaum et al 2012;Rocco et al 2013;Chagas et al 2014;Lau et al 2014).…”

An adaptive artificial neural network-based generative design method for layout designs

“…To demonstrate the performance of the proposed approach, two types of heat source layout design problems were solved using the proposed method. Such problems are frequently encountered in the thermal management of electronic devices/systems [17][18][19][20] and satellite systems [21,22]. Due to the large design space, efficient design methods are in great demand.…”